2022/11/30 - AWS Glue - 16 new 8 updated api methods
Changes This release adds support for AWS Glue Data Quality, which helps you evaluate and monitor the quality of your data and includes the API for creating, deleting, or updating data quality rulesets, runs and evaluations.
Cancels the specified recommendation run that was being used to generate rules.
See also: AWS API Documentation
Request Syntax
client.cancel_data_quality_rule_recommendation_run(
RunId='string'
)
string
[REQUIRED]
The unique run identifier associated with this run.
dict
Response Syntax
{}
Response Structure
(dict) --
Deletes a data quality ruleset.
See also: AWS API Documentation
Request Syntax
client.delete_data_quality_ruleset(
Name='string'
)
string
[REQUIRED]
A name for the data quality ruleset.
dict
Response Syntax
{}
Response Structure
(dict) --
Once you have a ruleset definition (either recommended or your own), you call this operation to evaluate the ruleset against a data source (Glue table). The evaluation computes results which you can retrieve with the GetDataQualityResult API.
See also: AWS API Documentation
Request Syntax
client.start_data_quality_ruleset_evaluation_run(
DataSource={
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
Role='string',
NumberOfWorkers=123,
Timeout=123,
ClientToken='string',
AdditionalRunOptions={
'CloudWatchMetricsEnabled': True|False,
'ResultsS3Prefix': 'string'
},
RulesetNames=[
'string',
]
)
dict
[REQUIRED]
The data source (Glue table) associated with this run.
GlueTable (dict) -- [REQUIRED]
An Glue table.
DatabaseName (string) -- [REQUIRED]
A database name in the Glue Data Catalog.
TableName (string) -- [REQUIRED]
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
string
[REQUIRED]
An IAM role supplied to encrypt the results of the run.
integer
The number of G.1X workers to be used in the run. The default is 5.
integer
The timeout for a run in minutes. This is the maximum time that a run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
string
Used for idempotency and is recommended to be set to a random ID (such as a UUID) to avoid creating or starting multiple instances of the same resource.
dict
Additional run options you can specify for an evaluation run.
CloudWatchMetricsEnabled (boolean) --
Whether or not to enable CloudWatch metrics.
ResultsS3Prefix (string) --
Prefix for Amazon S3 to store results.
list
[REQUIRED]
A list of ruleset names.
(string) --
dict
Response Syntax
{
'RunId': 'string'
}
Response Structure
(dict) --
RunId (string) --
The unique run identifier associated with this run.
Updates the specified data quality ruleset.
See also: AWS API Documentation
Request Syntax
client.update_data_quality_ruleset(
Name='string',
UpdatedName='string',
Description='string',
Ruleset='string'
)
string
[REQUIRED]
The name of the data quality ruleset.
string
The new name of the ruleset, if you are renaming it.
string
A description of the ruleset.
string
A Data Quality Definition Language (DQDL) ruleset. For more information, see the Glue developer guide.
dict
Response Syntax
{
'Name': 'string',
'Description': 'string',
'Ruleset': 'string'
}
Response Structure
(dict) --
Name (string) --
The name of the data quality ruleset.
Description (string) --
A description of the ruleset.
Ruleset (string) --
A Data Quality Definition Language (DQDL) ruleset. For more information, see the Glue developer guide.
Returns an existing ruleset by identifier or name.
See also: AWS API Documentation
Request Syntax
client.get_data_quality_ruleset(
Name='string'
)
string
[REQUIRED]
The name of the ruleset.
dict
Response Syntax
{
'Name': 'string',
'Description': 'string',
'Ruleset': 'string',
'TargetTable': {
'TableName': 'string',
'DatabaseName': 'string'
},
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'RecommendationRunId': 'string'
}
Response Structure
(dict) --
Name (string) --
The name of the ruleset.
Description (string) --
A description of the ruleset.
Ruleset (string) --
A Data Quality Definition Language (DQDL) ruleset. For more information, see the Glue developer guide.
TargetTable (dict) --
The name and database name of the target table.
TableName (string) --
The name of the Glue table.
DatabaseName (string) --
The name of the database where the Glue table exists.
CreatedOn (datetime) --
A timestamp. The time and date that this data quality ruleset was created.
LastModifiedOn (datetime) --
A timestamp. The last point in time when this data quality ruleset was modified.
RecommendationRunId (string) --
When a ruleset was created from a recommendation run, this run ID is generated to link the two together.
Retrieves the result of a data quality rule evaluation.
See also: AWS API Documentation
Request Syntax
client.get_data_quality_result(
ResultId='string'
)
string
[REQUIRED]
A unique result ID for the data quality result.
dict
Response Syntax
{
'ResultId': 'string',
'Score': 123.0,
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'RulesetName': 'string',
'EvaluationContext': 'string',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobName': 'string',
'JobRunId': 'string',
'RulesetEvaluationRunId': 'string',
'RuleResults': [
{
'Name': 'string',
'Description': 'string',
'EvaluationMessage': 'string',
'Result': 'PASS'|'FAIL'|'ERROR'
},
]
}
Response Structure
(dict) --
ResultId (string) --
A unique result ID for the data quality result.
Score (float) --
An aggregate data quality score. Represents the ratio of rules that passed to the total number of rules.
DataSource (dict) --
The table associated with the data quality result, if any.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
RulesetName (string) --
The name of the ruleset associated with the data quality result.
EvaluationContext (string) --
In the context of a job in Glue Studio, each node in the canvas is typically assigned some sort of name and data quality nodes will have names. In the case of multiple nodes, the evaluationContext can differentiate the nodes.
StartedOn (datetime) --
The date and time when the run for this data quality result started.
CompletedOn (datetime) --
The date and time when the run for this data quality result was completed.
JobName (string) --
The job name associated with the data quality result, if any.
JobRunId (string) --
The job run ID associated with the data quality result, if any.
RulesetEvaluationRunId (string) --
The unique run ID associated with the ruleset evaluation.
RuleResults (list) --
A list of DataQualityRuleResult objects representing the results for each rule.
(dict) --
Describes the result of the evaluation of a data quality rule.
Name (string) --
The name of the data quality rule.
Description (string) --
A description of the data quality rule.
EvaluationMessage (string) --
An evaluation message.
Result (string) --
A pass or fail status for the rule.
Cancels a run where a ruleset is being evaluated against a data source.
See also: AWS API Documentation
Request Syntax
client.cancel_data_quality_ruleset_evaluation_run(
RunId='string'
)
string
[REQUIRED]
The unique run identifier associated with this run.
dict
Response Syntax
{}
Response Structure
(dict) --
Lists the recommendation runs meeting the filter criteria.
See also: AWS API Documentation
Request Syntax
client.list_data_quality_rule_recommendation_runs(
Filter={
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'StartedBefore': datetime(2015, 1, 1),
'StartedAfter': datetime(2015, 1, 1)
},
NextToken='string',
MaxResults=123
)
dict
The filter criteria.
DataSource (dict) -- [REQUIRED]
Filter based on a specified data source (Glue table).
GlueTable (dict) -- [REQUIRED]
An Glue table.
DatabaseName (string) -- [REQUIRED]
A database name in the Glue Data Catalog.
TableName (string) -- [REQUIRED]
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
StartedBefore (datetime) --
Filter based on time for results started before provided time.
StartedAfter (datetime) --
Filter based on time for results started after provided time.
string
A paginated token to offset the results.
integer
The maximum number of results to return.
dict
Response Syntax
{
'Runs': [
{
'RunId': 'string',
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'StartedOn': datetime(2015, 1, 1),
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Runs (list) --
A list of DataQualityRuleRecommendationRunDescription objects.
(dict) --
Describes the result of a data quality rule recommendation run.
RunId (string) --
The unique run identifier associated with this run.
Status (string) --
The status for this run.
StartedOn (datetime) --
The date and time when this run started.
DataSource (dict) --
The data source (Glue table) associated with the recommendation run.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
NextToken (string) --
A pagination token, if more results are available.
Returns a paginated list of rulesets for the specified list of Glue tables.
See also: AWS API Documentation
Request Syntax
client.list_data_quality_rulesets(
NextToken='string',
MaxResults=123,
Filter={
'Name': 'string',
'Description': 'string',
'CreatedBefore': datetime(2015, 1, 1),
'CreatedAfter': datetime(2015, 1, 1),
'LastModifiedBefore': datetime(2015, 1, 1),
'LastModifiedAfter': datetime(2015, 1, 1),
'TargetTable': {
'TableName': 'string',
'DatabaseName': 'string'
}
},
Tags={
'string': 'string'
}
)
string
A paginated token to offset the results.
integer
The maximum number of results to return.
dict
The filter criteria.
Name (string) --
The name of the ruleset filter criteria.
Description (string) --
The description of the ruleset filter criteria.
CreatedBefore (datetime) --
Filter on rulesets created before this date.
CreatedAfter (datetime) --
Filter on rulesets created after this date.
LastModifiedBefore (datetime) --
Filter on rulesets last modified before this date.
LastModifiedAfter (datetime) --
Filter on rulesets last modified after this date.
TargetTable (dict) --
The name and database name of the target table.
TableName (string) -- [REQUIRED]
The name of the Glue table.
DatabaseName (string) -- [REQUIRED]
The name of the database where the Glue table exists.
dict
A list of key-value pair tags.
(string) --
(string) --
dict
Response Syntax
{
'Rulesets': [
{
'Name': 'string',
'Description': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'TargetTable': {
'TableName': 'string',
'DatabaseName': 'string'
},
'RecommendationRunId': 'string',
'RuleCount': 123
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Rulesets (list) --
A paginated list of rulesets for the specified list of Glue tables.
(dict) --
Describes a data quality ruleset returned by GetDataQualityRuleset .
Name (string) --
The name of the data quality ruleset.
Description (string) --
A description of the data quality ruleset.
CreatedOn (datetime) --
The date and time the data quality ruleset was created.
LastModifiedOn (datetime) --
The date and time the data quality ruleset was last modified.
TargetTable (dict) --
An object representing an Glue table.
TableName (string) --
The name of the Glue table.
DatabaseName (string) --
The name of the database where the Glue table exists.
RecommendationRunId (string) --
When a ruleset was created from a recommendation run, this run ID is generated to link the two together.
RuleCount (integer) --
The number of rules in the ruleset.
NextToken (string) --
A pagination token, if more results are available.
Starts a recommendation run that is used to generate rules when you don't know what rules to write. Glue Data Quality analyzes the data and comes up with recommendations for a potential ruleset. You can then triage the ruleset and modify the generated ruleset to your liking.
See also: AWS API Documentation
Request Syntax
client.start_data_quality_rule_recommendation_run(
DataSource={
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
Role='string',
NumberOfWorkers=123,
Timeout=123,
CreatedRulesetName='string',
ClientToken='string'
)
dict
[REQUIRED]
The data source (Glue table) associated with this run.
GlueTable (dict) -- [REQUIRED]
An Glue table.
DatabaseName (string) -- [REQUIRED]
A database name in the Glue Data Catalog.
TableName (string) -- [REQUIRED]
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
string
[REQUIRED]
An IAM role supplied to encrypt the results of the run.
integer
The number of G.1X workers to be used in the run. The default is 5.
integer
The timeout for a run in minutes. This is the maximum time that a run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
string
A name for the ruleset.
string
Used for idempotency and is recommended to be set to a random ID (such as a UUID) to avoid creating or starting multiple instances of the same resource.
dict
Response Syntax
{
'RunId': 'string'
}
Response Structure
(dict) --
RunId (string) --
The unique run identifier associated with this run.
Returns all data quality execution results for your account.
See also: AWS API Documentation
Request Syntax
client.list_data_quality_results(
Filter={
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'JobName': 'string',
'JobRunId': 'string',
'StartedAfter': datetime(2015, 1, 1),
'StartedBefore': datetime(2015, 1, 1)
},
NextToken='string',
MaxResults=123
)
dict
The filter criteria.
DataSource (dict) --
Filter results by the specified data source. For example, retrieving all results for an Glue table.
GlueTable (dict) -- [REQUIRED]
An Glue table.
DatabaseName (string) -- [REQUIRED]
A database name in the Glue Data Catalog.
TableName (string) -- [REQUIRED]
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
JobName (string) --
Filter results by the specified job name.
JobRunId (string) --
Filter results by the specified job run ID.
StartedAfter (datetime) --
Filter results by runs that started after this time.
StartedBefore (datetime) --
Filter results by runs that started before this time.
string
A paginated token to offset the results.
integer
The maximum number of results to return.
dict
Response Syntax
{
'Results': [
{
'ResultId': 'string',
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'JobName': 'string',
'JobRunId': 'string',
'StartedOn': datetime(2015, 1, 1)
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Results (list) --
A list of DataQualityResultDescription objects.
(dict) --
Describes a data quality result.
ResultId (string) --
The unique result ID for this data quality result.
DataSource (dict) --
The table name associated with the data quality result.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
JobName (string) --
The job name associated with the data quality result.
JobRunId (string) --
The job run ID associated with the data quality result.
StartedOn (datetime) --
The time that the run started for this data quality result.
NextToken (string) --
A pagination token, if more results are available.
Gets the specified recommendation run that was used to generate rules.
See also: AWS API Documentation
Request Syntax
client.get_data_quality_rule_recommendation_run(
RunId='string'
)
string
[REQUIRED]
The unique run identifier associated with this run.
dict
Response Syntax
{
'RunId': 'string',
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'Role': 'string',
'NumberOfWorkers': 123,
'Timeout': 123,
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'ErrorString': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ExecutionTime': 123,
'RecommendedRuleset': 'string',
'CreatedRulesetName': 'string'
}
Response Structure
(dict) --
RunId (string) --
The unique run identifier associated with this run.
DataSource (dict) --
The data source (an Glue table) associated with this run.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
Role (string) --
An IAM role supplied to encrypt the results of the run.
NumberOfWorkers (integer) --
The number of G.1X workers to be used in the run. The default is 5.
Timeout (integer) --
The timeout for a run in minutes. This is the maximum time that a run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
Status (string) --
The status for this run.
ErrorString (string) --
The error strings that are associated with the run.
StartedOn (datetime) --
The date and time when this run started.
LastModifiedOn (datetime) --
A timestamp. The last point in time when this data quality rule recommendation run was modified.
CompletedOn (datetime) --
The date and time when this run was completed.
ExecutionTime (integer) --
The amount of time (in seconds) that the run consumed resources.
RecommendedRuleset (string) --
When a start rule recommendation run completes, it creates a recommended ruleset (a set of rules). This member has those rules in Data Quality Definition Language (DQDL) format.
CreatedRulesetName (string) --
The name of the ruleset that was created by the run.
Retrieves a list of data quality results for the specified result IDs.
See also: AWS API Documentation
Request Syntax
client.batch_get_data_quality_result(
ResultIds=[
'string',
]
)
list
[REQUIRED]
A list of unique result IDs for the data quality results.
(string) --
dict
Response Syntax
{
'Results': [
{
'ResultId': 'string',
'Score': 123.0,
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'RulesetName': 'string',
'EvaluationContext': 'string',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobName': 'string',
'JobRunId': 'string',
'RulesetEvaluationRunId': 'string',
'RuleResults': [
{
'Name': 'string',
'Description': 'string',
'EvaluationMessage': 'string',
'Result': 'PASS'|'FAIL'|'ERROR'
},
]
},
],
'ResultsNotFound': [
'string',
]
}
Response Structure
(dict) --
Results (list) --
A list of DataQualityResult objects representing the data quality results.
(dict) --
Describes a data quality result.
ResultId (string) --
A unique result ID for the data quality result.
Score (float) --
An aggregate data quality score. Represents the ratio of rules that passed to the total number of rules.
