2026/10/29 - AWS Clean Rooms Service - 8 updated api methods
Changes Adds support for the PySpark 2.0 analysis template format and for choosing the file format (CSV or Parquet) of protected job results written to Amazon S3, including in a membership's default job result configuration.
{'collaborationAnalysisTemplates': {'format': {'PYSPARK_2_0'}}}
Retrieves multiple analysis templates within a collaboration by their Amazon Resource Names (ARNs).
See also: AWS API Documentation
Request Syntax
client.batch_get_collaboration_analysis_template(
collaborationIdentifier='string',
analysisTemplateArns=[
'string',
]
)
string
[REQUIRED]
A unique identifier for the collaboration that the analysis templates belong to. Currently accepts collaboration ID.
list
[REQUIRED]
The Amazon Resource Name (ARN) associated with the analysis template within a collaboration.
(string) --
dict
Response Syntax
{
'collaborationAnalysisTemplates': [
{
'id': 'string',
'arn': 'string',
'collaborationId': 'string',
'collaborationArn': 'string',
'description': 'string',
'creatorAccountId': 'string',
'name': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'schema': {
'referencedTables': [
'string',
]
},
'format': 'SQL'|'PYSPARK_1_0'|'PYSPARK_2_0',
'source': {
'text': 'string',
'artifacts': {
'entryPoint': {
'location': {
'bucket': 'string',
'key': 'string'
}
},
'additionalArtifacts': [
{
'location': {
'bucket': 'string',
'key': 'string'
}
},
],
'roleArn': 'string'
}
},
'sourceMetadata': {
'artifacts': {
'entryPointHash': {
'sha256': 'string'
},
'additionalArtifactHashes': [
{
'sha256': 'string'
},
]
}
},
'analysisParameters': [
{
'name': 'string',
'type': 'SMALLINT'|'INTEGER'|'BIGINT'|'DECIMAL'|'REAL'|'DOUBLE_PRECISION'|'BOOLEAN'|'CHAR'|'VARCHAR'|'DATE'|'TIMESTAMP'|'TIMESTAMPTZ'|'TIME'|'TIMETZ'|'VARBYTE'|'BINARY'|'BYTE'|'CHARACTER'|'DOUBLE'|'FLOAT'|'INT'|'LONG'|'NUMERIC'|'SHORT'|'STRING'|'TIMESTAMP_LTZ'|'TIMESTAMP_NTZ'|'TINYINT',
'defaultValue': 'string'
},
],
'validations': [
{
'type': 'DIFFERENTIAL_PRIVACY',
'status': 'VALID'|'INVALID'|'UNABLE_TO_VALIDATE',
'reasons': [
{
'message': 'string'
},
]
},
],
'errorMessageConfiguration': {
'type': 'DETAILED'
},
'syntheticDataParameters': {
'mlSyntheticDataParameters': {
'epsilon': 123.0,
'maxMembershipInferenceAttackScore': 123.0,
'columnClassification': {
'columnMapping': [
{
'columnName': 'string',
'columnType': 'CATEGORICAL'|'NUMERICAL',
'isPredictiveValue': True|False
},
]
}
}
}
},
],
'errors': [
{
'arn': 'string',
'code': 'string',
'message': 'string'
},
]
}
Response Structure
(dict) --
collaborationAnalysisTemplates (list) --
The retrieved list of analysis templates within a collaboration.
(dict) --
The analysis template within a collaboration.
id (string) --
The identifier of the analysis template.
arn (string) --
The Amazon Resource Name (ARN) of the analysis template.
collaborationId (string) --
A unique identifier for the collaboration that the analysis templates belong to. Currently accepts collaboration ID.
collaborationArn (string) --
The unique ARN for the analysis template’s associated collaboration.
description (string) --
The description of the analysis template.
creatorAccountId (string) --
The identifier used to reference members of the collaboration. Currently only supports Amazon Web Services account ID.
name (string) --
The name of the analysis template.
createTime (datetime) --
The time that the analysis template within a collaboration was created.
updateTime (datetime) --
The time that the analysis template in the collaboration was last updated.
schema (dict) --
The entire schema object.
referencedTables (list) --
The tables referenced in the analysis schema.
(string) --
format (string) --
The format of the analysis template in the collaboration.
source (dict) --
The source of the analysis template within a collaboration.
text (string) --
The query text.
artifacts (dict) --
The artifacts of the analysis source.
entryPoint (dict) --
The entry point for the analysis template artifacts.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
additionalArtifacts (list) --
Additional artifacts for the analysis template.
(dict) --
The analysis template artifact.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
roleArn (string) --
The role ARN for the analysis template artifacts.
sourceMetadata (dict) --
The source metadata for the collaboration analysis template.
artifacts (dict) --
The artifacts of the analysis source metadata.
entryPointHash (dict) --
The hash of the entry point for the analysis template artifact metadata.
sha256 (string) --
The SHA-256 hash value.
additionalArtifactHashes (list) --
Additional artifact hashes for the analysis template.
(dict) --
Hash
sha256 (string) --
The SHA-256 hash value.
analysisParameters (list) --
The analysis parameters that have been specified in the analysis template.
(dict) --
Optional. The member who can query can provide this placeholder for a literal data value in an analysis template.
name (string) --
The name of the parameter. The name must use only alphanumeric or underscore (_) characters.
type (string) --
The type of parameter.
defaultValue (string) --
Optional. The default value that is applied in the analysis template. The member who can query can override this value in the query editor.
validations (list) --
The validations that were performed.
(dict) --
The status details of the analysis template validation. Clean Rooms Differential Privacy uses a general-purpose query structure to support complex SQL queries and validates whether an analysis template fits that general-purpose query structure. Validation is performed when analysis templates are created and fetched. Because analysis templates are immutable by design, we recommend that you create analysis templates after you associate the configured tables with their analysis rule to your collaboration.
For more information, see https://docs.aws.amazon.com/clean-rooms/latest/userguide/analysis-rules-custom.html#custom-diff-privacy.
type (string) --
The type of validation that was performed.
status (string) --
The status of the validation.
reasons (list) --
The reasons for the validation results.
(dict) --
The reasons for the validation results.
message (string) --
The validation message.
errorMessageConfiguration (dict) --
The configuration that specifies the level of detail in error messages returned by analyses using this template. When set to DETAILED, error messages include more information to help troubleshoot issues with PySpark jobs. Detailed error messages may expose underlying data, including sensitive information. Recommended for faster troubleshooting in development and testing environments.
type (string) --
The level of detail for error messages returned by the PySpark job. When set to DETAILED, error messages include more information to help troubleshoot issues with your PySpark job.
Because this setting may expose sensitive data, it is recommended for development and testing environments.
syntheticDataParameters (dict) --
The synthetic data generation parameters configured for this collaboration analysis template.
mlSyntheticDataParameters (dict) --
The machine learning-specific parameters for synthetic data generation.
epsilon (float) --
The epsilon value for differential privacy when generating synthetic data. Lower values provide stronger privacy guarantees but may reduce data utility.
maxMembershipInferenceAttackScore (float) --
The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
columnClassification (dict) --
Classification details for data columns that specify how each column should be treated during synthetic data generation.
columnMapping (list) --
A mapping that defines the classification of data columns for synthetic data generation and specifies how each column should be handled during the privacy-preserving data synthesis process.
(dict) --
Properties that define how a specific data column should be handled during synthetic data generation, including its name, type, and role in predictive modeling.
columnName (string) --
The name of the data column as it appears in the dataset.
columnType (string) --
The data type of the column, which determines how the synthetic data generation algorithm processes and synthesizes values for this column.
isPredictiveValue (boolean) --
Indicates if this column contains predictive values that should be treated as target variables in machine learning models. This affects how the synthetic data generation preserves statistical relationships.
errors (list) --
Error reasons for collaboration analysis templates that could not be retrieved. One error is returned for every collaboration analysis template that could not be retrieved.
(dict) --
Details of errors thrown by the call to retrieve multiple analysis templates within a collaboration by their identifiers.
arn (string) --
The Amazon Resource Name (ARN) of the analysis template.
code (string) --
An error code for the error.
message (string) --
A description of why the call failed.
{'format': {'PYSPARK_2_0'}}
Response {'analysisTemplate': {'format': {'PYSPARK_2_0'}}}
Creates a new analysis template.
