2025/11/06 - Amazon QuickSight - 5 updated api methods
Changes Support for New Data Prep Experience
{'DataPrepConfiguration': {'DestinationTableMap': {'string': {'Alias': 'string',
'Source': {'TransformOperationId': 'string'}}},
'SourceTableMap': {'string': {'DataSet': {'DataSetArn': 'string',
'InputColumns': [{'Id': 'string',
'Name': 'string',
'SubType': 'FLOAT '
'| '
'FIXED',
'Type': 'STRING '
'| '
'INTEGER '
'| '
'DECIMAL '
'| '
'DATETIME '
'| '
'BIT '
'| '
'BOOLEAN '
'| '
'JSON'}]},
'PhysicalTableId': 'string'}},
'TransformStepMap': {'string': {'AggregateStep': {'Aggregations': [{'AggregationFunction': {'ListAggregation': {'Distinct': 'boolean',
'InputColumnName': 'string',
'Separator': 'string'},
'SimpleAggregation': {'FunctionType': 'COUNT '
'| '
'DISTINCT_COUNT '
'| '
'SUM '
'| '
'AVERAGE '
'| '
'MAX '
'| '
'MIN',
'InputColumnName': 'string'}},
'NewColumnId': 'string',
'NewColumnName': 'string'}],
'Alias': 'string',
'GroupByColumnNames': ['string'],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'AppendStep': {'Alias': 'string',
'AppendedColumns': [{'ColumnName': 'string',
'NewColumnId': 'string'}],
'FirstSource': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'SecondSource': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'CastColumnTypesStep': {'Alias': 'string',
'CastColumnTypeOperations': [{'ColumnName': 'string',
'Format': 'string',
'NewColumnType': 'STRING '
'| '
'INTEGER '
'| '
'DECIMAL '
'| '
'DATETIME',
'SubType': 'FLOAT '
'| '
'FIXED'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'CreateColumnsStep': {'Alias': 'string',
'Columns': [{'ColumnId': 'string',
'ColumnName': 'string',
'Expression': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'FiltersStep': {'Alias': 'string',
'FilterOperations': [{'ConditionExpression': 'string',
'DateFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'BEFORE '
'| '
'BEFORE_OR_EQUALS_TO '
'| '
'AFTER '
'| '
'AFTER_OR_EQUALS_TO',
'Value': {'StaticValue': 'timestamp'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'timestamp'},
'RangeMinimum': {'StaticValue': 'timestamp'}}},
'NumericFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'GREATER_THAN '
'| '
'GREATER_THAN_OR_EQUALS_TO '
'| '
'LESS_THAN '
'| '
'LESS_THAN_OR_EQUALS_TO',
'Value': {'StaticValue': 'double'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'double'},
'RangeMinimum': {'StaticValue': 'double'}}},
'StringFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'CONTAINS '
'| '
'DOES_NOT_CONTAIN '
'| '
'STARTS_WITH '
'| '
'ENDS_WITH',
'Value': {'StaticValue': 'string'}},
'ListFilterCondition': {'Operator': 'INCLUDE '
'| '
'EXCLUDE',
'Values': {'StaticValues': ['string']}}}}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'ImportTableStep': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'SourceTableId': 'string'}},
'JoinStep': {'Alias': 'string',
'LeftOperand': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'LeftOperandProperties': {'OutputColumnNameOverrides': [{'OutputColumnName': 'string',
'SourceColumnName': 'string'}]},
'OnClause': 'string',
'RightOperand': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'RightOperandProperties': {'OutputColumnNameOverrides': [{'OutputColumnName': 'string',
'SourceColumnName': 'string'}]},
'Type': 'INNER '
'| '
'OUTER '
'| '
'LEFT '
'| '
'RIGHT'},
'PivotStep': {'Alias': 'string',