DataSource (dict) --
The table associated with the data quality result, if any.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
RulesetName (string) --
The name of the ruleset associated with the data quality result.
EvaluationContext (string) --
In the context of a job in Glue Studio, each node in the canvas is typically assigned some sort of name and data quality nodes will have names. In the case of multiple nodes, the evaluationContext can differentiate the nodes.
StartedOn (datetime) --
The date and time when this data quality run started.
CompletedOn (datetime) --
The date and time when this data quality run completed.
JobName (string) --
The job name associated with the data quality result, if any.
JobRunId (string) --
The job run ID associated with the data quality result, if any.
RulesetEvaluationRunId (string) --
The unique run ID for the ruleset evaluation for this data quality result.
RuleResults (list) --
A list of DataQualityRuleResult objects representing the results for each rule.
(dict) --
Describes the result of the evaluation of a data quality rule.
Name (string) --
The name of the data quality rule.
Description (string) --
A description of the data quality rule.
EvaluationMessage (string) --
An evaluation message.
Result (string) --
A pass or fail status for the rule.
ResultsNotFound (list) --
A list of result IDs for which results were not found.
(string) --
Lists all the runs meeting the filter criteria, where a ruleset is evaluated against a data source.
See also: AWS API Documentation
Request Syntax
client.list_data_quality_ruleset_evaluation_runs(
Filter={
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'StartedBefore': datetime(2015, 1, 1),
'StartedAfter': datetime(2015, 1, 1)
},
NextToken='string',
MaxResults=123
)
dict
The filter criteria.
DataSource (dict) -- [REQUIRED]
Filter based on a data source (an Glue table) associated with the run.
GlueTable (dict) -- [REQUIRED]
An Glue table.
DatabaseName (string) -- [REQUIRED]
A database name in the Glue Data Catalog.
TableName (string) -- [REQUIRED]
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
StartedBefore (datetime) --
Filter results by runs that started before this time.
StartedAfter (datetime) --
Filter results by runs that started after this time.
string
A paginated token to offset the results.
integer
The maximum number of results to return.
dict
Response Syntax
{
'Runs': [
{
'RunId': 'string',
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'StartedOn': datetime(2015, 1, 1),
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Runs (list) --
A list of DataQualityRulesetEvaluationRunDescription objects representing data quality ruleset runs.
(dict) --
Describes the result of a data quality ruleset evaluation run.
RunId (string) --
The unique run identifier associated with this run.
Status (string) --
The status for this run.
StartedOn (datetime) --
The date and time when the run started.
DataSource (dict) --
The data source (an Glue table) associated with the run.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
NextToken (string) --
A pagination token, if more results are available.
Creates a data quality ruleset with DQDL rules applied to a specified Glue table.
You create the ruleset using the Data Quality Definition Language (DQDL). For more information, see the Glue developer guide.
See also: AWS API Documentation
Request Syntax
client.create_data_quality_ruleset(
Name='string',
Description='string',
Ruleset='string',
Tags={
'string': 'string'
},
TargetTable={
'TableName': 'string',
'DatabaseName': 'string'
},
ClientToken='string'
)
string
[REQUIRED]
A unique name for the data quality ruleset.
string
A description of the data quality ruleset.
string
[REQUIRED]
A Data Quality Definition Language (DQDL) ruleset. For more information, see the Glue developer guide.
dict
A list of tags applied to the data quality ruleset.
(string) --
(string) --
dict
A target table associated with the data quality ruleset.
TableName (string) -- [REQUIRED]
The name of the Glue table.
DatabaseName (string) -- [REQUIRED]
The name of the database where the Glue table exists.
string
Used for idempotency and is recommended to be set to a random ID (such as a UUID) to avoid creating or starting multiple instances of the same resource.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
A unique name for the data quality ruleset.
Retrieves a specific run where a ruleset is evaluated against a data source.
See also: AWS API Documentation
Request Syntax
client.get_data_quality_ruleset_evaluation_run(
RunId='string'
)
string
[REQUIRED]
The unique run identifier associated with this run.
dict
Response Syntax
{
'RunId': 'string',
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'Role': 'string',
'NumberOfWorkers': 123,
'Timeout': 123,
'AdditionalRunOptions': {
'CloudWatchMetricsEnabled': True|False,
'ResultsS3Prefix': 'string'
},
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'ErrorString': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ExecutionTime': 123,
'RulesetNames': [
'string',
],
'ResultIds': [
'string',
]
}
Response Structure
(dict) --
RunId (string) --
The unique run identifier associated with this run.
DataSource (dict) --
The data source (an Glue table) associated with this evaluation run.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
Role (string) --
An IAM role supplied to encrypt the results of the run.
NumberOfWorkers (integer) --
The number of G.1X workers to be used in the run. The default is 5.
Timeout (integer) --
The timeout for a run in minutes. This is the maximum time that a run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
AdditionalRunOptions (dict) --
Additional run options you can specify for an evaluation run.
CloudWatchMetricsEnabled (boolean) --
Whether or not to enable CloudWatch metrics.
ResultsS3Prefix (string) --
Prefix for Amazon S3 to store results.
Status (string) --
The status for this run.
ErrorString (string) --
The error strings that are associated with the run.
StartedOn (datetime) --
The date and time when this run started.
LastModifiedOn (datetime) --
A timestamp. The last point in time when this data quality rule recommendation run was modified.
CompletedOn (datetime) --
The date and time when this run was completed.
ExecutionTime (integer) --
The amount of time (in seconds) that the run consumed resources.
RulesetNames (list) --
A list of ruleset names for the run.
(string) --
ResultIds (list) --
A list of result IDs for the data quality results for the run.
(string) --
{'Jobs': {'CodeGenConfigurationNodes': {'EvaluateDataQuality': {'Inputs': ['string'],
'Name': 'string',
'Output': 'PrimaryInput '
'| '
'EvaluationResults',
'PublishingOptions': {'CloudWatchMetricsEnabled': 'boolean',
'EvaluationContext': 'string',
'ResultsPublishingEnabled': 'boolean',
'ResultsS3Prefix': 'string'},
'Ruleset': 'string',
'StopJobOnFailureOptions': {'StopJobOnFailureTiming': 'Immediate '
'| '
'AfterDataLoad'}}}}}
Returns a list of resource metadata for a given list of job names. After calling the ListJobs operation, you can call this operation to access the data to which you have been granted permissions. This operation supports all IAM permissions, including permission conditions that uses tags.
See also: AWS API Documentation
Request Syntax
client.batch_get_jobs(
JobNames=[
'string',
]
)
list
[REQUIRED]
A list of job names, which might be the names returned from the ListJobs operation.
(string) --
dict
Response Syntax
{
'Jobs': [
{
'Name': 'string',
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
},
],
'JobsNotFound': [
'string',
]
}
Response Structure
(dict) --
Jobs (list) --
A list of job definitions.
(dict) --
Specifies a job definition.
Name (string) --
The name you assign to this job definition.
Description (string) --
A description of the job.
LogUri (string) --
This field is reserved for future use.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
CreatedOn (datetime) --
The time and date that this job definition was created.
LastModifiedOn (datetime) --
The last point in time when this job definition was modified.
ExecutionProperty (dict) --
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
MaxConcurrentRuns (integer) --
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
Command (dict) --
The JobCommand that runs this job.
Name (string) --
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
ScriptLocation (string) --
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
PythonVersion (string) --
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
DefaultArguments (dict) --
The default arguments for this job, specified as name-value pairs.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
(string) --
(string) --
NonOverridableArguments (dict) --
Non-overridable arguments for this job, specified as name-value pairs.
(string) --
(string) --
Connections (dict) --
The connections used for this job.
Connections (list) --
A list of connections used by the job.
(string) --
MaxRetries (integer) --
The maximum number of times to retry this job after a JobRun fails.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to runs of this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Timeout (integer) --
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
MaxCapacity (float) --
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
When you specify a Python shell job ( JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
When you specify an Apache Spark ETL job ( JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job.
NotificationProperty (dict) --
Specifies configuration properties of a job notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
CodeGenConfigurationNodes (dict) --
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
(string) --
(dict) --
CodeGenConfigurationNode enumerates all valid Node types. One and only one of its member variables can be populated.
AthenaConnectorSource (dict) --
Specifies a connector to an Amazon Athena data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
ConnectionTable (string) --
The name of the table in the data source.
SchemaName (string) --
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
OutputSchemas (list) --
Specifies the data schema for the custom Athena source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
JDBCConnectorSource (dict) --
Specifies a connector to a JDBC data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
FilterPredicate (string) --
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
PartitionColumn (string) --
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
LowerBound (integer) --
The minimum value of partitionColumn that is used to decide partition stride.
UpperBound (integer) --
The maximum value of partitionColumn that is used to decide partition stride.
NumPartitions (integer) --
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
JobBookmarkKeys (list) --
The name of the job bookmark keys on which to sort.
(string) --
JobBookmarkKeysSortOrder (string) --
Specifies an ascending or descending sort order.
DataTypeMapping (dict) --
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
(string) --
(string) --
ConnectionTable (string) --
The name of the table in the data source.
Query (string) --
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
OutputSchemas (list) --
Specifies the data schema for the custom JDBC source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorSource (dict) --
Specifies a connector to an Apache Spark data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies data schema for the custom spark source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogSource (dict) --
Specifies a data store in the Glue Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
RedshiftSource (dict) --
Specifies an Amazon Redshift data store.
Name (string) --
The name of the Amazon Redshift data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
S3CatalogSource (dict) --
Specifies an Amazon S3 data store in the Glue Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
S3CsvSource (dict) --
Specifies a command-separated value (CSV) data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
Separator (string) --
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Escaper (string) --
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
QuoteChar (string) --
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
WithHeader (boolean) --
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
WriteHeader (boolean) --
A Boolean value that specifies whether to write the header to output. The default value is True .
SkipFirst (boolean) --
A Boolean value that specifies whether to skip the first data line. The default value is False .
OptimizePerformance (boolean) --
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
OutputSchemas (list) --
Specifies the data schema for the S3 CSV source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3JsonSource (dict) --
Specifies a JSON data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
JsonPath (string) --
A JsonPath string defining the JSON data.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
OutputSchemas (list) --
Specifies the data schema for the S3 JSON source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3ParquetSource (dict) --
Specifies an Apache Parquet data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
OutputSchemas (list) --
Specifies the data schema for the S3 Parquet source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
RelationalCatalogSource (dict) --
Specifies a Relational database data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
DynamoDBCatalogSource (dict) --
Specifies a DynamoDB data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
JDBCConnectorTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectionTable (string) --
The name of the table in the data target.
ConnectorName (string) --
The name of a connector that will be used.
ConnectionType (string) --
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the JDBC target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorTarget (dict) --
Specifies a target that uses an Apache Spark connector.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) --
The name of a connection for an Apache Spark connector.
ConnectorName (string) --
The name of an Apache Spark connector.
ConnectionType (string) --
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the custom spark target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogTarget (dict) --
Specifies a target that uses a Glue Data Catalog table.
Name (string) --
The name of your data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
Table (string) --
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
RedshiftTarget (dict) --
Specifies a target that uses Amazon Redshift.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
UpsertRedshiftOptions (dict) --
The set of options to configure an upsert operation when writing to a Redshift target.
TableLocation (string) --
The physical location of the Redshift table.
ConnectionName (string) --
The name of the connection to use to write to Redshift.
UpsertKeys (list) --
The keys used to determine whether to perform an update or insert.
(string) --
S3CatalogTarget (dict) --
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) --
The name of the table in the database to write to.
Database (string) --
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
S3GlueParquetTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) --
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
S3DirectTarget (dict) --
Specifies a data target that writes to Amazon S3.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) --
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Format (string) --
Specifies the data output format for the target.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
ApplyMapping (dict) --
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Mapping (list) --
Specifies the mapping of data property keys in the data source to data property keys in the data target.
(dict) --
Specifies the mapping of data property keys.
ToKey (string) --
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
FromPath (list) --
The table or column to be modified.
(string) --
FromType (string) --
The type of the data to be modified.
ToType (string) --
The data type that the data is to be modified to.
Dropped (boolean) --
If true, then the column is removed.
Children (list) --
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
SelectFields (dict) --
Specifies a transform that chooses the data property keys that you want to keep.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
DropFields (dict) --
Specifies a transform that chooses the data property keys that you want to drop.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
RenameField (dict) --
Specifies a transform that renames a single data property key.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
SourcePath (list) --
A JSON path to a variable in the data structure for the source data.
(string) --
TargetPath (list) --
A JSON path to a variable in the data structure for the target data.
(string) --
Spigot (dict) --
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Path (string) --
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Topk (integer) --
Specifies a number of records to write starting from the beginning of the dataset.
Prob (float) --
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Join (dict) --
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
JoinType (string) --
Specifies the type of join to be performed on the datasets.
Columns (list) --
A list of the two columns to be joined.
(dict) --
Specifies a column to be joined.
From (string) --
The column to be joined.
Keys (list) --
The key of the column to be joined.
(list) --
(string) --
SplitFields (dict) --
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
SelectFromCollection (dict) --
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Index (integer) --
The index for the DynamicFrame to be selected.
FillMissingValues (dict) --
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
ImputedPath (string) --
A JSON path to a variable in the data structure for the dataset that is imputed.
FilledPath (string) --
A JSON path to a variable in the data structure for the dataset that is filled.
Filter (dict) --
Specifies a transform that splits a dataset into two, based on a filter condition.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
LogicalOperator (string) --
The operator used to filter rows by comparing the key value to a specified value.
Filters (list) --
Specifies a filter expression.
(dict) --
Specifies a filter expression.
Operation (string) --
The type of operation to perform in the expression.
Negated (boolean) --
Whether the expression is to be negated.
Values (list) --
A list of filter values.
(dict) --
Represents a single entry in the list of values for a FilterExpression .
Type (string) --
The type of filter value.
Value (list) --
The value to be associated.
(string) --
CustomCode (dict) --
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Code (string) --
The custom code that is used to perform the data transformation.
ClassName (string) --
The name defined for the custom code node class.
OutputSchemas (list) --
Specifies the data schema for the custom code transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkSQL (dict) --
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
(string) --
SqlQuery (string) --
A SQL query that must use Spark SQL syntax and return a single data set.
SqlAliases (list) --
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
(dict) --
Represents a single entry in the list of values for SqlAliases .
From (string) --
A table, or a column in a table.
Alias (string) --
A temporary name given to a table, or a column in a table.
OutputSchemas (list) --
Specifies the data schema for the SparkSQL transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
DirectKinesisSource (dict) --
Specifies a direct Amazon Kinesis data source.
Name (string) --
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DirectKafkaSource (dict) --
Specifies an Apache Kafka data store.
Name (string) --
The name of the data store.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKinesisSource (dict) --
Specifies a Kinesis data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) --
The name of the table in the database to read from.
Database (string) --
The name of the database to read from.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKafkaSource (dict) --
Specifies an Apache Kafka data store in the Data Catalog.
Name (string) --
The name of the data store.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) --
The name of the table in the database to read from.
Database (string) --
The name of the database to read from.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DropNullFields (dict) --
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
NullCheckBoxList (dict) --
A structure that represents whether certain values are recognized as null values for removal.
IsEmpty (boolean) --
Specifies that an empty string is considered as a null value.
IsNullString (boolean) --
Specifies that a value spelling out the word 'null' is considered as a null value.
IsNegOne (boolean) --
Specifies that an integer value of -1 is considered as a null value.
NullTextList (list) --
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
(dict) --
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
Value (string) --
The value of the null placeholder.
Datatype (dict) --
The datatype of the value.
Id (string) --
The datatype of the value.
Label (string) --
A label assigned to the datatype.