See also: AWS API Documentation
Request Syntax
client.create_analysis_template(
description='string',
membershipIdentifier='string',
name='string',
format='SQL'|'PYSPARK_1_0'|'PYSPARK_2_0',
source={
'text': 'string',
'artifacts': {
'entryPoint': {
'location': {
'bucket': 'string',
'key': 'string'
}
},
'additionalArtifacts': [
{
'location': {
'bucket': 'string',
'key': 'string'
}
},
],
'roleArn': 'string'
}
},
tags={
'string': 'string'
},
analysisParameters=[
{
'name': 'string',
'type': 'SMALLINT'|'INTEGER'|'BIGINT'|'DECIMAL'|'REAL'|'DOUBLE_PRECISION'|'BOOLEAN'|'CHAR'|'VARCHAR'|'DATE'|'TIMESTAMP'|'TIMESTAMPTZ'|'TIME'|'TIMETZ'|'VARBYTE'|'BINARY'|'BYTE'|'CHARACTER'|'DOUBLE'|'FLOAT'|'INT'|'LONG'|'NUMERIC'|'SHORT'|'STRING'|'TIMESTAMP_LTZ'|'TIMESTAMP_NTZ'|'TINYINT',
'defaultValue': 'string'
},
],
schema={
'referencedTables': [
'string',
]
},
errorMessageConfiguration={
'type': 'DETAILED'
},
syntheticDataParameters={
'mlSyntheticDataParameters': {
'epsilon': 123.0,
'maxMembershipInferenceAttackScore': 123.0,
'columnClassification': {
'columnMapping': [
{
'columnName': 'string',
'columnType': 'CATEGORICAL'|'NUMERICAL',
'isPredictiveValue': True|False
},
]
}
}
}
)
string
The description of the analysis template.
string
[REQUIRED]
The identifier for a membership resource.
string
[REQUIRED]
The name of the analysis template.
string
[REQUIRED]
The format of the analysis template.
dict
[REQUIRED]
The information in the analysis template.
text (string) --
The query text.
artifacts (dict) --
The artifacts of the analysis source.
entryPoint (dict) -- [REQUIRED]
The entry point for the analysis template artifacts.
location (dict) -- [REQUIRED]
The artifact location.
bucket (string) -- [REQUIRED]
The bucket name.
key (string) -- [REQUIRED]
The object key.
additionalArtifacts (list) --
Additional artifacts for the analysis template.
(dict) --
The analysis template artifact.
location (dict) -- [REQUIRED]
The artifact location.
bucket (string) -- [REQUIRED]
The bucket name.
key (string) -- [REQUIRED]
The object key.
roleArn (string) -- [REQUIRED]
The role ARN for the analysis template artifacts.
dict
An optional label that you can assign to a resource when you create it. Each tag consists of a key and an optional value, both of which you define. When you use tagging, you can also use tag-based access control in IAM policies to control access to this resource.
(string) --
(string) --
list
The parameters of the analysis template.
(dict) --
Optional. The member who can query can provide this placeholder for a literal data value in an analysis template.
name (string) -- [REQUIRED]
The name of the parameter. The name must use only alphanumeric or underscore (_) characters.
type (string) -- [REQUIRED]
The type of parameter.
defaultValue (string) --
Optional. The default value that is applied in the analysis template. The member who can query can override this value in the query editor.
dict
A relation within an analysis.
referencedTables (list) --
The tables referenced in the analysis schema.
(string) --
dict
The configuration that specifies the level of detail in error messages returned by analyses using this template. When set to DETAILED, error messages include more information to help troubleshoot issues with PySpark jobs. Detailed error messages may expose underlying data, including sensitive information. Recommended for faster troubleshooting in development and testing environments.
type (string) -- [REQUIRED]
The level of detail for error messages returned by the PySpark job. When set to DETAILED, error messages include more information to help troubleshoot issues with your PySpark job.
Because this setting may expose sensitive data, it is recommended for development and testing environments.
dict
The parameters for generating synthetic data when running the analysis template.
mlSyntheticDataParameters (dict) --
The machine learning-specific parameters for synthetic data generation.
epsilon (float) -- [REQUIRED]
The epsilon value for differential privacy when generating synthetic data. Lower values provide stronger privacy guarantees but may reduce data utility.
maxMembershipInferenceAttackScore (float) -- [REQUIRED]
The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
columnClassification (dict) -- [REQUIRED]
Classification details for data columns that specify how each column should be treated during synthetic data generation.
columnMapping (list) -- [REQUIRED]
A mapping that defines the classification of data columns for synthetic data generation and specifies how each column should be handled during the privacy-preserving data synthesis process.
(dict) --
Properties that define how a specific data column should be handled during synthetic data generation, including its name, type, and role in predictive modeling.
columnName (string) -- [REQUIRED]
The name of the data column as it appears in the dataset.
columnType (string) -- [REQUIRED]
The data type of the column, which determines how the synthetic data generation algorithm processes and synthesizes values for this column.
isPredictiveValue (boolean) -- [REQUIRED]
Indicates if this column contains predictive values that should be treated as target variables in machine learning models. This affects how the synthetic data generation preserves statistical relationships.
dict
Response Syntax
{
'analysisTemplate': {
'id': 'string',
'arn': 'string',
'collaborationId': 'string',
'collaborationArn': 'string',
'membershipId': 'string',
'membershipArn': 'string',
'description': 'string',
'name': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'schema': {
'referencedTables': [
'string',
]
},
'format': 'SQL'|'PYSPARK_1_0'|'PYSPARK_2_0',
'source': {
'text': 'string',
'artifacts': {
'entryPoint': {
'location': {
'bucket': 'string',
'key': 'string'
}
},
'additionalArtifacts': [
{
'location': {
'bucket': 'string',
'key': 'string'
}
},
],
'roleArn': 'string'
}
},
'sourceMetadata': {
'artifacts': {
'entryPointHash': {
'sha256': 'string'
},
'additionalArtifactHashes': [
{
'sha256': 'string'
},
]
}
},
'analysisParameters': [
{
'name': 'string',
'type': 'SMALLINT'|'INTEGER'|'BIGINT'|'DECIMAL'|'REAL'|'DOUBLE_PRECISION'|'BOOLEAN'|'CHAR'|'VARCHAR'|'DATE'|'TIMESTAMP'|'TIMESTAMPTZ'|'TIME'|'TIMETZ'|'VARBYTE'|'BINARY'|'BYTE'|'CHARACTER'|'DOUBLE'|'FLOAT'|'INT'|'LONG'|'NUMERIC'|'SHORT'|'STRING'|'TIMESTAMP_LTZ'|'TIMESTAMP_NTZ'|'TINYINT',
'defaultValue': 'string'
},
],
'validations': [
{
'type': 'DIFFERENTIAL_PRIVACY',
'status': 'VALID'|'INVALID'|'UNABLE_TO_VALIDATE',
'reasons': [
{
'message': 'string'
},
]
},
],
'errorMessageConfiguration': {
'type': 'DETAILED'
},
'syntheticDataParameters': {
'mlSyntheticDataParameters': {
'epsilon': 123.0,
'maxMembershipInferenceAttackScore': 123.0,
'columnClassification': {
'columnMapping': [
{
'columnName': 'string',
'columnType': 'CATEGORICAL'|'NUMERICAL',
'isPredictiveValue': True|False
},
]
}
}
}
}
}
Response Structure
(dict) --
analysisTemplate (dict) --
The analysis template.
id (string) --
The identifier for the analysis template.
arn (string) --
The Amazon Resource Name (ARN) of the analysis template.
collaborationId (string) --
The unique ID for the associated collaboration of the analysis template.
collaborationArn (string) --
The unique ARN for the analysis template’s associated collaboration.
membershipId (string) --
The identifier of a member who created the analysis template.
membershipArn (string) --
The Amazon Resource Name (ARN) of the member who created the analysis template.
description (string) --
The description of the analysis template.
name (string) --
The name of the analysis template.
createTime (datetime) --
The time that the analysis template was created.
updateTime (datetime) --
The time that the analysis template was last updated.
schema (dict) --
The entire schema object.
referencedTables (list) --
The tables referenced in the analysis schema.
(string) --
format (string) --
The format of the analysis template.
source (dict) --
The source of the analysis template.
text (string) --
The query text.
artifacts (dict) --
The artifacts of the analysis source.
entryPoint (dict) --
The entry point for the analysis template artifacts.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
additionalArtifacts (list) --
Additional artifacts for the analysis template.
(dict) --
The analysis template artifact.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
roleArn (string) --
The role ARN for the analysis template artifacts.
sourceMetadata (dict) --
The source metadata for the analysis template.
artifacts (dict) --
The artifacts of the analysis source metadata.
entryPointHash (dict) --
The hash of the entry point for the analysis template artifact metadata.
sha256 (string) --
The SHA-256 hash value.
additionalArtifactHashes (list) --
Additional artifact hashes for the analysis template.
(dict) --
Hash
sha256 (string) --
The SHA-256 hash value.
analysisParameters (list) --
The parameters of the analysis template.