'GroupByColumnNames': ['string'],
'PivotConfiguration': {'LabelColumnName': 'string',
'PivotedLabels': [{'LabelName': 'string',
'NewColumnId': 'string',
'NewColumnName': 'string'}]},
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'ValueColumnConfiguration': {'AggregationFunction': {'ListAggregation': {'Distinct': 'boolean',
'InputColumnName': 'string',
'Separator': 'string'},
'SimpleAggregation': {'FunctionType': 'COUNT '
'| '
'DISTINCT_COUNT '
'| '
'SUM '
'| '
'AVERAGE '
'| '
'MAX '
'| '
'MIN',
'InputColumnName': 'string'}}}},
'ProjectStep': {'Alias': 'string',
'ProjectedColumns': ['string'],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'RenameColumnsStep': {'Alias': 'string',
'RenameColumnOperations': [{'ColumnName': 'string',
'NewColumnName': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'UnpivotStep': {'Alias': 'string',
'ColumnsToUnpivot': [{'ColumnName': 'string',
'NewValue': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'UnpivotedLabelColumnId': 'string',
'UnpivotedLabelColumnName': 'string',
'UnpivotedValueColumnId': 'string',
'UnpivotedValueColumnName': 'string'}}}},
'LogicalTableMap': {'DataTransforms': {'CreateColumnsOperation': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'FilterOperation': {'DateFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'BEFORE '
'| '
'BEFORE_OR_EQUALS_TO '
'| '
'AFTER '
'| '
'AFTER_OR_EQUALS_TO',
'Value': {'StaticValue': 'timestamp'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'timestamp'},
'RangeMinimum': {'StaticValue': 'timestamp'}}},
'NumericFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'GREATER_THAN '
'| '
'GREATER_THAN_OR_EQUALS_TO '
'| '
'LESS_THAN '
'| '
'LESS_THAN_OR_EQUALS_TO',
'Value': {'StaticValue': 'double'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'double'},
'RangeMinimum': {'StaticValue': 'double'}}},
'StringFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'CONTAINS '
'| '
'DOES_NOT_CONTAIN '
'| '
'STARTS_WITH '
'| '
'ENDS_WITH',
'Value': {'StaticValue': 'string'}},
'ListFilterCondition': {'Operator': 'INCLUDE '
'| '
'EXCLUDE',
'Values': {'StaticValues': ['string']}}}},
'ProjectOperation': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}}}},
'PhysicalTableMap': {'CustomSql': {'Columns': {'Id': 'string'}},
'RelationalTable': {'InputColumns': {'Id': 'string'}},
'S3Source': {'InputColumns': {'Id': 'string'},
'UploadSettings': {'CustomCellAddressRange': 'string'}},
'SaaSTable': {'DataSourceArn': 'string',
'InputColumns': [{'Id': 'string',
'Name': 'string',
'SubType': 'FLOAT | '
'FIXED',
'Type': 'STRING | '
'INTEGER | '
'DECIMAL | '
'DATETIME | BIT '
'| BOOLEAN | '
'JSON'}],
'TablePath': [{'Id': 'string',
'Name': 'string'}]}},
'SemanticModelConfiguration': {'TableMap': {'string': {'Alias': 'string',
'DestinationTableId': 'string',
'RowLevelPermissionConfiguration': {'RowLevelPermissionDataSet': {'Arn': 'string',
'FormatVersion': 'VERSION_1 '
'| '
'VERSION_2',
'Namespace': 'string',
'PermissionPolicy': 'GRANT_ACCESS '
'| '
'DENY_ACCESS',
'Status': 'ENABLED '
'| '
'DISABLED'},
'TagConfiguration': {'Status': 'ENABLED '
'| '
'DISABLED',
'TagRuleConfigurations': [['string']],
'TagRules': [{'ColumnName': 'string',
'MatchAllValue': 'string',
'TagKey': 'string',
'TagMultiValueDelimiter': 'string'}]}}}}}}
Creates a dataset. This operation doesn't support datasets that include uploaded files as a source.