Merge (dict) --
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Source (string) --
The source DynamicFrame that will be merged with a staging DynamicFrame .
PrimaryKeys (list) --
The list of primary key fields to match records from the source and staging dynamic frames.
(list) --
(string) --
Union (dict) --
Specifies a transform that combines the rows from two or more datasets into a single result.
Name (string) --
The name of the transform node.
Inputs (list) --
The node ID inputs to the transform.
(string) --
UnionType (string) --
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
PIIDetection (dict) --
Specifies a transform that identifies, removes or masks PII data.
Name (string) --
The name of the transform node.
Inputs (list) --
The node ID inputs to the transform.
(string) --
PiiType (string) --
Indicates the type of PIIDetection transform.
EntityTypesToDetect (list) --
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
(string) --
OutputColumnName (string) --
Indicates the output column name that will contain any entity type detected in that row.
SampleFraction (float) --
Indicates the fraction of the data to sample when scanning for PII entities.
ThresholdFraction (float) --
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
MaskValue (string) --
Indicates the value that will replace the detected entity.
Aggregate (dict) --
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
Name (string) --
The name of the transform node.
Inputs (list) --
Specifies the fields and rows to use as inputs for the aggregate transform.
(string) --
Groups (list) --
Specifies the fields to group by.
(list) --
(string) --
Aggs (list) --
Specifies the aggregate functions to be performed on specified fields.
(dict) --
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Column (list) --
Specifies the column on the data set on which the aggregation function will be applied.
(string) --
AggFunc (string) --
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
DropDuplicates (dict) --
Specifies a transform that removes rows of repeating data from a data set.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Columns (list) --
The name of the columns to be merged or removed if repeating.
(list) --
(string) --
GovernedCatalogTarget (dict) --
Specifies a data target that writes to a goverened catalog.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) --
The name of the table in the database to write to.
Database (string) --
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the governed catalog.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
GovernedCatalogSource (dict) --
Specifies a data source in a goverened Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
MicrosoftSQLServerCatalogSource (dict) --
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
MySQLCatalogSource (dict) --
Specifies a MySQL data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
OracleSQLCatalogSource (dict) --
Specifies an Oracle data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
PostgreSQLCatalogSource (dict) --
Specifies a PostgresSQL data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
MicrosoftSQLServerCatalogTarget (dict) --
Specifies a target that uses Microsoft SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
MySQLCatalogTarget (dict) --
Specifies a target that uses MySQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
OracleSQLCatalogTarget (dict) --
Specifies a target that uses Oracle SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
PostgreSQLCatalogTarget (dict) --
Specifies a target that uses Postgres SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
DynamicTransform (dict) --
Specifies a custom visual transform created by a user.
Name (string) --
Specifies the name of the dynamic transform.
TransformName (string) --
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Inputs (list) --
Specifies the inputs for the dynamic transform that are required.
(string) --
Parameters (list) --
Specifies the parameters of the dynamic transform.
(dict) --
Specifies the parameters in the config file of the dynamic transform.
Name (string) --
Specifies the name of the parameter in the config file of the dynamic transform.
Type (string) --
Specifies the parameter type in the config file of the dynamic transform.
ValidationRule (string) --
Specifies the validation rule in the config file of the dynamic transform.
ValidationMessage (string) --
Specifies the validation message in the config file of the dynamic transform.
Value (list) --
Specifies the value of the parameter in the config file of the dynamic transform.
(string) --
ListType (string) --
Specifies the list type of the parameter in the config file of the dynamic transform.
IsOptional (boolean) --
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
FunctionName (string) --
Specifies the name of the function of the dynamic transform.
Path (string) --
Specifies the path of the dynamic transform source and config files.
Version (string) --
This field is not used and will be deprecated in future release.
EvaluateDataQuality (dict) --
Specifies your data quality evaluation criteria.
Name (string) --
The name of the data quality evaluation.
Inputs (list) --
The inputs of your data quality evaluation.
(string) --
Ruleset (string) --
The ruleset for your data quality evaluation.
Output (string) --
The output of your data quality evaluation.
PublishingOptions (dict) --
Options to configure how your results are published.
EvaluationContext (string) --
The context of the evaluation.
ResultsS3Prefix (string) --
The Amazon S3 prefix prepended to the results.
CloudWatchMetricsEnabled (boolean) --
Enable metrics for your data quality results.
ResultsPublishingEnabled (boolean) --
Enable publishing for your data quality results.
StopJobOnFailureOptions (dict) --
Options to configure how your job will stop if your data quality evaluation fails.
StopJobOnFailureTiming (string) --
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
SourceControlDetails (dict) --
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
Provider (string) --
The provider for the remote repository.
Repository (string) --
The name of the remote repository that contains the job artifacts.
Owner (string) --
The owner of the remote repository that contains the job artifacts.
Branch (string) --
An optional branch in the remote repository.
Folder (string) --
An optional folder in the remote repository.
LastCommitId (string) --
The last commit ID for a commit in the remote repository.
AuthStrategy (string) --
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
AuthToken (string) --
The value of an authorization token.
JobsNotFound (list) --
A list of names of jobs not found.
(string) --
{'CodeGenConfigurationNodes': {'EvaluateDataQuality': {'Inputs': ['string'],
'Name': 'string',
'Output': 'PrimaryInput '
'| '
'EvaluationResults',
'PublishingOptions': {'CloudWatchMetricsEnabled': 'boolean',
'EvaluationContext': 'string',
'ResultsPublishingEnabled': 'boolean',
'ResultsS3Prefix': 'string'},
'Ruleset': 'string',
'StopJobOnFailureOptions': {'StopJobOnFailureTiming': 'Immediate '
'| '
'AfterDataLoad'}}}}
Creates a new job definition.
See also: AWS API Documentation
Request Syntax
client.create_job(
Name='string',
Description='string',
LogUri='string',
Role='string',
ExecutionProperty={
'MaxConcurrentRuns': 123
},
Command={
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
DefaultArguments={
'string': 'string'
},
NonOverridableArguments={
'string': 'string'
},
Connections={
'Connections': [
'string',
]
},
MaxRetries=123,
AllocatedCapacity=123,
Timeout=123,
MaxCapacity=123.0,
SecurityConfiguration='string',
Tags={
'string': 'string'
},
NotificationProperty={
'NotifyDelayAfter': 123
},
GlueVersion='string',
NumberOfWorkers=123,
WorkerType='Standard'|'G.1X'|'G.2X'|'G.025X',
CodeGenConfigurationNodes={
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
ExecutionClass='FLEX'|'STANDARD',
SourceControlDetails={
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
)
string
[REQUIRED]
The name you assign to this job definition. It must be unique in your account.
string
Description of the job being defined.
string
This field is reserved for future use.
string
[REQUIRED]
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
dict
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
MaxConcurrentRuns (integer) --
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
dict
[REQUIRED]
The JobCommand that runs this job.
Name (string) --
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
ScriptLocation (string) --
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
PythonVersion (string) --
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
dict
The default arguments for this job.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
(string) --
(string) --
dict
Non-overridable arguments for this job, specified as name-value pairs.
(string) --
(string) --
dict
The connections used for this job.
Connections (list) --
A list of connections used by the job.
(string) --
integer
The maximum number of times to retry this job if it fails.
integer
This parameter is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) to allocate to this Job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
integer
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
float
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
When you specify a Python shell job ( JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
When you specify an Apache Spark ETL job ( JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
string
The name of the SecurityConfiguration structure to be used with this job.
dict
The tags to use with this job. You may use tags to limit access to the job. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
(string) --
(string) --
dict
Specifies configuration properties of a job notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
string
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
integer
The number of workers of a defined workerType that are allocated when a job runs.
string
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
dict
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
(string) --
(dict) --
CodeGenConfigurationNode enumerates all valid Node types. One and only one of its member variables can be populated.
AthenaConnectorSource (dict) --
Specifies a connector to an Amazon Athena data source.
Name (string) -- [REQUIRED]
The name of the data source.
ConnectionName (string) -- [REQUIRED]
The name of the connection that is associated with the connector.
ConnectorName (string) -- [REQUIRED]
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
ConnectionTable (string) --
The name of the table in the data source.
SchemaName (string) -- [REQUIRED]
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
OutputSchemas (list) --
Specifies the data schema for the custom Athena source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
JDBCConnectorSource (dict) --
Specifies a connector to a JDBC data source.
Name (string) -- [REQUIRED]
The name of the data source.
ConnectionName (string) -- [REQUIRED]
The name of the connection that is associated with the connector.
ConnectorName (string) -- [REQUIRED]
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
FilterPredicate (string) --
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
PartitionColumn (string) --
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
LowerBound (integer) --
The minimum value of partitionColumn that is used to decide partition stride.
UpperBound (integer) --
The maximum value of partitionColumn that is used to decide partition stride.
NumPartitions (integer) --
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
JobBookmarkKeys (list) --
The name of the job bookmark keys on which to sort.
(string) --
JobBookmarkKeysSortOrder (string) --
Specifies an ascending or descending sort order.
DataTypeMapping (dict) --
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
(string) --
(string) --
ConnectionTable (string) --
The name of the table in the data source.
Query (string) --
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
OutputSchemas (list) --
Specifies the data schema for the custom JDBC source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorSource (dict) --
Specifies a connector to an Apache Spark data source.
Name (string) -- [REQUIRED]
The name of the data source.
ConnectionName (string) -- [REQUIRED]
The name of the connection that is associated with the connector.
ConnectorName (string) -- [REQUIRED]
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies data schema for the custom spark source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogSource (dict) --
Specifies a data store in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data store.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
RedshiftSource (dict) --
Specifies an Amazon Redshift data store.
Name (string) -- [REQUIRED]
The name of the Amazon Redshift data store.
Database (string) -- [REQUIRED]
The database to read from.
Table (string) -- [REQUIRED]
The database table to read from.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
S3CatalogSource (dict) --
Specifies an Amazon S3 data store in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data store.
Database (string) -- [REQUIRED]
The database to read from.
Table (string) -- [REQUIRED]
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
S3CsvSource (dict) --
Specifies a command-separated value (CSV) data store stored in Amazon S3.
Name (string) -- [REQUIRED]
The name of the data store.
Paths (list) -- [REQUIRED]
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
Separator (string) -- [REQUIRED]
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Escaper (string) --
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
QuoteChar (string) -- [REQUIRED]
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
WithHeader (boolean) --
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
WriteHeader (boolean) --
A Boolean value that specifies whether to write the header to output. The default value is True .
SkipFirst (boolean) --
A Boolean value that specifies whether to skip the first data line. The default value is False .
OptimizePerformance (boolean) --
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
OutputSchemas (list) --
Specifies the data schema for the S3 CSV source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3JsonSource (dict) --
Specifies a JSON data store stored in Amazon S3.
Name (string) -- [REQUIRED]
The name of the data store.
Paths (list) -- [REQUIRED]
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
JsonPath (string) --
A JsonPath string defining the JSON data.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
OutputSchemas (list) --
Specifies the data schema for the S3 JSON source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3ParquetSource (dict) --
Specifies an Apache Parquet data store stored in Amazon S3.
Name (string) -- [REQUIRED]
The name of the data store.
Paths (list) -- [REQUIRED]
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
OutputSchemas (list) --
Specifies the data schema for the S3 Parquet source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
RelationalCatalogSource (dict) --
Specifies a Relational database data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
DynamoDBCatalogSource (dict) --
Specifies a DynamoDB data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
JDBCConnectorTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) -- [REQUIRED]
The name of the connection that is associated with the connector.
ConnectionTable (string) -- [REQUIRED]
The name of the table in the data target.
ConnectorName (string) -- [REQUIRED]
The name of a connector that will be used.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the JDBC target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorTarget (dict) --
Specifies a target that uses an Apache Spark connector.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) -- [REQUIRED]
The name of a connection for an Apache Spark connector.
ConnectorName (string) -- [REQUIRED]
The name of an Apache Spark connector.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the custom spark target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogTarget (dict) --
Specifies a target that uses a Glue Data Catalog table.
Name (string) -- [REQUIRED]
The name of your data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
Table (string) -- [REQUIRED]
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
RedshiftTarget (dict) --
Specifies a target that uses Amazon Redshift.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
UpsertRedshiftOptions (dict) --
The set of options to configure an upsert operation when writing to a Redshift target.
TableLocation (string) --
The physical location of the Redshift table.
ConnectionName (string) --
The name of the connection to use to write to Redshift.
UpsertKeys (list) --
The keys used to determine whether to perform an update or insert.
(string) --
S3CatalogTarget (dict) --
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
Database (string) -- [REQUIRED]
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
S3GlueParquetTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) -- [REQUIRED]
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
S3DirectTarget (dict) --
Specifies a data target that writes to Amazon S3.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) -- [REQUIRED]
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Format (string) -- [REQUIRED]
Specifies the data output format for the target.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
ApplyMapping (dict) --
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Mapping (list) -- [REQUIRED]
Specifies the mapping of data property keys in the data source to data property keys in the data target.
(dict) --
Specifies the mapping of data property keys.
ToKey (string) --
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
FromPath (list) --
The table or column to be modified.
(string) --
FromType (string) --
The type of the data to be modified.
ToType (string) --
The data type that the data is to be modified to.
Dropped (boolean) --
If true, then the column is removed.
Children (list) --
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
SelectFields (dict) --
Specifies a transform that chooses the data property keys that you want to keep.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Paths (list) -- [REQUIRED]
A JSON path to a variable in the data structure.
(list) --
(string) --
DropFields (dict) --
Specifies a transform that chooses the data property keys that you want to drop.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Paths (list) -- [REQUIRED]
A JSON path to a variable in the data structure.
(list) --
(string) --
RenameField (dict) --
Specifies a transform that renames a single data property key.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
SourcePath (list) -- [REQUIRED]
A JSON path to a variable in the data structure for the source data.
(string) --
TargetPath (list) -- [REQUIRED]
A JSON path to a variable in the data structure for the target data.
(string) --
Spigot (dict) --
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Path (string) -- [REQUIRED]
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Topk (integer) --
Specifies a number of records to write starting from the beginning of the dataset.
Prob (float) --
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Join (dict) --
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
JoinType (string) -- [REQUIRED]
Specifies the type of join to be performed on the datasets.
Columns (list) -- [REQUIRED]
A list of the two columns to be joined.
(dict) --
Specifies a column to be joined.
From (string) -- [REQUIRED]
The column to be joined.
Keys (list) -- [REQUIRED]
The key of the column to be joined.
(list) --
(string) --
SplitFields (dict) --
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Paths (list) -- [REQUIRED]
A JSON path to a variable in the data structure.
(list) --
(string) --
SelectFromCollection (dict) --
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Index (integer) -- [REQUIRED]
The index for the DynamicFrame to be selected.
FillMissingValues (dict) --
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
ImputedPath (string) -- [REQUIRED]
A JSON path to a variable in the data structure for the dataset that is imputed.
FilledPath (string) --
A JSON path to a variable in the data structure for the dataset that is filled.
Filter (dict) --
Specifies a transform that splits a dataset into two, based on a filter condition.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
LogicalOperator (string) -- [REQUIRED]
The operator used to filter rows by comparing the key value to a specified value.
Filters (list) -- [REQUIRED]
Specifies a filter expression.
(dict) --
Specifies a filter expression.
Operation (string) -- [REQUIRED]
The type of operation to perform in the expression.
Negated (boolean) --
Whether the expression is to be negated.
Values (list) -- [REQUIRED]
A list of filter values.
(dict) --
Represents a single entry in the list of values for a FilterExpression .
Type (string) -- [REQUIRED]
The type of filter value.
Value (list) -- [REQUIRED]
The value to be associated.
(string) --
CustomCode (dict) --
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Code (string) -- [REQUIRED]
The custom code that is used to perform the data transformation.