(dict) --
Optional. The member who can query can provide this placeholder for a literal data value in an analysis template.
name (string) --
The name of the parameter. The name must use only alphanumeric or underscore (_) characters.
type (string) --
The type of parameter.
defaultValue (string) --
Optional. The default value that is applied in the analysis template. The member who can query can override this value in the query editor.
validations (list) --
Information about the validations performed on the analysis template.
(dict) --
The status details of the analysis template validation. Clean Rooms Differential Privacy uses a general-purpose query structure to support complex SQL queries and validates whether an analysis template fits that general-purpose query structure. Validation is performed when analysis templates are created and fetched. Because analysis templates are immutable by design, we recommend that you create analysis templates after you associate the configured tables with their analysis rule to your collaboration.
For more information, see https://docs.aws.amazon.com/clean-rooms/latest/userguide/analysis-rules-custom.html#custom-diff-privacy.
type (string) --
The type of validation that was performed.
status (string) --
The status of the validation.
reasons (list) --
The reasons for the validation results.
(dict) --
The reasons for the validation results.
message (string) --
The validation message.
errorMessageConfiguration (dict) --
The configuration that specifies the level of detail in error messages returned by analyses using this template. When set to DETAILED, error messages include more information to help troubleshoot issues with PySpark jobs. Detailed error messages may expose underlying data, including sensitive information. Recommended for faster troubleshooting in development and testing environments.
type (string) --
The level of detail for error messages returned by the PySpark job. When set to DETAILED, error messages include more information to help troubleshoot issues with your PySpark job.
Because this setting may expose sensitive data, it is recommended for development and testing environments.
syntheticDataParameters (dict) --
The parameters used to generate synthetic data for this analysis template.
mlSyntheticDataParameters (dict) --
The machine learning-specific parameters for synthetic data generation.
epsilon (float) --
The epsilon value for differential privacy when generating synthetic data. Lower values provide stronger privacy guarantees but may reduce data utility.
maxMembershipInferenceAttackScore (float) --
The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
columnClassification (dict) --
Classification details for data columns that specify how each column should be treated during synthetic data generation.
columnMapping (list) --
A mapping that defines the classification of data columns for synthetic data generation and specifies how each column should be handled during the privacy-preserving data synthesis process.
(dict) --
Properties that define how a specific data column should be handled during synthetic data generation, including its name, type, and role in predictive modeling.
columnName (string) --
The name of the data column as it appears in the dataset.
columnType (string) --
The data type of the column, which determines how the synthetic data generation algorithm processes and synthesizes values for this column.
isPredictiveValue (boolean) --
Indicates if this column contains predictive values that should be treated as target variables in machine learning models. This affects how the synthetic data generation preserves statistical relationships.
{'defaultJobResultConfiguration': {'outputConfiguration': {'s3': {'resultFormat': 'CSV '
'| '
'PARQUET'}}}}
Response {'membership': {'defaultJobResultConfiguration': {'outputConfiguration': {'s3': {'resultFormat': 'CSV '
'| '
'PARQUET'}}}}}
Creates a membership for a specific collaboration identifier and joins the collaboration.
See also: AWS API Documentation
Request Syntax
client.create_membership(
collaborationIdentifier='string',
queryLogStatus='ENABLED'|'DISABLED',
jobLogStatus='ENABLED'|'DISABLED',
tags={
'string': 'string'
},
defaultResultConfiguration={
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string',
'singleFileOutput': True|False
}
},
'roleArn': 'string'
},
defaultJobResultConfiguration={
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string'
}
},
'roleArn': 'string'
},
paymentConfiguration={
'queryCompute': {
'isResponsible': True|False
},
'machineLearning': {
'modelTraining': {
'isResponsible': True|False
},
'modelInference': {
'isResponsible': True|False
},
'syntheticDataGeneration': {
'isResponsible': True|False
}
},
'jobCompute': {
'isResponsible': True|False
}
},
isMetricsEnabled=True|False
)
string
[REQUIRED]
The unique ID for the associated collaboration.
string
[REQUIRED]
An indicator as to whether query logging has been enabled or disabled for the membership.
When ENABLED, Clean Rooms logs details about queries run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
string
An indicator as to whether job logging has been enabled or disabled for the collaboration.
When ENABLED, Clean Rooms logs details about jobs run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
dict
An optional label that you can assign to a resource when you create it. Each tag consists of a key and an optional value, both of which you define. When you use tagging, you can also use tag-based access control in IAM policies to control access to this resource.
(string) --
(string) --
dict
The default protected query result configuration as specified by the member who can receive results.
outputConfiguration (dict) -- [REQUIRED]
Configuration for protected query results.
s3 (dict) --
Contains the configuration to write the query results to S3.
resultFormat (string) -- [REQUIRED]
Intended file format of the result.
bucket (string) -- [REQUIRED]
The S3 bucket to unload the protected query results.
keyPrefix (string) --
The S3 prefix to unload the protected query results.
singleFileOutput (boolean) --
Indicates whether files should be output as a single file ( TRUE) or output as multiple files ( FALSE). This parameter is only supported for analyses with the Spark analytics engine.
roleArn (string) --
The unique ARN for an IAM role that is used by Clean Rooms to write protected query results to the result location, given by the member who can receive results.
dict
The default job result configuration that determines how job results are protected and managed within this membership. This configuration applies to all jobs.
outputConfiguration (dict) -- [REQUIRED]
The output configuration for a protected job result.
s3 (dict) --
Contains the configuration to write the job results to S3.
resultFormat (string) --
The file format of the protected job results. If you don't specify a format, results are written as CSV.
bucket (string) -- [REQUIRED]
The S3 bucket for job output.
keyPrefix (string) --
The S3 prefix to unload the protected job results.
roleArn (string) -- [REQUIRED]
The unique ARN for an IAM role that is used by Clean Rooms to write protected job results to the result location, given by the member who can receive results.
dict
The payment responsibilities accepted by the collaboration member.
Not required if the collaboration member has the member ability to run queries.
Required if the collaboration member doesn't have the member ability to run queries but is configured as a payer by the collaboration creator.
queryCompute (dict) -- [REQUIRED]
The payment responsibilities accepted by the collaboration member for query compute costs.
isResponsible (boolean) -- [REQUIRED]
Indicates whether the collaboration member has accepted to pay for query compute costs ( TRUE) or has not accepted to pay for query compute costs ( FALSE).
If the collaboration creator has not specified anyone to pay for query compute costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query compute costs.
If you set the value to TRUE but you are not responsible to pay for query compute costs.
machineLearning (dict) --
The payment responsibilities accepted by the collaboration member for machine learning costs.
modelTraining (dict) --
The payment responsibilities accepted by the member for model training.
isResponsible (boolean) -- [REQUIRED]
Indicates whether the collaboration member has accepted to pay for model training costs ( TRUE) or has not accepted to pay for model training costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model training costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model training costs.
If you set the value to TRUE but you are not responsible to pay for model training costs.
modelInference (dict) --
The payment responsibilities accepted by the member for model inference.
isResponsible (boolean) -- [REQUIRED]
Indicates whether the collaboration member has accepted to pay for model inference costs ( TRUE) or has not accepted to pay for model inference costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model inference costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model inference costs.
If you set the value to TRUE but you are not responsible to pay for model inference costs.
syntheticDataGeneration (dict) --
The payment configuration for synthetic data generation for this machine learning membership.
isResponsible (boolean) -- [REQUIRED]
Indicates if this membership is responsible for paying for synthetic data generation.
jobCompute (dict) --
The payment responsibilities accepted by the collaboration member for job compute costs.
isResponsible (boolean) -- [REQUIRED]
Indicates whether the collaboration member has accepted to pay for job compute costs ( TRUE) or has not accepted to pay for query and job compute costs ( FALSE).
There can be one or more members who are designated as payer candidates for queries and jobs.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query and job compute costs.
If you set the value to TRUE but you are not responsible to pay for query and job compute costs.
boolean
An indicator as to whether Amazon CloudWatch metrics have been enabled or disabled for the membership.
Amazon CloudWatch metrics are only available when the collaboration has metrics enabled. This option can be set by collaboration members who have the ability to run queries (analysis runners) or by members who are configured as payers.