See also: AWS API Documentation
Request Syntax
client.create_data_set(
AwsAccountId='string',
DataSetId='string',
Name='string',
PhysicalTableMap={
'string': {
'RelationalTable': {
'DataSourceArn': 'string',
'Catalog': 'string',
'Schema': 'string',
'Name': 'string',
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'CustomSql': {
'DataSourceArn': 'string',
'Name': 'string',
'SqlQuery': 'string',
'Columns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'S3Source': {
'DataSourceArn': 'string',
'UploadSettings': {
'Format': 'CSV'|'TSV'|'CLF'|'ELF'|'XLSX'|'JSON',
'StartFromRow': 123,
'ContainsHeader': True|False,
'TextQualifier': 'DOUBLE_QUOTE'|'SINGLE_QUOTE',
'Delimiter': 'string',
'CustomCellAddressRange': 'string'
},
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'SaaSTable': {
'DataSourceArn': 'string',
'TablePath': [
{
'Name': 'string',
'Id': 'string'
},
],
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
}
}
},
LogicalTableMap={
'string': {
'Alias': 'string',
'DataTransforms': [
{
'ProjectOperation': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ProjectedColumns': [
'string',
]
},
'FilterOperation': {
'ConditionExpression': 'string',
'StringFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'CONTAINS'|'DOES_NOT_CONTAIN'|'STARTS_WITH'|'ENDS_WITH',
'Value': {
'StaticValue': 'string'
}
},
'ListFilterCondition': {
'Operator': 'INCLUDE'|'EXCLUDE',
'Values': {
'StaticValues': [
'string',
]
}
}
},
'NumericFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'GREATER_THAN'|'GREATER_THAN_OR_EQUALS_TO'|'LESS_THAN'|'LESS_THAN_OR_EQUALS_TO',
'Value': {
'StaticValue': 123.0
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': 123.0
},
'RangeMaximum': {
'StaticValue': 123.0
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
},
'DateFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'BEFORE'|'BEFORE_OR_EQUALS_TO'|'AFTER'|'AFTER_OR_EQUALS_TO',
'Value': {
'StaticValue': datetime(2015, 1, 1)
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': datetime(2015, 1, 1)
},
'RangeMaximum': {
'StaticValue': datetime(2015, 1, 1)
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
}
},
'CreateColumnsOperation': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Columns': [
{
'ColumnName': 'string',
'ColumnId': 'string',
'Expression': 'string'
},
]
},
'RenameColumnOperation': {
'ColumnName': 'string',
'NewColumnName': 'string'
},
'CastColumnTypeOperation': {
'ColumnName': 'string',
'NewColumnType': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME',
'SubType': 'FLOAT'|'FIXED',
'Format': 'string'
},
'TagColumnOperation': {
'ColumnName': 'string',
'Tags': [
{
'ColumnGeographicRole': 'COUNTRY'|'STATE'|'COUNTY'|'CITY'|'POSTCODE'|'LONGITUDE'|'LATITUDE',
'ColumnDescription': {
'Text': 'string'
}
},
]
},
'UntagColumnOperation': {
'ColumnName': 'string',
'TagNames': [
'COLUMN_GEOGRAPHIC_ROLE'|'COLUMN_DESCRIPTION',
]
},
'OverrideDatasetParameterOperation': {
'ParameterName': 'string',
'NewParameterName': 'string',
'NewDefaultValues': {
'StringStaticValues': [
'string',
],
'DecimalStaticValues': [
123.0,
],
'DateTimeStaticValues': [
datetime(2015, 1, 1),
],
'IntegerStaticValues': [
123,
]
}
}
},
],
'Source': {
'JoinInstruction': {
'LeftOperand': 'string',
'RightOperand': 'string',
'LeftJoinKeyProperties': {
'UniqueKey': True|False
},
'RightJoinKeyProperties': {
'UniqueKey': True|False
},
'Type': 'INNER'|'OUTER'|'LEFT'|'RIGHT',
'OnClause': 'string'
},
'PhysicalTableId': 'string',
'DataSetArn': 'string'
}
}
},
ImportMode='SPICE'|'DIRECT_QUERY',
ColumnGroups=[
{
'GeoSpatialColumnGroup': {
'Name': 'string',
'CountryCode': 'US',
'Columns': [
'string',
]
}
},
],
FieldFolders={
'string': {
'description': 'string',
'columns': [
'string',
]
}
},
Permissions=[
{
'Principal': 'string',
'Actions': [
'string',
]
},
],
RowLevelPermissionDataSet={
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
},
RowLevelPermissionTagConfiguration={