ClassName (string) -- [REQUIRED]
The name defined for the custom code node class.
OutputSchemas (list) --
Specifies the data schema for the custom code transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkSQL (dict) --
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
(string) --
SqlQuery (string) -- [REQUIRED]
A SQL query that must use Spark SQL syntax and return a single data set.
SqlAliases (list) -- [REQUIRED]
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
(dict) --
Represents a single entry in the list of values for SqlAliases .
From (string) -- [REQUIRED]
A table, or a column in a table.
Alias (string) -- [REQUIRED]
A temporary name given to a table, or a column in a table.
OutputSchemas (list) --
Specifies the data schema for the SparkSQL transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
DirectKinesisSource (dict) --
Specifies a direct Amazon Kinesis data source.
Name (string) -- [REQUIRED]
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DirectKafkaSource (dict) --
Specifies an Apache Kafka data store.
Name (string) -- [REQUIRED]
The name of the data store.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKinesisSource (dict) --
Specifies a Kinesis data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
Database (string) -- [REQUIRED]
The name of the database to read from.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKafkaSource (dict) --
Specifies an Apache Kafka data store in the Data Catalog.
Name (string) -- [REQUIRED]
The name of the data store.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
Database (string) -- [REQUIRED]
The name of the database to read from.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DropNullFields (dict) --
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
NullCheckBoxList (dict) --
A structure that represents whether certain values are recognized as null values for removal.
IsEmpty (boolean) --
Specifies that an empty string is considered as a null value.
IsNullString (boolean) --
Specifies that a value spelling out the word 'null' is considered as a null value.
IsNegOne (boolean) --
Specifies that an integer value of -1 is considered as a null value.
NullTextList (list) --
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
(dict) --
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
Value (string) -- [REQUIRED]
The value of the null placeholder.
Datatype (dict) -- [REQUIRED]
The datatype of the value.
Id (string) -- [REQUIRED]
The datatype of the value.
Label (string) -- [REQUIRED]
A label assigned to the datatype.
Merge (dict) --
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Source (string) -- [REQUIRED]
The source DynamicFrame that will be merged with a staging DynamicFrame .
PrimaryKeys (list) -- [REQUIRED]
The list of primary key fields to match records from the source and staging dynamic frames.
(list) --
(string) --
Union (dict) --
Specifies a transform that combines the rows from two or more datasets into a single result.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The node ID inputs to the transform.
(string) --
UnionType (string) -- [REQUIRED]
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
PIIDetection (dict) --
Specifies a transform that identifies, removes or masks PII data.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The node ID inputs to the transform.
(string) --
PiiType (string) -- [REQUIRED]
Indicates the type of PIIDetection transform.
EntityTypesToDetect (list) -- [REQUIRED]
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
(string) --
OutputColumnName (string) --
Indicates the output column name that will contain any entity type detected in that row.
SampleFraction (float) --
Indicates the fraction of the data to sample when scanning for PII entities.
ThresholdFraction (float) --
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
MaskValue (string) --
Indicates the value that will replace the detected entity.
Aggregate (dict) --
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
Specifies the fields and rows to use as inputs for the aggregate transform.
(string) --
Groups (list) -- [REQUIRED]
Specifies the fields to group by.
(list) --
(string) --
Aggs (list) -- [REQUIRED]
Specifies the aggregate functions to be performed on specified fields.
(dict) --
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Column (list) -- [REQUIRED]
Specifies the column on the data set on which the aggregation function will be applied.
(string) --
AggFunc (string) -- [REQUIRED]
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
DropDuplicates (dict) --
Specifies a transform that removes rows of repeating data from a data set.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Columns (list) --
The name of the columns to be merged or removed if repeating.
(list) --
(string) --
GovernedCatalogTarget (dict) --
Specifies a data target that writes to a goverened catalog.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
Database (string) -- [REQUIRED]
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the governed catalog.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
GovernedCatalogSource (dict) --
Specifies a data source in a goverened Data Catalog.
Name (string) -- [REQUIRED]
The name of the data store.
Database (string) -- [REQUIRED]
The database to read from.
Table (string) -- [REQUIRED]
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
MicrosoftSQLServerCatalogSource (dict) --
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
MySQLCatalogSource (dict) --
Specifies a MySQL data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
OracleSQLCatalogSource (dict) --
Specifies an Oracle data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
PostgreSQLCatalogSource (dict) --
Specifies a PostgresSQL data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
MicrosoftSQLServerCatalogTarget (dict) --
Specifies a target that uses Microsoft SQL.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
MySQLCatalogTarget (dict) --
Specifies a target that uses MySQL.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
OracleSQLCatalogTarget (dict) --
Specifies a target that uses Oracle SQL.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
PostgreSQLCatalogTarget (dict) --
Specifies a target that uses Postgres SQL.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
DynamicTransform (dict) --
Specifies a custom visual transform created by a user.
Name (string) -- [REQUIRED]
Specifies the name of the dynamic transform.
TransformName (string) -- [REQUIRED]
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Inputs (list) -- [REQUIRED]
Specifies the inputs for the dynamic transform that are required.
(string) --
Parameters (list) --
Specifies the parameters of the dynamic transform.
(dict) --
Specifies the parameters in the config file of the dynamic transform.
Name (string) -- [REQUIRED]
Specifies the name of the parameter in the config file of the dynamic transform.
Type (string) -- [REQUIRED]
Specifies the parameter type in the config file of the dynamic transform.
ValidationRule (string) --
Specifies the validation rule in the config file of the dynamic transform.
ValidationMessage (string) --
Specifies the validation message in the config file of the dynamic transform.
Value (list) --
Specifies the value of the parameter in the config file of the dynamic transform.
(string) --
ListType (string) --
Specifies the list type of the parameter in the config file of the dynamic transform.
IsOptional (boolean) --
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
FunctionName (string) -- [REQUIRED]
Specifies the name of the function of the dynamic transform.
Path (string) -- [REQUIRED]
Specifies the path of the dynamic transform source and config files.
Version (string) --
This field is not used and will be deprecated in future release.
EvaluateDataQuality (dict) --
Specifies your data quality evaluation criteria.
Name (string) -- [REQUIRED]
The name of the data quality evaluation.
Inputs (list) -- [REQUIRED]
The inputs of your data quality evaluation.
(string) --
Ruleset (string) -- [REQUIRED]
The ruleset for your data quality evaluation.
Output (string) --
The output of your data quality evaluation.
PublishingOptions (dict) --
Options to configure how your results are published.
EvaluationContext (string) --
The context of the evaluation.
ResultsS3Prefix (string) --
The Amazon S3 prefix prepended to the results.
CloudWatchMetricsEnabled (boolean) --
Enable metrics for your data quality results.
ResultsPublishingEnabled (boolean) --
Enable publishing for your data quality results.
StopJobOnFailureOptions (dict) --
Options to configure how your job will stop if your data quality evaluation fails.
StopJobOnFailureTiming (string) --
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
string
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
dict
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
Provider (string) --
The provider for the remote repository.
Repository (string) --
The name of the remote repository that contains the job artifacts.
Owner (string) --
The owner of the remote repository that contains the job artifacts.
Branch (string) --
An optional branch in the remote repository.
Folder (string) --
An optional folder in the remote repository.
LastCommitId (string) --
The last commit ID for a commit in the remote repository.
AuthStrategy (string) --
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
AuthToken (string) --
The value of an authorization token.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
The unique name that was provided for this job definition.
{'InputRecordTables': {'AdditionalOptions': {'string': 'string'}}}
Creates an Glue machine learning transform. This operation creates the transform and all the necessary parameters to train it.
Call this operation as the first step in the process of using a machine learning transform (such as the FindMatches transform) for deduplicating data. You can provide an optional Description , in addition to the parameters that you want to use for your algorithm.
You must also specify certain parameters for the tasks that Glue runs on your behalf as part of learning from your data and creating a high-quality machine learning transform. These parameters include Role , and optionally, AllocatedCapacity , Timeout , and MaxRetries . For more information, see Jobs.
See also: AWS API Documentation
Request Syntax
client.create_ml_transform(
Name='string',
Description='string',
InputRecordTables=[
{
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
},
],
Parameters={
'TransformType': 'FIND_MATCHES',
'FindMatchesParameters': {
'PrimaryKeyColumnName': 'string',
'PrecisionRecallTradeoff': 123.0,
'AccuracyCostTradeoff': 123.0,
'EnforceProvidedLabels': True|False
}
},
Role='string',
GlueVersion='string',
MaxCapacity=123.0,
WorkerType='Standard'|'G.1X'|'G.2X'|'G.025X',
NumberOfWorkers=123,
Timeout=123,
MaxRetries=123,
Tags={
'string': 'string'
},
TransformEncryption={
'MlUserDataEncryption': {
'MlUserDataEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyId': 'string'
},
'TaskRunSecurityConfigurationName': 'string'
}
)
string
[REQUIRED]
The unique name that you give the transform when you create it.
string
A description of the machine learning transform that is being defined. The default is an empty string.
list
[REQUIRED]
A list of Glue table definitions used by the transform.
(dict) --
The database and table in the Glue Data Catalog that is used for input or output data.
DatabaseName (string) -- [REQUIRED]
A database name in the Glue Data Catalog.
TableName (string) -- [REQUIRED]
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
dict
[REQUIRED]
The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type.
TransformType (string) -- [REQUIRED]
The type of machine learning transform.
For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
FindMatchesParameters (dict) --
The parameters for the find matches algorithm.
PrimaryKeyColumnName (string) --
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
PrecisionRecallTradeoff (float) --
The value selected when tuning your transform for a balance between precision and recall. A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.
The precision metric indicates how often your model is correct when it predicts a match.
The recall metric indicates that for an actual match, how often your model predicts the match.
AccuracyCostTradeoff (float) --
The value that is selected when tuning your transform for a balance between accuracy and cost. A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate FindMatches transform, sometimes with unacceptable accuracy.
Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall.
Cost measures how many compute resources, and thus money, are consumed to run the transform.
EnforceProvidedLabels (boolean) --
The value to switch on or off to force the output to match the provided labels from users. If the value is True , the find matches transform forces the output to match the provided labels. The results override the normal conflation results. If the value is False , the find matches transform does not ensure all the labels provided are respected, and the results rely on the trained model.
Note that setting this value to true may increase the conflation execution time.
string
[REQUIRED]
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions. The required permissions include both Glue service role permissions to Glue resources, and Amazon S3 permissions required by the transform.
This role needs Glue service role permissions to allow access to resources in Glue. See Attach a Policy to IAM Users That Access Glue.
This role needs permission to your Amazon Simple Storage Service (Amazon S3) sources, targets, temporary directory, scripts, and any libraries used by the task run for this transform.
string
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
float
The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
MaxCapacity is a mutually exclusive option with NumberOfWorkers and WorkerType .
If either NumberOfWorkers or WorkerType is set, then MaxCapacity cannot be set.
If MaxCapacity is set then neither NumberOfWorkers or WorkerType can be set.
If WorkerType is set, then NumberOfWorkers is required (and vice versa).
MaxCapacity and NumberOfWorkers must both be at least 1.
When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
string
The type of predefined worker that is allocated when this task runs. Accepts a value of Standard, G.1X, or G.2X.
For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.
For the G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.
MaxCapacity is a mutually exclusive option with NumberOfWorkers and WorkerType .
If either NumberOfWorkers or WorkerType is set, then MaxCapacity cannot be set.
If MaxCapacity is set then neither NumberOfWorkers or WorkerType can be set.
If WorkerType is set, then NumberOfWorkers is required (and vice versa).
MaxCapacity and NumberOfWorkers must both be at least 1.
integer
The number of workers of a defined workerType that are allocated when this task runs.
If WorkerType is set, then NumberOfWorkers is required (and vice versa).
integer
The timeout of the task run for this transform in minutes. This is the maximum time that a task run for this transform can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
integer
The maximum number of times to retry a task for this transform after a task run fails.
dict
The tags to use with this machine learning transform. You may use tags to limit access to the machine learning transform. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
(string) --
(string) --
dict
The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
MlUserDataEncryption (dict) --
An MLUserDataEncryption object containing the encryption mode and customer-provided KMS key ID.
MlUserDataEncryptionMode (string) -- [REQUIRED]
The encryption mode applied to user data. Valid values are:
DISABLED: encryption is disabled
SSEKMS: use of server-side encryption with Key Management Service (SSE-KMS) for user data stored in Amazon S3.
KmsKeyId (string) --
The ID for the customer-provided KMS key.
TaskRunSecurityConfigurationName (string) --
The name of the security configuration.
dict
Response Syntax
{
'TransformId': 'string'
}
Response Structure
(dict) --
TransformId (string) --
A unique identifier that is generated for the transform.
{'Job': {'CodeGenConfigurationNodes': {'EvaluateDataQuality': {'Inputs': ['string'],
'Name': 'string',
'Output': 'PrimaryInput '
'| '
'EvaluationResults',
'PublishingOptions': {'CloudWatchMetricsEnabled': 'boolean',
'EvaluationContext': 'string',
'ResultsPublishingEnabled': 'boolean',
'ResultsS3Prefix': 'string'},
'Ruleset': 'string',
'StopJobOnFailureOptions': {'StopJobOnFailureTiming': 'Immediate '
'| '
'AfterDataLoad'}}}}}
Retrieves an existing job definition.
See also: AWS API Documentation
Request Syntax
client.get_job(
JobName='string'
)
string
[REQUIRED]
The name of the job definition to retrieve.
dict
Response Syntax
{
'Job': {
'Name': 'string',
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
}
}
Response Structure
(dict) --
Job (dict) --
The requested job definition.
Name (string) --
The name you assign to this job definition.
Description (string) --
A description of the job.
LogUri (string) --
This field is reserved for future use.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
CreatedOn (datetime) --
The time and date that this job definition was created.
LastModifiedOn (datetime) --
The last point in time when this job definition was modified.
ExecutionProperty (dict) --
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
MaxConcurrentRuns (integer) --
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
Command (dict) --
The JobCommand that runs this job.
Name (string) --
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
ScriptLocation (string) --
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
PythonVersion (string) --
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
DefaultArguments (dict) --
The default arguments for this job, specified as name-value pairs.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
(string) --
(string) --
NonOverridableArguments (dict) --
Non-overridable arguments for this job, specified as name-value pairs.
(string) --
(string) --
Connections (dict) --
The connections used for this job.
Connections (list) --
A list of connections used by the job.
(string) --
MaxRetries (integer) --
The maximum number of times to retry this job after a JobRun fails.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to runs of this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Timeout (integer) --
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
MaxCapacity (float) --
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
When you specify a Python shell job ( JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
When you specify an Apache Spark ETL job ( JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job.
NotificationProperty (dict) --
Specifies configuration properties of a job notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
CodeGenConfigurationNodes (dict) --
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
(string) --
(dict) --
CodeGenConfigurationNode enumerates all valid Node types. One and only one of its member variables can be populated.
AthenaConnectorSource (dict) --
Specifies a connector to an Amazon Athena data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
ConnectionTable (string) --
The name of the table in the data source.
SchemaName (string) --
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
OutputSchemas (list) --
Specifies the data schema for the custom Athena source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
JDBCConnectorSource (dict) --
Specifies a connector to a JDBC data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
FilterPredicate (string) --
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
PartitionColumn (string) --
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
LowerBound (integer) --
The minimum value of partitionColumn that is used to decide partition stride.
UpperBound (integer) --
The maximum value of partitionColumn that is used to decide partition stride.
NumPartitions (integer) --
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
JobBookmarkKeys (list) --
The name of the job bookmark keys on which to sort.
(string) --
JobBookmarkKeysSortOrder (string) --
Specifies an ascending or descending sort order.