When true, metrics about query execution are collected in Amazon CloudWatch. The default value is false.
dict
Response Syntax
{
'membership': {
'id': 'string',
'arn': 'string',
'collaborationArn': 'string',
'collaborationId': 'string',
'collaborationCreatorAccountId': 'string',
'collaborationCreatorDisplayName': 'string',
'collaborationName': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'status': 'ACTIVE'|'REMOVED'|'COLLABORATION_DELETED',
'memberAbilities': [
'CAN_QUERY'|'CAN_RECEIVE_RESULTS'|'CAN_RUN_JOB'|'CAN_EXPORT_QUERY_ANALYSIS_LOG',
],
'mlMemberAbilities': {
'customMLMemberAbilities': [
'CAN_RECEIVE_MODEL_OUTPUT'|'CAN_RECEIVE_INFERENCE_OUTPUT',
]
},
'queryLogStatus': 'ENABLED'|'DISABLED',
'jobLogStatus': 'ENABLED'|'DISABLED',
'defaultResultConfiguration': {
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string',
'singleFileOutput': True|False
}
},
'roleArn': 'string'
},
'defaultJobResultConfiguration': {
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string'
}
},
'roleArn': 'string'
},
'paymentConfiguration': {
'queryCompute': {
'isResponsible': True|False
},
'machineLearning': {
'modelTraining': {
'isResponsible': True|False
},
'modelInference': {
'isResponsible': True|False
},
'syntheticDataGeneration': {
'isResponsible': True|False
}
},
'jobCompute': {
'isResponsible': True|False
}
},
'isMetricsEnabled': True|False
}
}
Response Structure
(dict) --
membership (dict) --
The membership that was created.
id (string) --
The unique ID of the membership.
arn (string) --
The unique ARN for the membership.
collaborationArn (string) --
The unique ARN for the membership's associated collaboration.
collaborationId (string) --
The unique ID for the membership's collaboration.
collaborationCreatorAccountId (string) --
The identifier used to reference members of the collaboration. Currently only supports Amazon Web Services account ID.
collaborationCreatorDisplayName (string) --
The display name of the collaboration creator.
collaborationName (string) --
The name of the membership's collaboration.
createTime (datetime) --
The time when the membership was created.
updateTime (datetime) --
The time the membership metadata was last updated.
status (string) --
The status of the membership.
memberAbilities (list) --
The abilities granted to the collaboration member.
(string) --
mlMemberAbilities (dict) --
Specifies the ML member abilities that are granted to a collaboration member.
customMLMemberAbilities (list) --
The custom ML member abilities for a collaboration member.
(string) --
queryLogStatus (string) --
An indicator as to whether query logging has been enabled or disabled for the membership.
When ENABLED, Clean Rooms logs details about queries run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
jobLogStatus (string) --
An indicator as to whether job logging has been enabled or disabled for the collaboration.
When ENABLED, Clean Rooms logs details about jobs run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
defaultResultConfiguration (dict) --
The default protected query result configuration as specified by the member who can receive results.
outputConfiguration (dict) --
Configuration for protected query results.
s3 (dict) --
Contains the configuration to write the query results to S3.
resultFormat (string) --
Intended file format of the result.
bucket (string) --
The S3 bucket to unload the protected query results.
keyPrefix (string) --
The S3 prefix to unload the protected query results.
singleFileOutput (boolean) --
Indicates whether files should be output as a single file ( TRUE) or output as multiple files ( FALSE). This parameter is only supported for analyses with the Spark analytics engine.
roleArn (string) --
The unique ARN for an IAM role that is used by Clean Rooms to write protected query results to the result location, given by the member who can receive results.
defaultJobResultConfiguration (dict) --
The default job result configuration for the membership.
outputConfiguration (dict) --
The output configuration for a protected job result.
s3 (dict) --
Contains the configuration to write the job results to S3.
resultFormat (string) --
The file format of the protected job results. If you don't specify a format, results are written as CSV.
bucket (string) --
The S3 bucket for job output.
keyPrefix (string) --
The S3 prefix to unload the protected job results.
roleArn (string) --
The unique ARN for an IAM role that is used by Clean Rooms to write protected job results to the result location, given by the member who can receive results.
paymentConfiguration (dict) --
The payment responsibilities accepted by the collaboration member.
queryCompute (dict) --
The payment responsibilities accepted by the collaboration member for query compute costs.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for query compute costs ( TRUE) or has not accepted to pay for query compute costs ( FALSE).
If the collaboration creator has not specified anyone to pay for query compute costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query compute costs.
If you set the value to TRUE but you are not responsible to pay for query compute costs.
machineLearning (dict) --
The payment responsibilities accepted by the collaboration member for machine learning costs.
modelTraining (dict) --
The payment responsibilities accepted by the member for model training.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for model training costs ( TRUE) or has not accepted to pay for model training costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model training costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model training costs.
If you set the value to TRUE but you are not responsible to pay for model training costs.
modelInference (dict) --
The payment responsibilities accepted by the member for model inference.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for model inference costs ( TRUE) or has not accepted to pay for model inference costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model inference costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model inference costs.
If you set the value to TRUE but you are not responsible to pay for model inference costs.
syntheticDataGeneration (dict) --
The payment configuration for synthetic data generation for this machine learning membership.
isResponsible (boolean) --
Indicates if this membership is responsible for paying for synthetic data generation.
jobCompute (dict) --
The payment responsibilities accepted by the collaboration member for job compute costs.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for job compute costs ( TRUE) or has not accepted to pay for query and job compute costs ( FALSE).
There can be one or more members who are designated as payer candidates for queries and jobs.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query and job compute costs.
If you set the value to TRUE but you are not responsible to pay for query and job compute costs.
isMetricsEnabled (boolean) --
An indicator as to whether Amazon CloudWatch metrics are enabled for the membership.
When true, metrics about query execution are collected in Amazon CloudWatch.
{'analysisTemplate': {'format': {'PYSPARK_2_0'}}}
Retrieves an analysis template.
See also: AWS API Documentation
Request Syntax
client.get_analysis_template(
membershipIdentifier='string',
analysisTemplateIdentifier='string'
)
string
[REQUIRED]
The identifier for a membership resource.
string
[REQUIRED]
The identifier for the analysis template resource.
dict
Response Syntax
{
'analysisTemplate': {
'id': 'string',
'arn': 'string',
'collaborationId': 'string',
'collaborationArn': 'string',
'membershipId': 'string',
'membershipArn': 'string',
'description': 'string',
'name': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'schema': {
'referencedTables': [
'string',
]
},
'format': 'SQL'|'PYSPARK_1_0'|'PYSPARK_2_0',
'source': {
'text': 'string',
'artifacts': {
'entryPoint': {
'location': {
'bucket': 'string',
'key': 'string'
}
},
'additionalArtifacts': [
{
'location': {
'bucket': 'string',
'key': 'string'
}
},
],
'roleArn': 'string'
}
},
'sourceMetadata': {
'artifacts': {
'entryPointHash': {
'sha256': 'string'
},
'additionalArtifactHashes': [
{
'sha256': 'string'
},
]
}
},
'analysisParameters': [
{
'name': 'string',
'type': 'SMALLINT'|'INTEGER'|'BIGINT'|'DECIMAL'|'REAL'|'DOUBLE_PRECISION'|'BOOLEAN'|'CHAR'|'VARCHAR'|'DATE'|'TIMESTAMP'|'TIMESTAMPTZ'|'TIME'|'TIMETZ'|'VARBYTE'|'BINARY'|'BYTE'|'CHARACTER'|'DOUBLE'|'FLOAT'|'INT'|'LONG'|'NUMERIC'|'SHORT'|'STRING'|'TIMESTAMP_LTZ'|'TIMESTAMP_NTZ'|'TINYINT',
'defaultValue': 'string'
},
],
'validations': [
{
'type': 'DIFFERENTIAL_PRIVACY',
'status': 'VALID'|'INVALID'|'UNABLE_TO_VALIDATE',
'reasons': [
{
'message': 'string'
},
]
},
],
'errorMessageConfiguration': {
'type': 'DETAILED'
},
'syntheticDataParameters': {
'mlSyntheticDataParameters': {
'epsilon': 123.0,
'maxMembershipInferenceAttackScore': 123.0,
'columnClassification': {
'columnMapping': [
{
'columnName': 'string',
'columnType': 'CATEGORICAL'|'NUMERICAL',
'isPredictiveValue': True|False
},
]
}
}
}
}
}
Response Structure
(dict) --
analysisTemplate (dict) --
The analysis template.
id (string) --
The identifier for the analysis template.
arn (string) --
The Amazon Resource Name (ARN) of the analysis template.
collaborationId (string) --
The unique ID for the associated collaboration of the analysis template.
collaborationArn (string) --
The unique ARN for the analysis template’s associated collaboration.
membershipId (string) --
The identifier of a member who created the analysis template.
membershipArn (string) --
The Amazon Resource Name (ARN) of the member who created the analysis template.
description (string) --
The description of the analysis template.
name (string) --
The name of the analysis template.
createTime (datetime) --
The time that the analysis template was created.
updateTime (datetime) --
The time that the analysis template was last updated.
schema (dict) --
The entire schema object.
referencedTables (list) --
The tables referenced in the analysis schema.