DataTypeMapping (dict) --
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
(string) --
(string) --
ConnectionTable (string) --
The name of the table in the data source.
Query (string) --
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
OutputSchemas (list) --
Specifies the data schema for the custom JDBC source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorSource (dict) --
Specifies a connector to an Apache Spark data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies data schema for the custom spark source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogSource (dict) --
Specifies a data store in the Glue Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
RedshiftSource (dict) --
Specifies an Amazon Redshift data store.
Name (string) --
The name of the Amazon Redshift data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
S3CatalogSource (dict) --
Specifies an Amazon S3 data store in the Glue Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
S3CsvSource (dict) --
Specifies a command-separated value (CSV) data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
Separator (string) --
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Escaper (string) --
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
QuoteChar (string) --
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
WithHeader (boolean) --
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
WriteHeader (boolean) --
A Boolean value that specifies whether to write the header to output. The default value is True .
SkipFirst (boolean) --
A Boolean value that specifies whether to skip the first data line. The default value is False .
OptimizePerformance (boolean) --
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
OutputSchemas (list) --
Specifies the data schema for the S3 CSV source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3JsonSource (dict) --
Specifies a JSON data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
JsonPath (string) --
A JsonPath string defining the JSON data.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
OutputSchemas (list) --
Specifies the data schema for the S3 JSON source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3ParquetSource (dict) --
Specifies an Apache Parquet data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
OutputSchemas (list) --
Specifies the data schema for the S3 Parquet source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
RelationalCatalogSource (dict) --
Specifies a Relational database data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
DynamoDBCatalogSource (dict) --
Specifies a DynamoDB data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
JDBCConnectorTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectionTable (string) --
The name of the table in the data target.
ConnectorName (string) --
The name of a connector that will be used.
ConnectionType (string) --
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the JDBC target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorTarget (dict) --
Specifies a target that uses an Apache Spark connector.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) --
The name of a connection for an Apache Spark connector.
ConnectorName (string) --
The name of an Apache Spark connector.
ConnectionType (string) --
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the custom spark target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogTarget (dict) --
Specifies a target that uses a Glue Data Catalog table.
Name (string) --
The name of your data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
Table (string) --
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
RedshiftTarget (dict) --
Specifies a target that uses Amazon Redshift.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
UpsertRedshiftOptions (dict) --
The set of options to configure an upsert operation when writing to a Redshift target.
TableLocation (string) --
The physical location of the Redshift table.
ConnectionName (string) --
The name of the connection to use to write to Redshift.
UpsertKeys (list) --
The keys used to determine whether to perform an update or insert.
(string) --
S3CatalogTarget (dict) --
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) --
The name of the table in the database to write to.
Database (string) --
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
S3GlueParquetTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) --
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
S3DirectTarget (dict) --
Specifies a data target that writes to Amazon S3.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) --
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Format (string) --
Specifies the data output format for the target.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
ApplyMapping (dict) --
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Mapping (list) --
Specifies the mapping of data property keys in the data source to data property keys in the data target.
(dict) --
Specifies the mapping of data property keys.
ToKey (string) --
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
FromPath (list) --
The table or column to be modified.
(string) --
FromType (string) --
The type of the data to be modified.
ToType (string) --
The data type that the data is to be modified to.
Dropped (boolean) --
If true, then the column is removed.
Children (list) --
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
SelectFields (dict) --
Specifies a transform that chooses the data property keys that you want to keep.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
DropFields (dict) --
Specifies a transform that chooses the data property keys that you want to drop.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
RenameField (dict) --
Specifies a transform that renames a single data property key.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
SourcePath (list) --
A JSON path to a variable in the data structure for the source data.
(string) --
TargetPath (list) --
A JSON path to a variable in the data structure for the target data.
(string) --
Spigot (dict) --
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Path (string) --
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Topk (integer) --
Specifies a number of records to write starting from the beginning of the dataset.
Prob (float) --
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Join (dict) --
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
JoinType (string) --
Specifies the type of join to be performed on the datasets.
Columns (list) --
A list of the two columns to be joined.
(dict) --
Specifies a column to be joined.
From (string) --
The column to be joined.
Keys (list) --
The key of the column to be joined.
(list) --
(string) --
SplitFields (dict) --
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
SelectFromCollection (dict) --
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Index (integer) --
The index for the DynamicFrame to be selected.
FillMissingValues (dict) --
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
ImputedPath (string) --
A JSON path to a variable in the data structure for the dataset that is imputed.
FilledPath (string) --
A JSON path to a variable in the data structure for the dataset that is filled.
Filter (dict) --
Specifies a transform that splits a dataset into two, based on a filter condition.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
LogicalOperator (string) --
The operator used to filter rows by comparing the key value to a specified value.
Filters (list) --
Specifies a filter expression.
(dict) --
Specifies a filter expression.
Operation (string) --
The type of operation to perform in the expression.
Negated (boolean) --
Whether the expression is to be negated.
Values (list) --
A list of filter values.
(dict) --
Represents a single entry in the list of values for a FilterExpression .
Type (string) --
The type of filter value.
Value (list) --
The value to be associated.
(string) --
CustomCode (dict) --
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Code (string) --
The custom code that is used to perform the data transformation.
ClassName (string) --
The name defined for the custom code node class.
OutputSchemas (list) --
Specifies the data schema for the custom code transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkSQL (dict) --
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
(string) --
SqlQuery (string) --
A SQL query that must use Spark SQL syntax and return a single data set.
SqlAliases (list) --
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
(dict) --
Represents a single entry in the list of values for SqlAliases .
From (string) --
A table, or a column in a table.
Alias (string) --
A temporary name given to a table, or a column in a table.
OutputSchemas (list) --
Specifies the data schema for the SparkSQL transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
DirectKinesisSource (dict) --
Specifies a direct Amazon Kinesis data source.
Name (string) --
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DirectKafkaSource (dict) --
Specifies an Apache Kafka data store.
Name (string) --
The name of the data store.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKinesisSource (dict) --
Specifies a Kinesis data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) --
The name of the table in the database to read from.
Database (string) --
The name of the database to read from.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKafkaSource (dict) --
Specifies an Apache Kafka data store in the Data Catalog.
Name (string) --
The name of the data store.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) --
The name of the table in the database to read from.
Database (string) --
The name of the database to read from.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DropNullFields (dict) --
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
NullCheckBoxList (dict) --
A structure that represents whether certain values are recognized as null values for removal.
IsEmpty (boolean) --
Specifies that an empty string is considered as a null value.
IsNullString (boolean) --
Specifies that a value spelling out the word 'null' is considered as a null value.
IsNegOne (boolean) --
Specifies that an integer value of -1 is considered as a null value.
NullTextList (list) --
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
(dict) --
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
Value (string) --
The value of the null placeholder.
Datatype (dict) --
The datatype of the value.
Id (string) --
The datatype of the value.
Label (string) --
A label assigned to the datatype.
Merge (dict) --
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Source (string) --
The source DynamicFrame that will be merged with a staging DynamicFrame .
PrimaryKeys (list) --
The list of primary key fields to match records from the source and staging dynamic frames.
(list) --
(string) --
Union (dict) --
Specifies a transform that combines the rows from two or more datasets into a single result.
Name (string) --
The name of the transform node.
Inputs (list) --
The node ID inputs to the transform.
(string) --
UnionType (string) --
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
PIIDetection (dict) --
Specifies a transform that identifies, removes or masks PII data.
Name (string) --
The name of the transform node.
Inputs (list) --
The node ID inputs to the transform.
(string) --
PiiType (string) --
Indicates the type of PIIDetection transform.
EntityTypesToDetect (list) --
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
(string) --
OutputColumnName (string) --
Indicates the output column name that will contain any entity type detected in that row.
SampleFraction (float) --
Indicates the fraction of the data to sample when scanning for PII entities.
ThresholdFraction (float) --
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
MaskValue (string) --
Indicates the value that will replace the detected entity.
Aggregate (dict) --
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
Name (string) --
The name of the transform node.
Inputs (list) --
Specifies the fields and rows to use as inputs for the aggregate transform.
(string) --
Groups (list) --
Specifies the fields to group by.
(list) --
(string) --
Aggs (list) --
Specifies the aggregate functions to be performed on specified fields.
(dict) --
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Column (list) --
Specifies the column on the data set on which the aggregation function will be applied.
(string) --
AggFunc (string) --
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
DropDuplicates (dict) --
Specifies a transform that removes rows of repeating data from a data set.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Columns (list) --
The name of the columns to be merged or removed if repeating.
(list) --
(string) --
GovernedCatalogTarget (dict) --
Specifies a data target that writes to a goverened catalog.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) --
The name of the table in the database to write to.
Database (string) --
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the governed catalog.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
GovernedCatalogSource (dict) --
Specifies a data source in a goverened Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
MicrosoftSQLServerCatalogSource (dict) --
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
MySQLCatalogSource (dict) --
Specifies a MySQL data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
OracleSQLCatalogSource (dict) --
Specifies an Oracle data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
PostgreSQLCatalogSource (dict) --
Specifies a PostgresSQL data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
MicrosoftSQLServerCatalogTarget (dict) --
Specifies a target that uses Microsoft SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
MySQLCatalogTarget (dict) --
Specifies a target that uses MySQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
OracleSQLCatalogTarget (dict) --
Specifies a target that uses Oracle SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
PostgreSQLCatalogTarget (dict) --
Specifies a target that uses Postgres SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
DynamicTransform (dict) --
Specifies a custom visual transform created by a user.
Name (string) --
Specifies the name of the dynamic transform.
TransformName (string) --
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Inputs (list) --
Specifies the inputs for the dynamic transform that are required.
(string) --
Parameters (list) --
Specifies the parameters of the dynamic transform.
(dict) --
Specifies the parameters in the config file of the dynamic transform.
Name (string) --
Specifies the name of the parameter in the config file of the dynamic transform.
Type (string) --
Specifies the parameter type in the config file of the dynamic transform.
ValidationRule (string) --
Specifies the validation rule in the config file of the dynamic transform.
ValidationMessage (string) --
Specifies the validation message in the config file of the dynamic transform.
Value (list) --
Specifies the value of the parameter in the config file of the dynamic transform.
(string) --
ListType (string) --
Specifies the list type of the parameter in the config file of the dynamic transform.
IsOptional (boolean) --
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
FunctionName (string) --
Specifies the name of the function of the dynamic transform.
Path (string) --
Specifies the path of the dynamic transform source and config files.
Version (string) --
This field is not used and will be deprecated in future release.
EvaluateDataQuality (dict) --
Specifies your data quality evaluation criteria.
Name (string) --
The name of the data quality evaluation.
Inputs (list) --
The inputs of your data quality evaluation.
(string) --
Ruleset (string) --
The ruleset for your data quality evaluation.
Output (string) --
The output of your data quality evaluation.
PublishingOptions (dict) --
Options to configure how your results are published.
EvaluationContext (string) --
The context of the evaluation.
ResultsS3Prefix (string) --
The Amazon S3 prefix prepended to the results.
CloudWatchMetricsEnabled (boolean) --
Enable metrics for your data quality results.
ResultsPublishingEnabled (boolean) --
Enable publishing for your data quality results.
StopJobOnFailureOptions (dict) --
Options to configure how your job will stop if your data quality evaluation fails.
StopJobOnFailureTiming (string) --
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
SourceControlDetails (dict) --
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
Provider (string) --
The provider for the remote repository.
Repository (string) --
The name of the remote repository that contains the job artifacts.
Owner (string) --
The owner of the remote repository that contains the job artifacts.
Branch (string) --
An optional branch in the remote repository.
Folder (string) --
An optional folder in the remote repository.
LastCommitId (string) --
The last commit ID for a commit in the remote repository.
AuthStrategy (string) --
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
AuthToken (string) --
The value of an authorization token.
{'Jobs': {'CodeGenConfigurationNodes': {'EvaluateDataQuality': {'Inputs': ['string'],
'Name': 'string',
'Output': 'PrimaryInput '
'| '
'EvaluationResults',
'PublishingOptions': {'CloudWatchMetricsEnabled': 'boolean',
'EvaluationContext': 'string',
'ResultsPublishingEnabled': 'boolean',
'ResultsS3Prefix': 'string'},
'Ruleset': 'string',
'StopJobOnFailureOptions': {'StopJobOnFailureTiming': 'Immediate '
'| '
'AfterDataLoad'}}}}}
Retrieves all current job definitions.
See also: AWS API Documentation
Request Syntax
client.get_jobs(
NextToken='string',
MaxResults=123
)
string
A continuation token, if this is a continuation call.
integer
The maximum size of the response.
dict
Response Syntax
{
'Jobs': [
{
'Name': 'string',
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Jobs (list) --
A list of job definitions.
(dict) --
Specifies a job definition.
Name (string) --
The name you assign to this job definition.
Description (string) --
A description of the job.
LogUri (string) --
This field is reserved for future use.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
CreatedOn (datetime) --
The time and date that this job definition was created.
LastModifiedOn (datetime) --
The last point in time when this job definition was modified.
ExecutionProperty (dict) --
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
MaxConcurrentRuns (integer) --
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
Command (dict) --
The JobCommand that runs this job.
Name (string) --
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
ScriptLocation (string) --
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
PythonVersion (string) --
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
DefaultArguments (dict) --
The default arguments for this job, specified as name-value pairs.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
(string) --
(string) --
NonOverridableArguments (dict) --
Non-overridable arguments for this job, specified as name-value pairs.
(string) --
(string) --
Connections (dict) --
The connections used for this job.
Connections (list) --
A list of connections used by the job.
(string) --
MaxRetries (integer) --
The maximum number of times to retry this job after a JobRun fails.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to runs of this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Timeout (integer) --
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
MaxCapacity (float) --
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
When you specify a Python shell job ( JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
When you specify an Apache Spark ETL job ( JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job.
NotificationProperty (dict) --
Specifies configuration properties of a job notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
CodeGenConfigurationNodes (dict) --
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
(string) --
(dict) --
CodeGenConfigurationNode enumerates all valid Node types. One and only one of its member variables can be populated.
AthenaConnectorSource (dict) --
Specifies a connector to an Amazon Athena data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
ConnectionTable (string) --
The name of the table in the data source.
SchemaName (string) --
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
OutputSchemas (list) --
Specifies the data schema for the custom Athena source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
JDBCConnectorSource (dict) --
Specifies a connector to a JDBC data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
FilterPredicate (string) --
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
PartitionColumn (string) --
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
LowerBound (integer) --
The minimum value of partitionColumn that is used to decide partition stride.
UpperBound (integer) --
The maximum value of partitionColumn that is used to decide partition stride.
NumPartitions (integer) --
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
JobBookmarkKeys (list) --
The name of the job bookmark keys on which to sort.
(string) --
JobBookmarkKeysSortOrder (string) --
Specifies an ascending or descending sort order.
DataTypeMapping (dict) --
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
(string) --
(string) --
ConnectionTable (string) --
The name of the table in the data source.
Query (string) --
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
OutputSchemas (list) --
Specifies the data schema for the custom JDBC source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorSource (dict) --
Specifies a connector to an Apache Spark data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies data schema for the custom spark source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogSource (dict) --
Specifies a data store in the Glue Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
RedshiftSource (dict) --
Specifies an Amazon Redshift data store.
Name (string) --
The name of the Amazon Redshift data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
S3CatalogSource (dict) --
Specifies an Amazon S3 data store in the Glue Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
S3CsvSource (dict) --
Specifies a command-separated value (CSV) data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
Separator (string) --
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Escaper (string) --
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
QuoteChar (string) --
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
WithHeader (boolean) --
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
WriteHeader (boolean) --
A Boolean value that specifies whether to write the header to output. The default value is True .