(string) --
format (string) --
The format of the analysis template.
source (dict) --
The source of the analysis template.
text (string) --
The query text.
artifacts (dict) --
The artifacts of the analysis source.
entryPoint (dict) --
The entry point for the analysis template artifacts.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
additionalArtifacts (list) --
Additional artifacts for the analysis template.
(dict) --
The analysis template artifact.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
roleArn (string) --
The role ARN for the analysis template artifacts.
sourceMetadata (dict) --
The source metadata for the analysis template.
artifacts (dict) --
The artifacts of the analysis source metadata.
entryPointHash (dict) --
The hash of the entry point for the analysis template artifact metadata.
sha256 (string) --
The SHA-256 hash value.
additionalArtifactHashes (list) --
Additional artifact hashes for the analysis template.
(dict) --
Hash
sha256 (string) --
The SHA-256 hash value.
analysisParameters (list) --
The parameters of the analysis template.
(dict) --
Optional. The member who can query can provide this placeholder for a literal data value in an analysis template.
name (string) --
The name of the parameter. The name must use only alphanumeric or underscore (_) characters.
type (string) --
The type of parameter.
defaultValue (string) --
Optional. The default value that is applied in the analysis template. The member who can query can override this value in the query editor.
validations (list) --
Information about the validations performed on the analysis template.
(dict) --
The status details of the analysis template validation. Clean Rooms Differential Privacy uses a general-purpose query structure to support complex SQL queries and validates whether an analysis template fits that general-purpose query structure. Validation is performed when analysis templates are created and fetched. Because analysis templates are immutable by design, we recommend that you create analysis templates after you associate the configured tables with their analysis rule to your collaboration.
For more information, see https://docs.aws.amazon.com/clean-rooms/latest/userguide/analysis-rules-custom.html#custom-diff-privacy.
type (string) --
The type of validation that was performed.
status (string) --
The status of the validation.
reasons (list) --
The reasons for the validation results.
(dict) --
The reasons for the validation results.
message (string) --
The validation message.
errorMessageConfiguration (dict) --
The configuration that specifies the level of detail in error messages returned by analyses using this template. When set to DETAILED, error messages include more information to help troubleshoot issues with PySpark jobs. Detailed error messages may expose underlying data, including sensitive information. Recommended for faster troubleshooting in development and testing environments.
type (string) --
The level of detail for error messages returned by the PySpark job. When set to DETAILED, error messages include more information to help troubleshoot issues with your PySpark job.
Because this setting may expose sensitive data, it is recommended for development and testing environments.
syntheticDataParameters (dict) --
The parameters used to generate synthetic data for this analysis template.
mlSyntheticDataParameters (dict) --
The machine learning-specific parameters for synthetic data generation.
epsilon (float) --
The epsilon value for differential privacy when generating synthetic data. Lower values provide stronger privacy guarantees but may reduce data utility.
maxMembershipInferenceAttackScore (float) --
The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
columnClassification (dict) --
Classification details for data columns that specify how each column should be treated during synthetic data generation.
columnMapping (list) --
A mapping that defines the classification of data columns for synthetic data generation and specifies how each column should be handled during the privacy-preserving data synthesis process.
(dict) --
Properties that define how a specific data column should be handled during synthetic data generation, including its name, type, and role in predictive modeling.
columnName (string) --
The name of the data column as it appears in the dataset.
columnType (string) --
The data type of the column, which determines how the synthetic data generation algorithm processes and synthesizes values for this column.
isPredictiveValue (boolean) --
Indicates if this column contains predictive values that should be treated as target variables in machine learning models. This affects how the synthetic data generation preserves statistical relationships.
{'collaborationAnalysisTemplate': {'format': {'PYSPARK_2_0'}}}
Retrieves an analysis template within a collaboration.
See also: AWS API Documentation
Request Syntax
client.get_collaboration_analysis_template(
collaborationIdentifier='string',
analysisTemplateArn='string'
)
string
[REQUIRED]
A unique identifier for the collaboration that the analysis templates belong to. Currently accepts collaboration ID.
string
[REQUIRED]
The Amazon Resource Name (ARN) associated with the analysis template within a collaboration.
dict
Response Syntax
{
'collaborationAnalysisTemplate': {
'id': 'string',
'arn': 'string',
'collaborationId': 'string',
'collaborationArn': 'string',
'description': 'string',
'creatorAccountId': 'string',
'name': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'schema': {
'referencedTables': [
'string',
]
},
'format': 'SQL'|'PYSPARK_1_0'|'PYSPARK_2_0',
'source': {
'text': 'string',
'artifacts': {
'entryPoint': {
'location': {
'bucket': 'string',
'key': 'string'
}
},
'additionalArtifacts': [
{
'location': {
'bucket': 'string',
'key': 'string'
}
},
],
'roleArn': 'string'
}
},
'sourceMetadata': {
'artifacts': {
'entryPointHash': {
'sha256': 'string'
},
'additionalArtifactHashes': [
{
'sha256': 'string'
},
]
}
},
'analysisParameters': [
{
'name': 'string',
'type': 'SMALLINT'|'INTEGER'|'BIGINT'|'DECIMAL'|'REAL'|'DOUBLE_PRECISION'|'BOOLEAN'|'CHAR'|'VARCHAR'|'DATE'|'TIMESTAMP'|'TIMESTAMPTZ'|'TIME'|'TIMETZ'|'VARBYTE'|'BINARY'|'BYTE'|'CHARACTER'|'DOUBLE'|'FLOAT'|'INT'|'LONG'|'NUMERIC'|'SHORT'|'STRING'|'TIMESTAMP_LTZ'|'TIMESTAMP_NTZ'|'TINYINT',
'defaultValue': 'string'
},
],
'validations': [
{
'type': 'DIFFERENTIAL_PRIVACY',
'status': 'VALID'|'INVALID'|'UNABLE_TO_VALIDATE',
'reasons': [
{
'message': 'string'
},
]
},
],
'errorMessageConfiguration': {
'type': 'DETAILED'
},
'syntheticDataParameters': {
'mlSyntheticDataParameters': {
'epsilon': 123.0,
'maxMembershipInferenceAttackScore': 123.0,
'columnClassification': {
'columnMapping': [
{
'columnName': 'string',
'columnType': 'CATEGORICAL'|'NUMERICAL',
'isPredictiveValue': True|False
},
]
}
}
}
}
}
Response Structure
(dict) --
collaborationAnalysisTemplate (dict) --
The analysis template within a collaboration.
id (string) --
The identifier of the analysis template.
arn (string) --
The Amazon Resource Name (ARN) of the analysis template.
collaborationId (string) --
A unique identifier for the collaboration that the analysis templates belong to. Currently accepts collaboration ID.
collaborationArn (string) --
The unique ARN for the analysis template’s associated collaboration.
description (string) --
The description of the analysis template.
creatorAccountId (string) --
The identifier used to reference members of the collaboration. Currently only supports Amazon Web Services account ID.
name (string) --
The name of the analysis template.
createTime (datetime) --
The time that the analysis template within a collaboration was created.
updateTime (datetime) --
The time that the analysis template in the collaboration was last updated.
schema (dict) --
The entire schema object.
referencedTables (list) --
The tables referenced in the analysis schema.
(string) --
format (string) --
The format of the analysis template in the collaboration.
source (dict) --
The source of the analysis template within a collaboration.
text (string) --
The query text.
artifacts (dict) --
The artifacts of the analysis source.
entryPoint (dict) --
The entry point for the analysis template artifacts.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
additionalArtifacts (list) --
Additional artifacts for the analysis template.
(dict) --
The analysis template artifact.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
roleArn (string) --
The role ARN for the analysis template artifacts.
sourceMetadata (dict) --
The source metadata for the collaboration analysis template.
artifacts (dict) --
The artifacts of the analysis source metadata.
entryPointHash (dict) --
The hash of the entry point for the analysis template artifact metadata.
sha256 (string) --
The SHA-256 hash value.
additionalArtifactHashes (list) --
Additional artifact hashes for the analysis template.
(dict) --
Hash
sha256 (string) --
The SHA-256 hash value.
analysisParameters (list) --
The analysis parameters that have been specified in the analysis template.
(dict) --
Optional. The member who can query can provide this placeholder for a literal data value in an analysis template.
name (string) --
The name of the parameter. The name must use only alphanumeric or underscore (_) characters.
type (string) --
The type of parameter.
defaultValue (string) --
Optional. The default value that is applied in the analysis template. The member who can query can override this value in the query editor.
validations (list) --
The validations that were performed.
(dict) --
The status details of the analysis template validation. Clean Rooms Differential Privacy uses a general-purpose query structure to support complex SQL queries and validates whether an analysis template fits that general-purpose query structure. Validation is performed when analysis templates are created and fetched. Because analysis templates are immutable by design, we recommend that you create analysis templates after you associate the configured tables with their analysis rule to your collaboration.
For more information, see https://docs.aws.amazon.com/clean-rooms/latest/userguide/analysis-rules-custom.html#custom-diff-privacy.
type (string) --
The type of validation that was performed.
status (string) --
The status of the validation.
reasons (list) --
The reasons for the validation results.
(dict) --
The reasons for the validation results.
message (string) --
The validation message.
errorMessageConfiguration (dict) --
The configuration that specifies the level of detail in error messages returned by analyses using this template. When set to DETAILED, error messages include more information to help troubleshoot issues with PySpark jobs. Detailed error messages may expose underlying data, including sensitive information. Recommended for faster troubleshooting in development and testing environments.
type (string) --
The level of detail for error messages returned by the PySpark job. When set to DETAILED, error messages include more information to help troubleshoot issues with your PySpark job.
Because this setting may expose sensitive data, it is recommended for development and testing environments.
syntheticDataParameters (dict) --
The synthetic data generation parameters configured for this collaboration analysis template.
mlSyntheticDataParameters (dict) --
The machine learning-specific parameters for synthetic data generation.
epsilon (float) --
The epsilon value for differential privacy when generating synthetic data. Lower values provide stronger privacy guarantees but may reduce data utility.
maxMembershipInferenceAttackScore (float) --
The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
columnClassification (dict) --
Classification details for data columns that specify how each column should be treated during synthetic data generation.
columnMapping (list) --
A mapping that defines the classification of data columns for synthetic data generation and specifies how each column should be handled during the privacy-preserving data synthesis process.
(dict) --
Properties that define how a specific data column should be handled during synthetic data generation, including its name, type, and role in predictive modeling.
columnName (string) --
The name of the data column as it appears in the dataset.
columnType (string) --
The data type of the column, which determines how the synthetic data generation algorithm processes and synthesizes values for this column.
isPredictiveValue (boolean) --
Indicates if this column contains predictive values that should be treated as target variables in machine learning models. This affects how the synthetic data generation preserves statistical relationships.
{'membership': {'defaultJobResultConfiguration': {'outputConfiguration': {'s3': {'resultFormat': 'CSV '
'| '
'PARQUET'}}}}}
Retrieves a specified membership for an identifier.
See also: AWS API Documentation
Request Syntax
client.get_membership(
membershipIdentifier='string'
)
string
[REQUIRED]
The identifier for a membership resource.
dict
Response Syntax
{
'membership': {
'id': 'string',
'arn': 'string',
'collaborationArn': 'string',
'collaborationId': 'string',
'collaborationCreatorAccountId': 'string',
'collaborationCreatorDisplayName': 'string',
'collaborationName': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'status': 'ACTIVE'|'REMOVED'|'COLLABORATION_DELETED',
'memberAbilities': [
'CAN_QUERY'|'CAN_RECEIVE_RESULTS'|'CAN_RUN_JOB'|'CAN_EXPORT_QUERY_ANALYSIS_LOG',
],
'mlMemberAbilities': {
'customMLMemberAbilities': [
'CAN_RECEIVE_MODEL_OUTPUT'|'CAN_RECEIVE_INFERENCE_OUTPUT',
]
},
'queryLogStatus': 'ENABLED'|'DISABLED',
'jobLogStatus': 'ENABLED'|'DISABLED',
'defaultResultConfiguration': {
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string',
'singleFileOutput': True|False
}
},
'roleArn': 'string'
},
'defaultJobResultConfiguration': {
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string'
}
},
'roleArn': 'string'
},
'paymentConfiguration': {
'queryCompute': {
'isResponsible': True|False
},
'machineLearning': {
'modelTraining': {
'isResponsible': True|False
},
'modelInference': {
'isResponsible': True|False
},
'syntheticDataGeneration': {
'isResponsible': True|False
}
},
'jobCompute': {
'isResponsible': True|False
}
},
'isMetricsEnabled': True|False
}
}
Response Structure
(dict) --
membership (dict) --
The membership retrieved for the provided identifier.
id (string) --
The unique ID of the membership.
arn (string) --
The unique ARN for the membership.
collaborationArn (string) --
The unique ARN for the membership's associated collaboration.
collaborationId (string) --
The unique ID for the membership's collaboration.
collaborationCreatorAccountId (string) --
The identifier used to reference members of the collaboration. Currently only supports Amazon Web Services account ID.
collaborationCreatorDisplayName (string) --
The display name of the collaboration creator.
collaborationName (string) --
The name of the membership's collaboration.
createTime (datetime) --
The time when the membership was created.
updateTime (datetime) --
The time the membership metadata was last updated.
status (string) --
The status of the membership.
memberAbilities (list) --
The abilities granted to the collaboration member.
(string) --
mlMemberAbilities (dict) --
Specifies the ML member abilities that are granted to a collaboration member.
customMLMemberAbilities (list) --
The custom ML member abilities for a collaboration member.
(string) --
queryLogStatus (string) --
An indicator as to whether query logging has been enabled or disabled for the membership.
When ENABLED, Clean Rooms logs details about queries run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
jobLogStatus (string) --
An indicator as to whether job logging has been enabled or disabled for the collaboration.
When ENABLED, Clean Rooms logs details about jobs run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
defaultResultConfiguration (dict) --
The default protected query result configuration as specified by the member who can receive results.
outputConfiguration (dict) --
Configuration for protected query results.
s3 (dict) --
Contains the configuration to write the query results to S3.
resultFormat (string) --
Intended file format of the result.
bucket (string) --
The S3 bucket to unload the protected query results.
keyPrefix (string) --
The S3 prefix to unload the protected query results.
singleFileOutput (boolean) --
Indicates whether files should be output as a single file ( TRUE) or output as multiple files ( FALSE). This parameter is only supported for analyses with the Spark analytics engine.
roleArn (string) --
The unique ARN for an IAM role that is used by Clean Rooms to write protected query results to the result location, given by the member who can receive results.
defaultJobResultConfiguration (dict) --
The default job result configuration for the membership.
outputConfiguration (dict) --
The output configuration for a protected job result.
s3 (dict) --
Contains the configuration to write the job results to S3.
resultFormat (string) --
The file format of the protected job results. If you don't specify a format, results are written as CSV.
bucket (string) --
The S3 bucket for job output.
keyPrefix (string) --
The S3 prefix to unload the protected job results.
roleArn (string) --
The unique ARN for an IAM role that is used by Clean Rooms to write protected job results to the result location, given by the member who can receive results.
paymentConfiguration (dict) --
The payment responsibilities accepted by the collaboration member.
queryCompute (dict) --
The payment responsibilities accepted by the collaboration member for query compute costs.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for query compute costs ( TRUE) or has not accepted to pay for query compute costs ( FALSE).
If the collaboration creator has not specified anyone to pay for query compute costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query compute costs.
If you set the value to TRUE but you are not responsible to pay for query compute costs.
machineLearning (dict) --
The payment responsibilities accepted by the collaboration member for machine learning costs.
modelTraining (dict) --
The payment responsibilities accepted by the member for model training.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for model training costs ( TRUE) or has not accepted to pay for model training costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model training costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model training costs.
If you set the value to TRUE but you are not responsible to pay for model training costs.
modelInference (dict) --
The payment responsibilities accepted by the member for model inference.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for model inference costs ( TRUE) or has not accepted to pay for model inference costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model inference costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model inference costs.
If you set the value to TRUE but you are not responsible to pay for model inference costs.
syntheticDataGeneration (dict) --
The payment configuration for synthetic data generation for this machine learning membership.
isResponsible (boolean) --
Indicates if this membership is responsible for paying for synthetic data generation.
jobCompute (dict) --
The payment responsibilities accepted by the collaboration member for job compute costs.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for job compute costs ( TRUE) or has not accepted to pay for query and job compute costs ( FALSE).
There can be one or more members who are designated as payer candidates for queries and jobs.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query and job compute costs.
If you set the value to TRUE but you are not responsible to pay for query and job compute costs.
isMetricsEnabled (boolean) --
An indicator as to whether Amazon CloudWatch metrics are enabled for the membership.
When true, metrics about query execution are collected in Amazon CloudWatch.
{'analysisTemplate': {'format': {'PYSPARK_2_0'}}}
Updates the analysis template metadata.