SkipFirst (boolean) --
A Boolean value that specifies whether to skip the first data line. The default value is False .
OptimizePerformance (boolean) --
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
OutputSchemas (list) --
Specifies the data schema for the S3 CSV source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3JsonSource (dict) --
Specifies a JSON data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
JsonPath (string) --
A JsonPath string defining the JSON data.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
OutputSchemas (list) --
Specifies the data schema for the S3 JSON source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3ParquetSource (dict) --
Specifies an Apache Parquet data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
OutputSchemas (list) --
Specifies the data schema for the S3 Parquet source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
RelationalCatalogSource (dict) --
Specifies a Relational database data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
DynamoDBCatalogSource (dict) --
Specifies a DynamoDB data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
JDBCConnectorTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectionTable (string) --
The name of the table in the data target.
ConnectorName (string) --
The name of a connector that will be used.
ConnectionType (string) --
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the JDBC target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorTarget (dict) --
Specifies a target that uses an Apache Spark connector.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) --
The name of a connection for an Apache Spark connector.
ConnectorName (string) --
The name of an Apache Spark connector.
ConnectionType (string) --
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the custom spark target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogTarget (dict) --
Specifies a target that uses a Glue Data Catalog table.
Name (string) --
The name of your data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
Table (string) --
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
RedshiftTarget (dict) --
Specifies a target that uses Amazon Redshift.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
UpsertRedshiftOptions (dict) --
The set of options to configure an upsert operation when writing to a Redshift target.
TableLocation (string) --
The physical location of the Redshift table.
ConnectionName (string) --
The name of the connection to use to write to Redshift.
UpsertKeys (list) --
The keys used to determine whether to perform an update or insert.
(string) --
S3CatalogTarget (dict) --
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) --
The name of the table in the database to write to.
Database (string) --
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
S3GlueParquetTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) --
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
S3DirectTarget (dict) --
Specifies a data target that writes to Amazon S3.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) --
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Format (string) --
Specifies the data output format for the target.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
ApplyMapping (dict) --
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Mapping (list) --
Specifies the mapping of data property keys in the data source to data property keys in the data target.
(dict) --
Specifies the mapping of data property keys.
ToKey (string) --
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
FromPath (list) --
The table or column to be modified.
(string) --
FromType (string) --
The type of the data to be modified.
ToType (string) --
The data type that the data is to be modified to.
Dropped (boolean) --
If true, then the column is removed.
Children (list) --
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
SelectFields (dict) --
Specifies a transform that chooses the data property keys that you want to keep.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
DropFields (dict) --
Specifies a transform that chooses the data property keys that you want to drop.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
RenameField (dict) --
Specifies a transform that renames a single data property key.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
SourcePath (list) --
A JSON path to a variable in the data structure for the source data.
(string) --
TargetPath (list) --
A JSON path to a variable in the data structure for the target data.
(string) --
Spigot (dict) --
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Path (string) --
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Topk (integer) --
Specifies a number of records to write starting from the beginning of the dataset.
Prob (float) --
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Join (dict) --
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
JoinType (string) --
Specifies the type of join to be performed on the datasets.
Columns (list) --
A list of the two columns to be joined.
(dict) --
Specifies a column to be joined.
From (string) --
The column to be joined.
Keys (list) --
The key of the column to be joined.
(list) --
(string) --
SplitFields (dict) --
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Paths (list) --
A JSON path to a variable in the data structure.
(list) --
(string) --
SelectFromCollection (dict) --
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Index (integer) --
The index for the DynamicFrame to be selected.
FillMissingValues (dict) --
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
ImputedPath (string) --
A JSON path to a variable in the data structure for the dataset that is imputed.
FilledPath (string) --
A JSON path to a variable in the data structure for the dataset that is filled.
Filter (dict) --
Specifies a transform that splits a dataset into two, based on a filter condition.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
LogicalOperator (string) --
The operator used to filter rows by comparing the key value to a specified value.
Filters (list) --
Specifies a filter expression.
(dict) --
Specifies a filter expression.
Operation (string) --
The type of operation to perform in the expression.
Negated (boolean) --
Whether the expression is to be negated.
Values (list) --
A list of filter values.
(dict) --
Represents a single entry in the list of values for a FilterExpression .
Type (string) --
The type of filter value.
Value (list) --
The value to be associated.
(string) --
CustomCode (dict) --
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Code (string) --
The custom code that is used to perform the data transformation.
ClassName (string) --
The name defined for the custom code node class.
OutputSchemas (list) --
Specifies the data schema for the custom code transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkSQL (dict) --
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
(string) --
SqlQuery (string) --
A SQL query that must use Spark SQL syntax and return a single data set.
SqlAliases (list) --
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
(dict) --
Represents a single entry in the list of values for SqlAliases .
From (string) --
A table, or a column in a table.
Alias (string) --
A temporary name given to a table, or a column in a table.
OutputSchemas (list) --
Specifies the data schema for the SparkSQL transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
DirectKinesisSource (dict) --
Specifies a direct Amazon Kinesis data source.
Name (string) --
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DirectKafkaSource (dict) --
Specifies an Apache Kafka data store.
Name (string) --
The name of the data store.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKinesisSource (dict) --
Specifies a Kinesis data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) --
The name of the table in the database to read from.
Database (string) --
The name of the database to read from.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKafkaSource (dict) --
Specifies an Apache Kafka data store in the Data Catalog.
Name (string) --
The name of the data store.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) --
The name of the table in the database to read from.
Database (string) --
The name of the database to read from.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DropNullFields (dict) --
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
NullCheckBoxList (dict) --
A structure that represents whether certain values are recognized as null values for removal.
IsEmpty (boolean) --
Specifies that an empty string is considered as a null value.
IsNullString (boolean) --
Specifies that a value spelling out the word 'null' is considered as a null value.
IsNegOne (boolean) --
Specifies that an integer value of -1 is considered as a null value.
NullTextList (list) --
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
(dict) --
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
Value (string) --
The value of the null placeholder.
Datatype (dict) --
The datatype of the value.
Id (string) --
The datatype of the value.
Label (string) --
A label assigned to the datatype.
Merge (dict) --
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Source (string) --
The source DynamicFrame that will be merged with a staging DynamicFrame .
PrimaryKeys (list) --
The list of primary key fields to match records from the source and staging dynamic frames.
(list) --
(string) --
Union (dict) --
Specifies a transform that combines the rows from two or more datasets into a single result.
Name (string) --
The name of the transform node.
Inputs (list) --
The node ID inputs to the transform.
(string) --
UnionType (string) --
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
PIIDetection (dict) --
Specifies a transform that identifies, removes or masks PII data.
Name (string) --
The name of the transform node.
Inputs (list) --
The node ID inputs to the transform.
(string) --
PiiType (string) --
Indicates the type of PIIDetection transform.
EntityTypesToDetect (list) --
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
(string) --
OutputColumnName (string) --
Indicates the output column name that will contain any entity type detected in that row.
SampleFraction (float) --
Indicates the fraction of the data to sample when scanning for PII entities.
ThresholdFraction (float) --
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
MaskValue (string) --
Indicates the value that will replace the detected entity.
Aggregate (dict) --
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
Name (string) --
The name of the transform node.
Inputs (list) --
Specifies the fields and rows to use as inputs for the aggregate transform.
(string) --
Groups (list) --
Specifies the fields to group by.
(list) --
(string) --
Aggs (list) --
Specifies the aggregate functions to be performed on specified fields.
(dict) --
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Column (list) --
Specifies the column on the data set on which the aggregation function will be applied.
(string) --
AggFunc (string) --
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
DropDuplicates (dict) --
Specifies a transform that removes rows of repeating data from a data set.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
(string) --
Columns (list) --
The name of the columns to be merged or removed if repeating.
(list) --
(string) --
GovernedCatalogTarget (dict) --
Specifies a data target that writes to a goverened catalog.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) --
The name of the table in the database to write to.
Database (string) --
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the governed catalog.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
GovernedCatalogSource (dict) --
Specifies a data source in a goverened Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
MicrosoftSQLServerCatalogSource (dict) --
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
MySQLCatalogSource (dict) --
Specifies a MySQL data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
OracleSQLCatalogSource (dict) --
Specifies an Oracle data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
PostgreSQLCatalogSource (dict) --
Specifies a PostgresSQL data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
MicrosoftSQLServerCatalogTarget (dict) --
Specifies a target that uses Microsoft SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
MySQLCatalogTarget (dict) --
Specifies a target that uses MySQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
OracleSQLCatalogTarget (dict) --
Specifies a target that uses Oracle SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
PostgreSQLCatalogTarget (dict) --
Specifies a target that uses Postgres SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
(string) --
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
DynamicTransform (dict) --
Specifies a custom visual transform created by a user.
Name (string) --
Specifies the name of the dynamic transform.
TransformName (string) --
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Inputs (list) --
Specifies the inputs for the dynamic transform that are required.
(string) --
Parameters (list) --
Specifies the parameters of the dynamic transform.
(dict) --
Specifies the parameters in the config file of the dynamic transform.
Name (string) --
Specifies the name of the parameter in the config file of the dynamic transform.
Type (string) --
Specifies the parameter type in the config file of the dynamic transform.
ValidationRule (string) --
Specifies the validation rule in the config file of the dynamic transform.
ValidationMessage (string) --
Specifies the validation message in the config file of the dynamic transform.
Value (list) --
Specifies the value of the parameter in the config file of the dynamic transform.
(string) --
ListType (string) --
Specifies the list type of the parameter in the config file of the dynamic transform.
IsOptional (boolean) --
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
FunctionName (string) --
Specifies the name of the function of the dynamic transform.
Path (string) --
Specifies the path of the dynamic transform source and config files.
Version (string) --
This field is not used and will be deprecated in future release.
EvaluateDataQuality (dict) --
Specifies your data quality evaluation criteria.
Name (string) --
The name of the data quality evaluation.
Inputs (list) --
The inputs of your data quality evaluation.
(string) --
Ruleset (string) --
The ruleset for your data quality evaluation.
Output (string) --
The output of your data quality evaluation.
PublishingOptions (dict) --
Options to configure how your results are published.
EvaluationContext (string) --
The context of the evaluation.
ResultsS3Prefix (string) --
The Amazon S3 prefix prepended to the results.
CloudWatchMetricsEnabled (boolean) --
Enable metrics for your data quality results.
ResultsPublishingEnabled (boolean) --
Enable publishing for your data quality results.
StopJobOnFailureOptions (dict) --
Options to configure how your job will stop if your data quality evaluation fails.
StopJobOnFailureTiming (string) --
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
SourceControlDetails (dict) --
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
Provider (string) --
The provider for the remote repository.
Repository (string) --
The name of the remote repository that contains the job artifacts.
Owner (string) --
The owner of the remote repository that contains the job artifacts.
Branch (string) --
An optional branch in the remote repository.
Folder (string) --
An optional folder in the remote repository.
LastCommitId (string) --
The last commit ID for a commit in the remote repository.
AuthStrategy (string) --
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
AuthToken (string) --
The value of an authorization token.
NextToken (string) --
A continuation token, if not all job definitions have yet been returned.
{'InputRecordTables': {'AdditionalOptions': {'string': 'string'}}}
Gets an Glue machine learning transform artifact and all its corresponding metadata. Machine learning transforms are a special type of transform that use machine learning to learn the details of the transformation to be performed by learning from examples provided by humans. These transformations are then saved by Glue. You can retrieve their metadata by calling GetMLTransform .
See also: AWS API Documentation
Request Syntax
client.get_ml_transform(
TransformId='string'
)
string
[REQUIRED]
The unique identifier of the transform, generated at the time that the transform was created.
dict
Response Syntax
{
'TransformId': 'string',
'Name': 'string',
'Description': 'string',
'Status': 'NOT_READY'|'READY'|'DELETING',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'InputRecordTables': [
{
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
},
],
'Parameters': {
'TransformType': 'FIND_MATCHES',
'FindMatchesParameters': {
'PrimaryKeyColumnName': 'string',
'PrecisionRecallTradeoff': 123.0,
'AccuracyCostTradeoff': 123.0,
'EnforceProvidedLabels': True|False
}
},
'EvaluationMetrics': {
'TransformType': 'FIND_MATCHES',
'FindMatchesMetrics': {
'AreaUnderPRCurve': 123.0,
'Precision': 123.0,
'Recall': 123.0,
'F1': 123.0,
'ConfusionMatrix': {
'NumTruePositives': 123,
'NumFalsePositives': 123,
'NumTrueNegatives': 123,
'NumFalseNegatives': 123
},
'ColumnImportances': [
{
'ColumnName': 'string',
'Importance': 123.0
},
]
}
},
'LabelCount': 123,
'Schema': [
{
'Name': 'string',
'DataType': 'string'
},
],
'Role': 'string',
'GlueVersion': 'string',
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'Timeout': 123,
'MaxRetries': 123,
'TransformEncryption': {
'MlUserDataEncryption': {
'MlUserDataEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyId': 'string'
},
'TaskRunSecurityConfigurationName': 'string'
}
}
Response Structure
(dict) --
TransformId (string) --
The unique identifier of the transform, generated at the time that the transform was created.
Name (string) --
The unique name given to the transform when it was created.
Description (string) --
A description of the transform.
Status (string) --
The last known status of the transform (to indicate whether it can be used or not). One of "NOT_READY", "READY", or "DELETING".
CreatedOn (datetime) --
The date and time when the transform was created.
LastModifiedOn (datetime) --
The date and time when the transform was last modified.
InputRecordTables (list) --
A list of Glue table definitions used by the transform.
(dict) --
The database and table in the Glue Data Catalog that is used for input or output data.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
Parameters (dict) --
The configuration parameters that are specific to the algorithm used.
TransformType (string) --
The type of machine learning transform.
For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
FindMatchesParameters (dict) --
The parameters for the find matches algorithm.
PrimaryKeyColumnName (string) --
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
PrecisionRecallTradeoff (float) --
The value selected when tuning your transform for a balance between precision and recall. A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.
The precision metric indicates how often your model is correct when it predicts a match.
The recall metric indicates that for an actual match, how often your model predicts the match.
AccuracyCostTradeoff (float) --
The value that is selected when tuning your transform for a balance between accuracy and cost. A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate FindMatches transform, sometimes with unacceptable accuracy.
Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall.
Cost measures how many compute resources, and thus money, are consumed to run the transform.
EnforceProvidedLabels (boolean) --
The value to switch on or off to force the output to match the provided labels from users. If the value is True , the find matches transform forces the output to match the provided labels. The results override the normal conflation results. If the value is False , the find matches transform does not ensure all the labels provided are respected, and the results rely on the trained model.
Note that setting this value to true may increase the conflation execution time.
EvaluationMetrics (dict) --
The latest evaluation metrics.
TransformType (string) --
The type of machine learning transform.
FindMatchesMetrics (dict) --
The evaluation metrics for the find matches algorithm.
AreaUnderPRCurve (float) --
The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs. recall. Higher values indicate that you have a more attractive precision vs. recall tradeoff.
For more information, see Precision and recall in Wikipedia.
Precision (float) --
The precision metric indicates when often your transform is correct when it predicts a match. Specifically, it measures how well the transform finds true positives from the total true positives possible.
For more information, see Precision and recall in Wikipedia.
Recall (float) --
The recall metric indicates that for an actual match, how often your transform predicts the match. Specifically, it measures how well the transform finds true positives from the total records in the source data.
For more information, see Precision and recall in Wikipedia.
F1 (float) --
The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.
For more information, see F1 score in Wikipedia.
ConfusionMatrix (dict) --
The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.
For more information, see Confusion matrix in Wikipedia.