See also: AWS API Documentation
Request Syntax
client.update_analysis_template(
membershipIdentifier='string',
analysisTemplateIdentifier='string',
description='string'
)
string
[REQUIRED]
The identifier for a membership resource.
string
[REQUIRED]
The identifier for the analysis template resource.
string
A new description for the analysis template.
dict
Response Syntax
{
'analysisTemplate': {
'id': 'string',
'arn': 'string',
'collaborationId': 'string',
'collaborationArn': 'string',
'membershipId': 'string',
'membershipArn': 'string',
'description': 'string',
'name': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'schema': {
'referencedTables': [
'string',
]
},
'format': 'SQL'|'PYSPARK_1_0'|'PYSPARK_2_0',
'source': {
'text': 'string',
'artifacts': {
'entryPoint': {
'location': {
'bucket': 'string',
'key': 'string'
}
},
'additionalArtifacts': [
{
'location': {
'bucket': 'string',
'key': 'string'
}
},
],
'roleArn': 'string'
}
},
'sourceMetadata': {
'artifacts': {
'entryPointHash': {
'sha256': 'string'
},
'additionalArtifactHashes': [
{
'sha256': 'string'
},
]
}
},
'analysisParameters': [
{
'name': 'string',
'type': 'SMALLINT'|'INTEGER'|'BIGINT'|'DECIMAL'|'REAL'|'DOUBLE_PRECISION'|'BOOLEAN'|'CHAR'|'VARCHAR'|'DATE'|'TIMESTAMP'|'TIMESTAMPTZ'|'TIME'|'TIMETZ'|'VARBYTE'|'BINARY'|'BYTE'|'CHARACTER'|'DOUBLE'|'FLOAT'|'INT'|'LONG'|'NUMERIC'|'SHORT'|'STRING'|'TIMESTAMP_LTZ'|'TIMESTAMP_NTZ'|'TINYINT',
'defaultValue': 'string'
},
],
'validations': [
{
'type': 'DIFFERENTIAL_PRIVACY',
'status': 'VALID'|'INVALID'|'UNABLE_TO_VALIDATE',
'reasons': [
{
'message': 'string'
},
]
},
],
'errorMessageConfiguration': {
'type': 'DETAILED'
},
'syntheticDataParameters': {
'mlSyntheticDataParameters': {
'epsilon': 123.0,
'maxMembershipInferenceAttackScore': 123.0,
'columnClassification': {
'columnMapping': [
{
'columnName': 'string',
'columnType': 'CATEGORICAL'|'NUMERICAL',
'isPredictiveValue': True|False
},
]
}
}
}
}
}
Response Structure
(dict) --
analysisTemplate (dict) --
The analysis template.
id (string) --
The identifier for the analysis template.
arn (string) --
The Amazon Resource Name (ARN) of the analysis template.
collaborationId (string) --
The unique ID for the associated collaboration of the analysis template.
collaborationArn (string) --
The unique ARN for the analysis template’s associated collaboration.
membershipId (string) --
The identifier of a member who created the analysis template.
membershipArn (string) --
The Amazon Resource Name (ARN) of the member who created the analysis template.
description (string) --
The description of the analysis template.
name (string) --
The name of the analysis template.
createTime (datetime) --
The time that the analysis template was created.
updateTime (datetime) --
The time that the analysis template was last updated.
schema (dict) --
The entire schema object.
referencedTables (list) --
The tables referenced in the analysis schema.
(string) --
format (string) --
The format of the analysis template.
source (dict) --
The source of the analysis template.
text (string) --
The query text.
artifacts (dict) --
The artifacts of the analysis source.
entryPoint (dict) --
The entry point for the analysis template artifacts.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
additionalArtifacts (list) --
Additional artifacts for the analysis template.
(dict) --
The analysis template artifact.
location (dict) --
The artifact location.
bucket (string) --
The bucket name.
key (string) --
The object key.
roleArn (string) --
The role ARN for the analysis template artifacts.
sourceMetadata (dict) --
The source metadata for the analysis template.
artifacts (dict) --
The artifacts of the analysis source metadata.
entryPointHash (dict) --
The hash of the entry point for the analysis template artifact metadata.
sha256 (string) --
The SHA-256 hash value.
additionalArtifactHashes (list) --
Additional artifact hashes for the analysis template.
(dict) --
Hash
sha256 (string) --
The SHA-256 hash value.
analysisParameters (list) --
The parameters of the analysis template.
(dict) --
Optional. The member who can query can provide this placeholder for a literal data value in an analysis template.
name (string) --
The name of the parameter. The name must use only alphanumeric or underscore (_) characters.
type (string) --
The type of parameter.
defaultValue (string) --
Optional. The default value that is applied in the analysis template. The member who can query can override this value in the query editor.
validations (list) --
Information about the validations performed on the analysis template.
(dict) --
The status details of the analysis template validation. Clean Rooms Differential Privacy uses a general-purpose query structure to support complex SQL queries and validates whether an analysis template fits that general-purpose query structure. Validation is performed when analysis templates are created and fetched. Because analysis templates are immutable by design, we recommend that you create analysis templates after you associate the configured tables with their analysis rule to your collaboration.
For more information, see https://docs.aws.amazon.com/clean-rooms/latest/userguide/analysis-rules-custom.html#custom-diff-privacy.
type (string) --
The type of validation that was performed.
status (string) --
The status of the validation.
reasons (list) --
The reasons for the validation results.
(dict) --
The reasons for the validation results.
message (string) --
The validation message.
errorMessageConfiguration (dict) --
The configuration that specifies the level of detail in error messages returned by analyses using this template. When set to DETAILED, error messages include more information to help troubleshoot issues with PySpark jobs. Detailed error messages may expose underlying data, including sensitive information. Recommended for faster troubleshooting in development and testing environments.
type (string) --
The level of detail for error messages returned by the PySpark job. When set to DETAILED, error messages include more information to help troubleshoot issues with your PySpark job.
Because this setting may expose sensitive data, it is recommended for development and testing environments.
syntheticDataParameters (dict) --
The parameters used to generate synthetic data for this analysis template.
mlSyntheticDataParameters (dict) --
The machine learning-specific parameters for synthetic data generation.
epsilon (float) --
The epsilon value for differential privacy when generating synthetic data. Lower values provide stronger privacy guarantees but may reduce data utility.
maxMembershipInferenceAttackScore (float) --
The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
columnClassification (dict) --
Classification details for data columns that specify how each column should be treated during synthetic data generation.
columnMapping (list) --
A mapping that defines the classification of data columns for synthetic data generation and specifies how each column should be handled during the privacy-preserving data synthesis process.
(dict) --
Properties that define how a specific data column should be handled during synthetic data generation, including its name, type, and role in predictive modeling.
columnName (string) --
The name of the data column as it appears in the dataset.
columnType (string) --
The data type of the column, which determines how the synthetic data generation algorithm processes and synthesizes values for this column.
isPredictiveValue (boolean) --
Indicates if this column contains predictive values that should be treated as target variables in machine learning models. This affects how the synthetic data generation preserves statistical relationships.
{'defaultJobResultConfiguration': {'outputConfiguration': {'s3': {'resultFormat': 'CSV '
'| '
'PARQUET'}}}}
Response {'membership': {'defaultJobResultConfiguration': {'outputConfiguration': {'s3': {'resultFormat': 'CSV '
'| '
'PARQUET'}}}}}
Updates a membership.
See also: AWS API Documentation
Request Syntax
client.update_membership(
membershipIdentifier='string',
queryLogStatus='ENABLED'|'DISABLED',
jobLogStatus='ENABLED'|'DISABLED',
defaultResultConfiguration={
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string',
'singleFileOutput': True|False
}
},
'roleArn': 'string'
},
defaultJobResultConfiguration={
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string'
}
},
'roleArn': 'string'
},
membershipPaymentConfiguration={
'queryCompute': {
'isResponsible': True|False
},
'machineLearning': {
'modelTraining': {
'isResponsible': True|False
},
'modelInference': {
'isResponsible': True|False
},
'syntheticDataGeneration': {
'isResponsible': True|False
}
},
'jobCompute': {
'isResponsible': True|False
}
}
)
string
[REQUIRED]
The unique identifier of the membership.
string
An indicator as to whether query logging has been enabled or disabled for the membership.
When ENABLED, Clean Rooms logs details about queries run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
string
An indicator as to whether job logging has been enabled or disabled for the collaboration.
When ENABLED, Clean Rooms logs details about jobs run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
dict
The default protected query result configuration as specified by the member who can receive results.
outputConfiguration (dict) -- [REQUIRED]
Configuration for protected query results.
s3 (dict) --
Contains the configuration to write the query results to S3.
resultFormat (string) -- [REQUIRED]
Intended file format of the result.
bucket (string) -- [REQUIRED]
The S3 bucket to unload the protected query results.
keyPrefix (string) --
The S3 prefix to unload the protected query results.
singleFileOutput (boolean) --
Indicates whether files should be output as a single file ( TRUE) or output as multiple files ( FALSE). This parameter is only supported for analyses with the Spark analytics engine.
roleArn (string) --
The unique ARN for an IAM role that is used by Clean Rooms to write protected query results to the result location, given by the member who can receive results.
dict
The default job result configuration.
outputConfiguration (dict) -- [REQUIRED]
The output configuration for a protected job result.
s3 (dict) --
Contains the configuration to write the job results to S3.
resultFormat (string) --
The file format of the protected job results. If you don't specify a format, results are written as CSV.
bucket (string) -- [REQUIRED]
The S3 bucket for job output.
keyPrefix (string) --
The S3 prefix to unload the protected job results.
roleArn (string) -- [REQUIRED]
The unique ARN for an IAM role that is used by Clean Rooms to write protected job results to the result location, given by the member who can receive results.
dict
The payment configuration to update for the membership.
queryCompute (dict) --
An object representing the payment responsibilities accepted by the collaboration member for query compute costs.
isResponsible (boolean) -- [REQUIRED]
Indicates whether the collaboration member has accepted to pay for query compute costs ( TRUE) or has not accepted to pay for query compute costs ( FALSE).
If the collaboration creator has not specified anyone to pay for query compute costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query compute costs.
If you set the value to TRUE but you are not responsible to pay for query compute costs.
machineLearning (dict) --
An object representing the collaboration member's machine learning payment responsibilities set by the collaboration creator.
modelTraining (dict) --
The payment responsibilities accepted by the member for model training.
isResponsible (boolean) -- [REQUIRED]
Indicates whether the collaboration member has accepted to pay for model training costs ( TRUE) or has not accepted to pay for model training costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model training costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model training costs.
If you set the value to TRUE but you are not responsible to pay for model training costs.
modelInference (dict) --
The payment responsibilities accepted by the member for model inference.
isResponsible (boolean) -- [REQUIRED]
Indicates whether the collaboration member has accepted to pay for model inference costs ( TRUE) or has not accepted to pay for model inference costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model inference costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model inference costs.
If you set the value to TRUE but you are not responsible to pay for model inference costs.
syntheticDataGeneration (dict) --
The payment configuration for synthetic data generation for this machine learning membership.
isResponsible (boolean) -- [REQUIRED]
Indicates if this membership is responsible for paying for synthetic data generation.
jobCompute (dict) --
An object representing the payment responsibilities accepted by the collaboration member for query and job compute costs.
isResponsible (boolean) -- [REQUIRED]
Indicates whether the collaboration member has accepted to pay for job compute costs ( TRUE) or has not accepted to pay for query and job compute costs ( FALSE).
There can be one or more members who are designated as payer candidates for queries and jobs.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query and job compute costs.
If you set the value to TRUE but you are not responsible to pay for query and job compute costs.
dict
Response Syntax
{
'membership': {
'id': 'string',
'arn': 'string',
'collaborationArn': 'string',
'collaborationId': 'string',
'collaborationCreatorAccountId': 'string',
'collaborationCreatorDisplayName': 'string',
'collaborationName': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'status': 'ACTIVE'|'REMOVED'|'COLLABORATION_DELETED',
'memberAbilities': [
'CAN_QUERY'|'CAN_RECEIVE_RESULTS'|'CAN_RUN_JOB'|'CAN_EXPORT_QUERY_ANALYSIS_LOG',
],
'mlMemberAbilities': {
'customMLMemberAbilities': [
'CAN_RECEIVE_MODEL_OUTPUT'|'CAN_RECEIVE_INFERENCE_OUTPUT',
]
},
'queryLogStatus': 'ENABLED'|'DISABLED',
'jobLogStatus': 'ENABLED'|'DISABLED',
'defaultResultConfiguration': {
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string',
'singleFileOutput': True|False
}
},
'roleArn': 'string'
},
'defaultJobResultConfiguration': {
'outputConfiguration': {
's3': {
'resultFormat': 'CSV'|'PARQUET',
'bucket': 'string',
'keyPrefix': 'string'
}
},
'roleArn': 'string'
},
'paymentConfiguration': {
'queryCompute': {
'isResponsible': True|False
},
'machineLearning': {
'modelTraining': {
'isResponsible': True|False
},
'modelInference': {
'isResponsible': True|False
},
'syntheticDataGeneration': {
'isResponsible': True|False
}
},
'jobCompute': {
'isResponsible': True|False
}
},
'isMetricsEnabled': True|False
}
}
Response Structure
(dict) --
membership (dict) --
The membership object.
id (string) --
The unique ID of the membership.
arn (string) --
The unique ARN for the membership.
collaborationArn (string) --
The unique ARN for the membership's associated collaboration.
collaborationId (string) --
The unique ID for the membership's collaboration.
collaborationCreatorAccountId (string) --
The identifier used to reference members of the collaboration. Currently only supports Amazon Web Services account ID.
collaborationCreatorDisplayName (string) --
The display name of the collaboration creator.
collaborationName (string) --
The name of the membership's collaboration.
createTime (datetime) --
The time when the membership was created.
updateTime (datetime) --
The time the membership metadata was last updated.
status (string) --
The status of the membership.
memberAbilities (list) --
The abilities granted to the collaboration member.
(string) --
mlMemberAbilities (dict) --
Specifies the ML member abilities that are granted to a collaboration member.
customMLMemberAbilities (list) --
The custom ML member abilities for a collaboration member.
(string) --
queryLogStatus (string) --
An indicator as to whether query logging has been enabled or disabled for the membership.
When ENABLED, Clean Rooms logs details about queries run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
jobLogStatus (string) --
An indicator as to whether job logging has been enabled or disabled for the collaboration.
When ENABLED, Clean Rooms logs details about jobs run within this collaboration and those logs can be viewed in Amazon CloudWatch Logs. The default value is DISABLED.
defaultResultConfiguration (dict) --
The default protected query result configuration as specified by the member who can receive results.
outputConfiguration (dict) --
Configuration for protected query results.
s3 (dict) --
Contains the configuration to write the query results to S3.
resultFormat (string) --
Intended file format of the result.
bucket (string) --
The S3 bucket to unload the protected query results.
keyPrefix (string) --
The S3 prefix to unload the protected query results.
singleFileOutput (boolean) --
Indicates whether files should be output as a single file ( TRUE) or output as multiple files ( FALSE). This parameter is only supported for analyses with the Spark analytics engine.
roleArn (string) --
The unique ARN for an IAM role that is used by Clean Rooms to write protected query results to the result location, given by the member who can receive results.
defaultJobResultConfiguration (dict) --
The default job result configuration for the membership.
outputConfiguration (dict) --
The output configuration for a protected job result.
s3 (dict) --
Contains the configuration to write the job results to S3.
resultFormat (string) --
The file format of the protected job results. If you don't specify a format, results are written as CSV.
bucket (string) --
The S3 bucket for job output.
keyPrefix (string) --
The S3 prefix to unload the protected job results.
roleArn (string) --
The unique ARN for an IAM role that is used by Clean Rooms to write protected job results to the result location, given by the member who can receive results.
paymentConfiguration (dict) --
The payment responsibilities accepted by the collaboration member.
queryCompute (dict) --
The payment responsibilities accepted by the collaboration member for query compute costs.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for query compute costs ( TRUE) or has not accepted to pay for query compute costs ( FALSE).
If the collaboration creator has not specified anyone to pay for query compute costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query compute costs.
If you set the value to TRUE but you are not responsible to pay for query compute costs.
machineLearning (dict) --
The payment responsibilities accepted by the collaboration member for machine learning costs.
modelTraining (dict) --
The payment responsibilities accepted by the member for model training.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for model training costs ( TRUE) or has not accepted to pay for model training costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model training costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model training costs.
If you set the value to TRUE but you are not responsible to pay for model training costs.
modelInference (dict) --
The payment responsibilities accepted by the member for model inference.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for model inference costs ( TRUE) or has not accepted to pay for model inference costs ( FALSE).
If the collaboration creator has not specified anyone to pay for model inference costs, then the member who can query is the default payer.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for model inference costs.
If you set the value to TRUE but you are not responsible to pay for model inference costs.
syntheticDataGeneration (dict) --
The payment configuration for synthetic data generation for this machine learning membership.
isResponsible (boolean) --
Indicates if this membership is responsible for paying for synthetic data generation.
jobCompute (dict) --
The payment responsibilities accepted by the collaboration member for job compute costs.
isResponsible (boolean) --
Indicates whether the collaboration member has accepted to pay for job compute costs ( TRUE) or has not accepted to pay for query and job compute costs ( FALSE).
There can be one or more members who are designated as payer candidates for queries and jobs.
An error message is returned for the following reasons:
If you set the value to FALSE but you are responsible to pay for query and job compute costs.
If you set the value to TRUE but you are not responsible to pay for query and job compute costs.
isMetricsEnabled (boolean) --
An indicator as to whether Amazon CloudWatch metrics are enabled for the membership.
When true, metrics about query execution are collected in Amazon CloudWatch.