NumTruePositives (integer) --
The number of matches in the data that the transform correctly found, in the confusion matrix for your transform.
NumFalsePositives (integer) --
The number of nonmatches in the data that the transform incorrectly classified as a match, in the confusion matrix for your transform.
NumTrueNegatives (integer) --
The number of nonmatches in the data that the transform correctly rejected, in the confusion matrix for your transform.
NumFalseNegatives (integer) --
The number of matches in the data that the transform didn't find, in the confusion matrix for your transform.
ColumnImportances (list) --
A list of ColumnImportance structures containing column importance metrics, sorted in order of descending importance.
(dict) --
A structure containing the column name and column importance score for a column.
Column importance helps you understand how columns contribute to your model, by identifying which columns in your records are more important than others.
ColumnName (string) --
The name of a column.
Importance (float) --
The column importance score for the column, as a decimal.
LabelCount (integer) --
The number of labels available for this transform.
Schema (list) --
The Map<Column, Type> object that represents the schema that this transform accepts. Has an upper bound of 100 columns.
(dict) --
A key-value pair representing a column and data type that this transform can run against. The Schema parameter of the MLTransform may contain up to 100 of these structures.
Name (string) --
The name of the column.
DataType (string) --
The type of data in the column.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions.
GlueVersion (string) --
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
WorkerType (string) --
The type of predefined worker that is allocated when this task runs. Accepts a value of Standard, G.1X, or G.2X.
For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.
For the G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.
NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when this task runs.
Timeout (integer) --
The timeout for a task run for this transform in minutes. This is the maximum time that a task run for this transform can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
MaxRetries (integer) --
The maximum number of times to retry a task for this transform after a task run fails.
TransformEncryption (dict) --
The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
MlUserDataEncryption (dict) --
An MLUserDataEncryption object containing the encryption mode and customer-provided KMS key ID.
MlUserDataEncryptionMode (string) --
The encryption mode applied to user data. Valid values are:
DISABLED: encryption is disabled
SSEKMS: use of server-side encryption with Key Management Service (SSE-KMS) for user data stored in Amazon S3.
KmsKeyId (string) --
The ID for the customer-provided KMS key.
TaskRunSecurityConfigurationName (string) --
The name of the security configuration.
{'Transforms': {'InputRecordTables': {'AdditionalOptions': {'string': 'string'}}}}
Gets a sortable, filterable list of existing Glue machine learning transforms. Machine learning transforms are a special type of transform that use machine learning to learn the details of the transformation to be performed by learning from examples provided by humans. These transformations are then saved by Glue, and you can retrieve their metadata by calling GetMLTransforms .
See also: AWS API Documentation
Request Syntax
client.get_ml_transforms(
NextToken='string',
MaxResults=123,
Filter={
'Name': 'string',
'TransformType': 'FIND_MATCHES',
'Status': 'NOT_READY'|'READY'|'DELETING',
'GlueVersion': 'string',
'CreatedBefore': datetime(2015, 1, 1),
'CreatedAfter': datetime(2015, 1, 1),
'LastModifiedBefore': datetime(2015, 1, 1),
'LastModifiedAfter': datetime(2015, 1, 1),
'Schema': [
{
'Name': 'string',
'DataType': 'string'
},
]
},
Sort={
'Column': 'NAME'|'TRANSFORM_TYPE'|'STATUS'|'CREATED'|'LAST_MODIFIED',
'SortDirection': 'DESCENDING'|'ASCENDING'
}
)
string
A paginated token to offset the results.
integer
The maximum number of results to return.
dict
The filter transformation criteria.
Name (string) --
A unique transform name that is used to filter the machine learning transforms.
TransformType (string) --
The type of machine learning transform that is used to filter the machine learning transforms.
Status (string) --
Filters the list of machine learning transforms by the last known status of the transforms (to indicate whether a transform can be used or not). One of "NOT_READY", "READY", or "DELETING".
GlueVersion (string) --
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
CreatedBefore (datetime) --
The time and date before which the transforms were created.
CreatedAfter (datetime) --
The time and date after which the transforms were created.
LastModifiedBefore (datetime) --
Filter on transforms last modified before this date.
LastModifiedAfter (datetime) --
Filter on transforms last modified after this date.
Schema (list) --
Filters on datasets with a specific schema. The Map<Column, Type> object is an array of key-value pairs representing the schema this transform accepts, where Column is the name of a column, and Type is the type of the data such as an integer or string. Has an upper bound of 100 columns.
(dict) --
A key-value pair representing a column and data type that this transform can run against. The Schema parameter of the MLTransform may contain up to 100 of these structures.
Name (string) --
The name of the column.
DataType (string) --
The type of data in the column.
dict
The sorting criteria.
Column (string) -- [REQUIRED]
The column to be used in the sorting criteria that are associated with the machine learning transform.
SortDirection (string) -- [REQUIRED]
The sort direction to be used in the sorting criteria that are associated with the machine learning transform.
dict
Response Syntax
{
'Transforms': [
{
'TransformId': 'string',
'Name': 'string',
'Description': 'string',
'Status': 'NOT_READY'|'READY'|'DELETING',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'InputRecordTables': [
{
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
},
],
'Parameters': {
'TransformType': 'FIND_MATCHES',
'FindMatchesParameters': {
'PrimaryKeyColumnName': 'string',
'PrecisionRecallTradeoff': 123.0,
'AccuracyCostTradeoff': 123.0,
'EnforceProvidedLabels': True|False
}
},
'EvaluationMetrics': {
'TransformType': 'FIND_MATCHES',
'FindMatchesMetrics': {
'AreaUnderPRCurve': 123.0,
'Precision': 123.0,
'Recall': 123.0,
'F1': 123.0,
'ConfusionMatrix': {
'NumTruePositives': 123,
'NumFalsePositives': 123,
'NumTrueNegatives': 123,
'NumFalseNegatives': 123
},
'ColumnImportances': [
{
'ColumnName': 'string',
'Importance': 123.0
},
]
}
},
'LabelCount': 123,
'Schema': [
{
'Name': 'string',
'DataType': 'string'
},
],
'Role': 'string',
'GlueVersion': 'string',
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'Timeout': 123,
'MaxRetries': 123,
'TransformEncryption': {
'MlUserDataEncryption': {
'MlUserDataEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyId': 'string'
},
'TaskRunSecurityConfigurationName': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Transforms (list) --
A list of machine learning transforms.
(dict) --
A structure for a machine learning transform.
TransformId (string) --
The unique transform ID that is generated for the machine learning transform. The ID is guaranteed to be unique and does not change.
Name (string) --
A user-defined name for the machine learning transform. Names are not guaranteed unique and can be changed at any time.
Description (string) --
A user-defined, long-form description text for the machine learning transform. Descriptions are not guaranteed to be unique and can be changed at any time.
Status (string) --
The current status of the machine learning transform.
CreatedOn (datetime) --
A timestamp. The time and date that this machine learning transform was created.
LastModifiedOn (datetime) --
A timestamp. The last point in time when this machine learning transform was modified.
InputRecordTables (list) --
A list of Glue table definitions used by the transform.
(dict) --
The database and table in the Glue Data Catalog that is used for input or output data.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.
catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.
(string) --
(string) --
Parameters (dict) --
A TransformParameters object. You can use parameters to tune (customize) the behavior of the machine learning transform by specifying what data it learns from and your preference on various tradeoffs (such as precious vs. recall, or accuracy vs. cost).
TransformType (string) --
The type of machine learning transform.
For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
FindMatchesParameters (dict) --
The parameters for the find matches algorithm.
PrimaryKeyColumnName (string) --
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
PrecisionRecallTradeoff (float) --
The value selected when tuning your transform for a balance between precision and recall. A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.
The precision metric indicates how often your model is correct when it predicts a match.
The recall metric indicates that for an actual match, how often your model predicts the match.
AccuracyCostTradeoff (float) --
The value that is selected when tuning your transform for a balance between accuracy and cost. A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate FindMatches transform, sometimes with unacceptable accuracy.
Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall.
Cost measures how many compute resources, and thus money, are consumed to run the transform.
EnforceProvidedLabels (boolean) --
The value to switch on or off to force the output to match the provided labels from users. If the value is True , the find matches transform forces the output to match the provided labels. The results override the normal conflation results. If the value is False , the find matches transform does not ensure all the labels provided are respected, and the results rely on the trained model.
Note that setting this value to true may increase the conflation execution time.
EvaluationMetrics (dict) --
An EvaluationMetrics object. Evaluation metrics provide an estimate of the quality of your machine learning transform.
TransformType (string) --
The type of machine learning transform.
FindMatchesMetrics (dict) --
The evaluation metrics for the find matches algorithm.
AreaUnderPRCurve (float) --
The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs. recall. Higher values indicate that you have a more attractive precision vs. recall tradeoff.
For more information, see Precision and recall in Wikipedia.
Precision (float) --
The precision metric indicates when often your transform is correct when it predicts a match. Specifically, it measures how well the transform finds true positives from the total true positives possible.
For more information, see Precision and recall in Wikipedia.
Recall (float) --
The recall metric indicates that for an actual match, how often your transform predicts the match. Specifically, it measures how well the transform finds true positives from the total records in the source data.
For more information, see Precision and recall in Wikipedia.
F1 (float) --
The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.
For more information, see F1 score in Wikipedia.
ConfusionMatrix (dict) --
The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.
For more information, see Confusion matrix in Wikipedia.
NumTruePositives (integer) --
The number of matches in the data that the transform correctly found, in the confusion matrix for your transform.
NumFalsePositives (integer) --
The number of nonmatches in the data that the transform incorrectly classified as a match, in the confusion matrix for your transform.
NumTrueNegatives (integer) --
The number of nonmatches in the data that the transform correctly rejected, in the confusion matrix for your transform.
NumFalseNegatives (integer) --
The number of matches in the data that the transform didn't find, in the confusion matrix for your transform.
ColumnImportances (list) --
A list of ColumnImportance structures containing column importance metrics, sorted in order of descending importance.
(dict) --
A structure containing the column name and column importance score for a column.
Column importance helps you understand how columns contribute to your model, by identifying which columns in your records are more important than others.
ColumnName (string) --
The name of a column.
Importance (float) --
The column importance score for the column, as a decimal.
LabelCount (integer) --
A count identifier for the labeling files generated by Glue for this transform. As you create a better transform, you can iteratively download, label, and upload the labeling file.
Schema (list) --
A map of key-value pairs representing the columns and data types that this transform can run against. Has an upper bound of 100 columns.
(dict) --
A key-value pair representing a column and data type that this transform can run against. The Schema parameter of the MLTransform may contain up to 100 of these structures.
Name (string) --
The name of the column.
DataType (string) --
The type of data in the column.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions. The required permissions include both Glue service role permissions to Glue resources, and Amazon S3 permissions required by the transform.
This role needs Glue service role permissions to allow access to resources in Glue. See Attach a Policy to IAM Users That Access Glue.
This role needs permission to your Amazon Simple Storage Service (Amazon S3) sources, targets, temporary directory, scripts, and any libraries used by the task run for this transform.
GlueVersion (string) --
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
MaxCapacity is a mutually exclusive option with NumberOfWorkers and WorkerType .
If either NumberOfWorkers or WorkerType is set, then MaxCapacity cannot be set.
If MaxCapacity is set then neither NumberOfWorkers or WorkerType can be set.
If WorkerType is set, then NumberOfWorkers is required (and vice versa).
MaxCapacity and NumberOfWorkers must both be at least 1.
When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
WorkerType (string) --
The type of predefined worker that is allocated when a task of this transform runs. Accepts a value of Standard, G.1X, or G.2X.
For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.
For the G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.
MaxCapacity is a mutually exclusive option with NumberOfWorkers and WorkerType .
If either NumberOfWorkers or WorkerType is set, then MaxCapacity cannot be set.
If MaxCapacity is set then neither NumberOfWorkers or WorkerType can be set.
If WorkerType is set, then NumberOfWorkers is required (and vice versa).
MaxCapacity and NumberOfWorkers must both be at least 1.
NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a task of the transform runs.
If WorkerType is set, then NumberOfWorkers is required (and vice versa).
Timeout (integer) --
The timeout in minutes of the machine learning transform.
MaxRetries (integer) --
The maximum number of times to retry after an MLTaskRun of the machine learning transform fails.
TransformEncryption (dict) --
The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
MlUserDataEncryption (dict) --
An MLUserDataEncryption object containing the encryption mode and customer-provided KMS key ID.
MlUserDataEncryptionMode (string) --
The encryption mode applied to user data. Valid values are:
DISABLED: encryption is disabled
SSEKMS: use of server-side encryption with Key Management Service (SSE-KMS) for user data stored in Amazon S3.
KmsKeyId (string) --
The ID for the customer-provided KMS key.
TaskRunSecurityConfigurationName (string) --
The name of the security configuration.
NextToken (string) --
A pagination token, if more results are available.
{'JobUpdate': {'CodeGenConfigurationNodes': {'EvaluateDataQuality': {'Inputs': ['string'],
'Name': 'string',
'Output': 'PrimaryInput '
'| '
'EvaluationResults',
'PublishingOptions': {'CloudWatchMetricsEnabled': 'boolean',
'EvaluationContext': 'string',
'ResultsPublishingEnabled': 'boolean',
'ResultsS3Prefix': 'string'},
'Ruleset': 'string',
'StopJobOnFailureOptions': {'StopJobOnFailureTiming': 'Immediate '
'| '
'AfterDataLoad'}}}}}
Updates an existing job definition. The previous job definition is completely overwritten by this information.
See also: AWS API Documentation
Request Syntax
client.update_job(
JobName='string',
JobUpdate={
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
}
)
string
[REQUIRED]
The name of the job definition to update.
dict
[REQUIRED]
Specifies the values with which to update the job definition. Unspecified configuration is removed or reset to default values.
Description (string) --
Description of the job being defined.
LogUri (string) --
This field is reserved for future use.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role associated with this job (required).
ExecutionProperty (dict) --
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
MaxConcurrentRuns (integer) --
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
Command (dict) --
The JobCommand that runs this job (required).
Name (string) --
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
ScriptLocation (string) --
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
PythonVersion (string) --
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
DefaultArguments (dict) --
The default arguments for this job.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
(string) --
(string) --
NonOverridableArguments (dict) --
Non-overridable arguments for this job, specified as name-value pairs.
(string) --
(string) --
Connections (dict) --
The connections used for this job.
Connections (list) --
A list of connections used by the job.
(string) --
MaxRetries (integer) --
The maximum number of times to retry this job if it fails.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) to allocate to this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Timeout (integer) --
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
MaxCapacity (float) --
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
When you specify a Python shell job ( JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
When you specify an Apache Spark ETL job ( JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
For the Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.
For the G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job.
NotificationProperty (dict) --
Specifies the configuration properties of a job notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
CodeGenConfigurationNodes (dict) --
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
(string) --
(dict) --
CodeGenConfigurationNode enumerates all valid Node types. One and only one of its member variables can be populated.
AthenaConnectorSource (dict) --
Specifies a connector to an Amazon Athena data source.
Name (string) -- [REQUIRED]
The name of the data source.
ConnectionName (string) -- [REQUIRED]
The name of the connection that is associated with the connector.
ConnectorName (string) -- [REQUIRED]
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
ConnectionTable (string) --
The name of the table in the data source.
SchemaName (string) -- [REQUIRED]
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
OutputSchemas (list) --
Specifies the data schema for the custom Athena source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
JDBCConnectorSource (dict) --
Specifies a connector to a JDBC data source.
Name (string) -- [REQUIRED]
The name of the data source.
ConnectionName (string) -- [REQUIRED]
The name of the connection that is associated with the connector.
ConnectorName (string) -- [REQUIRED]
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
FilterPredicate (string) --
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
PartitionColumn (string) --
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
LowerBound (integer) --
The minimum value of partitionColumn that is used to decide partition stride.
UpperBound (integer) --
The maximum value of partitionColumn that is used to decide partition stride.
NumPartitions (integer) --
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
JobBookmarkKeys (list) --
The name of the job bookmark keys on which to sort.
(string) --
JobBookmarkKeysSortOrder (string) --
Specifies an ascending or descending sort order.
DataTypeMapping (dict) --
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
(string) --
(string) --
ConnectionTable (string) --
The name of the table in the data source.
Query (string) --
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
OutputSchemas (list) --
Specifies the data schema for the custom JDBC source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorSource (dict) --
Specifies a connector to an Apache Spark data source.
Name (string) -- [REQUIRED]
The name of the data source.
ConnectionName (string) -- [REQUIRED]
The name of the connection that is associated with the connector.
ConnectorName (string) -- [REQUIRED]
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies data schema for the custom spark source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogSource (dict) --
Specifies a data store in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data store.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
RedshiftSource (dict) --
Specifies an Amazon Redshift data store.
Name (string) -- [REQUIRED]
The name of the Amazon Redshift data store.
Database (string) -- [REQUIRED]
The database to read from.
Table (string) -- [REQUIRED]
The database table to read from.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
S3CatalogSource (dict) --
Specifies an Amazon S3 data store in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data store.
Database (string) -- [REQUIRED]
The database to read from.
Table (string) -- [REQUIRED]
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
S3CsvSource (dict) --
Specifies a command-separated value (CSV) data store stored in Amazon S3.
Name (string) -- [REQUIRED]
The name of the data store.
Paths (list) -- [REQUIRED]
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
Separator (string) -- [REQUIRED]
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Escaper (string) --
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
QuoteChar (string) -- [REQUIRED]
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
WithHeader (boolean) --
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
WriteHeader (boolean) --
A Boolean value that specifies whether to write the header to output. The default value is True .
SkipFirst (boolean) --
A Boolean value that specifies whether to skip the first data line. The default value is False .
OptimizePerformance (boolean) --
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
OutputSchemas (list) --
Specifies the data schema for the S3 CSV source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3JsonSource (dict) --
Specifies a JSON data store stored in Amazon S3.
Name (string) -- [REQUIRED]
The name of the data store.
Paths (list) -- [REQUIRED]
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
JsonPath (string) --
A JsonPath string defining the JSON data.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
OutputSchemas (list) --
Specifies the data schema for the S3 JSON source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3ParquetSource (dict) --
Specifies an Apache Parquet data store stored in Amazon S3.
Name (string) -- [REQUIRED]
The name of the data store.
Paths (list) -- [REQUIRED]
A list of the Amazon S3 paths to read from.
(string) --
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
(string) --
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
OutputSchemas (list) --
Specifies the data schema for the S3 Parquet source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
RelationalCatalogSource (dict) --
Specifies a Relational database data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
DynamoDBCatalogSource (dict) --
Specifies a DynamoDB data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
JDBCConnectorTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) -- [REQUIRED]
The name of the connection that is associated with the connector.
ConnectionTable (string) -- [REQUIRED]
The name of the table in the data target.
ConnectorName (string) -- [REQUIRED]
The name of a connector that will be used.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the JDBC target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorTarget (dict) --
Specifies a target that uses an Apache Spark connector.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
ConnectionName (string) -- [REQUIRED]
The name of a connection for an Apache Spark connector.
ConnectorName (string) -- [REQUIRED]
The name of an Apache Spark connector.
ConnectionType (string) -- [REQUIRED]
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
(string) --
(string) --
OutputSchemas (list) --
Specifies the data schema for the custom spark target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogTarget (dict) --
Specifies a target that uses a Glue Data Catalog table.
Name (string) -- [REQUIRED]
The name of your data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
Table (string) -- [REQUIRED]
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
RedshiftTarget (dict) --
Specifies a target that uses Amazon Redshift.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
UpsertRedshiftOptions (dict) --
The set of options to configure an upsert operation when writing to a Redshift target.
TableLocation (string) --
The physical location of the Redshift table.
ConnectionName (string) --
The name of the connection to use to write to Redshift.
UpsertKeys (list) --
The keys used to determine whether to perform an update or insert.
(string) --
S3CatalogTarget (dict) --
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
Database (string) -- [REQUIRED]
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
S3GlueParquetTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) -- [REQUIRED]
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
S3DirectTarget (dict) --
Specifies a data target that writes to Amazon S3.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Path (string) -- [REQUIRED]
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Format (string) -- [REQUIRED]
Specifies the data output format for the target.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
ApplyMapping (dict) --
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Mapping (list) -- [REQUIRED]
Specifies the mapping of data property keys in the data source to data property keys in the data target.
(dict) --
Specifies the mapping of data property keys.
ToKey (string) --
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
FromPath (list) --
The table or column to be modified.
(string) --
FromType (string) --
The type of the data to be modified.
ToType (string) --
The data type that the data is to be modified to.
Dropped (boolean) --
If true, then the column is removed.
Children (list) --
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
SelectFields (dict) --
Specifies a transform that chooses the data property keys that you want to keep.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Paths (list) -- [REQUIRED]
A JSON path to a variable in the data structure.
(list) --
(string) --
DropFields (dict) --
Specifies a transform that chooses the data property keys that you want to drop.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Paths (list) -- [REQUIRED]
A JSON path to a variable in the data structure.
(list) --
(string) --
RenameField (dict) --
Specifies a transform that renames a single data property key.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
SourcePath (list) -- [REQUIRED]
A JSON path to a variable in the data structure for the source data.
(string) --
TargetPath (list) -- [REQUIRED]
A JSON path to a variable in the data structure for the target data.
(string) --
Spigot (dict) --
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Path (string) -- [REQUIRED]
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Topk (integer) --
Specifies a number of records to write starting from the beginning of the dataset.
Prob (float) --
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Join (dict) --
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
JoinType (string) -- [REQUIRED]
Specifies the type of join to be performed on the datasets.
Columns (list) -- [REQUIRED]
A list of the two columns to be joined.
(dict) --
Specifies a column to be joined.
From (string) -- [REQUIRED]
The column to be joined.
Keys (list) -- [REQUIRED]
The key of the column to be joined.
(list) --
(string) --
SplitFields (dict) --
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Paths (list) -- [REQUIRED]
A JSON path to a variable in the data structure.
(list) --
(string) --
SelectFromCollection (dict) --
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Index (integer) -- [REQUIRED]
The index for the DynamicFrame to be selected.
FillMissingValues (dict) --
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
ImputedPath (string) -- [REQUIRED]
A JSON path to a variable in the data structure for the dataset that is imputed.
FilledPath (string) --
A JSON path to a variable in the data structure for the dataset that is filled.
Filter (dict) --
Specifies a transform that splits a dataset into two, based on a filter condition.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
LogicalOperator (string) -- [REQUIRED]
The operator used to filter rows by comparing the key value to a specified value.
Filters (list) -- [REQUIRED]
Specifies a filter expression.
(dict) --
Specifies a filter expression.
Operation (string) -- [REQUIRED]
The type of operation to perform in the expression.
Negated (boolean) --
Whether the expression is to be negated.
Values (list) -- [REQUIRED]
A list of filter values.
(dict) --
Represents a single entry in the list of values for a FilterExpression .
Type (string) -- [REQUIRED]
The type of filter value.
Value (list) -- [REQUIRED]
The value to be associated.
(string) --
CustomCode (dict) --
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Code (string) -- [REQUIRED]
The custom code that is used to perform the data transformation.
ClassName (string) -- [REQUIRED]
The name defined for the custom code node class.
OutputSchemas (list) --
Specifies the data schema for the custom code transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkSQL (dict) --
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
(string) --
SqlQuery (string) -- [REQUIRED]
A SQL query that must use Spark SQL syntax and return a single data set.
SqlAliases (list) -- [REQUIRED]
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
(dict) --
Represents a single entry in the list of values for SqlAliases .
From (string) -- [REQUIRED]
A table, or a column in a table.
Alias (string) -- [REQUIRED]
A temporary name given to a table, or a column in a table.
OutputSchemas (list) --
Specifies the data schema for the SparkSQL transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) -- [REQUIRED]
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
DirectKinesisSource (dict) --
Specifies a direct Amazon Kinesis data source.
Name (string) -- [REQUIRED]
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DirectKafkaSource (dict) --
Specifies an Apache Kafka data store.
Name (string) -- [REQUIRED]
The name of the data store.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKinesisSource (dict) --
Specifies a Kinesis data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
Database (string) -- [REQUIRED]
The name of the database to read from.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKafkaSource (dict) --
Specifies an Apache Kafka data store in the Data Catalog.
Name (string) -- [REQUIRED]
The name of the data store.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
Database (string) -- [REQUIRED]
The name of the database to read from.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DropNullFields (dict) --
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
NullCheckBoxList (dict) --
A structure that represents whether certain values are recognized as null values for removal.
IsEmpty (boolean) --
Specifies that an empty string is considered as a null value.
IsNullString (boolean) --
Specifies that a value spelling out the word 'null' is considered as a null value.
IsNegOne (boolean) --
Specifies that an integer value of -1 is considered as a null value.
NullTextList (list) --
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
(dict) --
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
Value (string) -- [REQUIRED]
The value of the null placeholder.
Datatype (dict) -- [REQUIRED]
The datatype of the value.
Id (string) -- [REQUIRED]
The datatype of the value.
Label (string) -- [REQUIRED]
A label assigned to the datatype.
Merge (dict) --
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Source (string) -- [REQUIRED]
The source DynamicFrame that will be merged with a staging DynamicFrame .
PrimaryKeys (list) -- [REQUIRED]
The list of primary key fields to match records from the source and staging dynamic frames.
(list) --
(string) --
Union (dict) --
Specifies a transform that combines the rows from two or more datasets into a single result.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The node ID inputs to the transform.
(string) --
UnionType (string) -- [REQUIRED]
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
PIIDetection (dict) --
Specifies a transform that identifies, removes or masks PII data.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The node ID inputs to the transform.
(string) --
PiiType (string) -- [REQUIRED]
Indicates the type of PIIDetection transform.
EntityTypesToDetect (list) -- [REQUIRED]
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
(string) --
OutputColumnName (string) --
Indicates the output column name that will contain any entity type detected in that row.
SampleFraction (float) --
Indicates the fraction of the data to sample when scanning for PII entities.
ThresholdFraction (float) --
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
MaskValue (string) --
Indicates the value that will replace the detected entity.
Aggregate (dict) --
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
Specifies the fields and rows to use as inputs for the aggregate transform.
(string) --
Groups (list) -- [REQUIRED]
Specifies the fields to group by.
(list) --
(string) --
Aggs (list) -- [REQUIRED]
Specifies the aggregate functions to be performed on specified fields.
(dict) --
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Column (list) -- [REQUIRED]
Specifies the column on the data set on which the aggregation function will be applied.
(string) --
AggFunc (string) -- [REQUIRED]
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
DropDuplicates (dict) --
Specifies a transform that removes rows of repeating data from a data set.
Name (string) -- [REQUIRED]
The name of the transform node.
Inputs (list) -- [REQUIRED]
The data inputs identified by their node names.
(string) --
Columns (list) --
The name of the columns to be merged or removed if repeating.
(list) --
(string) --
GovernedCatalogTarget (dict) --
Specifies a data target that writes to a goverened catalog.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
(list) --
(string) --
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
Database (string) -- [REQUIRED]
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the governed catalog.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
GovernedCatalogSource (dict) --
Specifies a data source in a goverened Data Catalog.
Name (string) -- [REQUIRED]
The name of the data store.
Database (string) -- [REQUIRED]
The database to read from.
Table (string) -- [REQUIRED]
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
MicrosoftSQLServerCatalogSource (dict) --
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
MySQLCatalogSource (dict) --
Specifies a MySQL data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
OracleSQLCatalogSource (dict) --
Specifies an Oracle data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
PostgreSQLCatalogSource (dict) --
Specifies a PostgresSQL data source in the Glue Data Catalog.
Name (string) -- [REQUIRED]
The name of the data source.
Database (string) -- [REQUIRED]
The name of the database to read from.
Table (string) -- [REQUIRED]
The name of the table in the database to read from.
MicrosoftSQLServerCatalogTarget (dict) --
Specifies a target that uses Microsoft SQL.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
MySQLCatalogTarget (dict) --
Specifies a target that uses MySQL.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
OracleSQLCatalogTarget (dict) --
Specifies a target that uses Oracle SQL.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
PostgreSQLCatalogTarget (dict) --
Specifies a target that uses Postgres SQL.
Name (string) -- [REQUIRED]
The name of the data target.
Inputs (list) -- [REQUIRED]
The nodes that are inputs to the data target.
(string) --
Database (string) -- [REQUIRED]
The name of the database to write to.
Table (string) -- [REQUIRED]
The name of the table in the database to write to.
DynamicTransform (dict) --
Specifies a custom visual transform created by a user.
Name (string) -- [REQUIRED]
Specifies the name of the dynamic transform.
TransformName (string) -- [REQUIRED]
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Inputs (list) -- [REQUIRED]
Specifies the inputs for the dynamic transform that are required.
(string) --
Parameters (list) --
Specifies the parameters of the dynamic transform.
(dict) --
Specifies the parameters in the config file of the dynamic transform.
Name (string) -- [REQUIRED]
Specifies the name of the parameter in the config file of the dynamic transform.
Type (string) -- [REQUIRED]
Specifies the parameter type in the config file of the dynamic transform.
ValidationRule (string) --
Specifies the validation rule in the config file of the dynamic transform.
ValidationMessage (string) --
Specifies the validation message in the config file of the dynamic transform.
Value (list) --
Specifies the value of the parameter in the config file of the dynamic transform.
(string) --
ListType (string) --
Specifies the list type of the parameter in the config file of the dynamic transform.
IsOptional (boolean) --
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
FunctionName (string) -- [REQUIRED]
Specifies the name of the function of the dynamic transform.
Path (string) -- [REQUIRED]
Specifies the path of the dynamic transform source and config files.
Version (string) --
This field is not used and will be deprecated in future release.
EvaluateDataQuality (dict) --
Specifies your data quality evaluation criteria.
Name (string) -- [REQUIRED]
The name of the data quality evaluation.
Inputs (list) -- [REQUIRED]
The inputs of your data quality evaluation.
(string) --
Ruleset (string) -- [REQUIRED]
The ruleset for your data quality evaluation.
Output (string) --
The output of your data quality evaluation.
PublishingOptions (dict) --
Options to configure how your results are published.
EvaluationContext (string) --
The context of the evaluation.
ResultsS3Prefix (string) --
The Amazon S3 prefix prepended to the results.
CloudWatchMetricsEnabled (boolean) --
Enable metrics for your data quality results.
ResultsPublishingEnabled (boolean) --
Enable publishing for your data quality results.
StopJobOnFailureOptions (dict) --
Options to configure how your job will stop if your data quality evaluation fails.
StopJobOnFailureTiming (string) --
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
SourceControlDetails (dict) --
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
Provider (string) --
The provider for the remote repository.
Repository (string) --
The name of the remote repository that contains the job artifacts.
Owner (string) --
The owner of the remote repository that contains the job artifacts.
Branch (string) --
An optional branch in the remote repository.
Folder (string) --
An optional folder in the remote repository.
LastCommitId (string) --
The last commit ID for a commit in the remote repository.
AuthStrategy (string) --
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
AuthToken (string) --
The value of an authorization token.
dict
Response Syntax
{
'JobName': 'string'
}
Response Structure
(dict) --
JobName (string) --
Returns the name of the updated job definition.