'Status': 'ENABLED'|'DISABLED',
'TagRules': [
{
'TagKey': 'string',
'ColumnName': 'string',
'TagMultiValueDelimiter': 'string',
'MatchAllValue': 'string'
},
],
'TagRuleConfigurations': [
[
'string',
],
]
},
ColumnLevelPermissionRules=[
{
'Principals': [
'string',
],
'ColumnNames': [
'string',
]
},
],
Tags=[
{
'Key': 'string',
'Value': 'string'
},
],
DataSetUsageConfiguration={
'DisableUseAsDirectQuerySource': True|False,
'DisableUseAsImportedSource': True|False
},
DatasetParameters=[
{
'StringDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
'string',
]
}
},
'DecimalDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
123.0,
]
}
},
'IntegerDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
123,
]
}
},
'DateTimeDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'TimeGranularity': 'YEAR'|'QUARTER'|'MONTH'|'WEEK'|'DAY'|'HOUR'|'MINUTE'|'SECOND'|'MILLISECOND',
'DefaultValues': {
'StaticValues': [
datetime(2015, 1, 1),
]
}
}
},
],
FolderArns=[
'string',
],
PerformanceConfiguration={
'UniqueKeys': [
{
'ColumnNames': [
'string',
]
},
]
},
UseAs='RLS_RULES',
DataPrepConfiguration={
'SourceTableMap': {
'string': {
'PhysicalTableId': 'string',
'DataSet': {
'DataSetArn': 'string',
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
}
}
},
'TransformStepMap': {
'string': {
'ImportTableStep': {
'Alias': 'string',
'Source': {
'SourceTableId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
}
},
'ProjectStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ProjectedColumns': [
'string',
]
},
'FiltersStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'FilterOperations': [
{
'ConditionExpression': 'string',
'StringFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'CONTAINS'|'DOES_NOT_CONTAIN'|'STARTS_WITH'|'ENDS_WITH',
'Value': {
'StaticValue': 'string'
}
},
'ListFilterCondition': {
'Operator': 'INCLUDE'|'EXCLUDE',
'Values': {
'StaticValues': [
'string',
]
}
}
},
'NumericFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'GREATER_THAN'|'GREATER_THAN_OR_EQUALS_TO'|'LESS_THAN'|'LESS_THAN_OR_EQUALS_TO',
'Value': {
'StaticValue': 123.0
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': 123.0
},
'RangeMaximum': {
'StaticValue': 123.0
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
},
'DateFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'BEFORE'|'BEFORE_OR_EQUALS_TO'|'AFTER'|'AFTER_OR_EQUALS_TO',
'Value': {
'StaticValue': datetime(2015, 1, 1)
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': datetime(2015, 1, 1)
},
'RangeMaximum': {
'StaticValue': datetime(2015, 1, 1)
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
}
},
]
},
'CreateColumnsStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Columns': [
{
'ColumnName': 'string',
'ColumnId': 'string',
'Expression': 'string'
},
]
},
'RenameColumnsStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'RenameColumnOperations': [
{
'ColumnName': 'string',
'NewColumnName': 'string'
},
]
},
'CastColumnTypesStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'CastColumnTypeOperations': [
{
'ColumnName': 'string',
'NewColumnType': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME',
'SubType': 'FLOAT'|'FIXED',
'Format': 'string'
},
]
},
'JoinStep': {
'Alias': 'string',
'LeftOperand': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'RightOperand': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Type': 'INNER'|'OUTER'|'LEFT'|'RIGHT',
'OnClause': 'string',
'LeftOperandProperties': {
'OutputColumnNameOverrides': [
{
'SourceColumnName': 'string',
'OutputColumnName': 'string'
},
]
},
'RightOperandProperties': {
'OutputColumnNameOverrides': [
{
'SourceColumnName': 'string',
'OutputColumnName': 'string'
},
]
}
},
'AggregateStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'GroupByColumnNames': [
'string',
],
'Aggregations': [
{
'AggregationFunction': {
'SimpleAggregation': {
'InputColumnName': 'string',
'FunctionType': 'COUNT'|'DISTINCT_COUNT'|'SUM'|'AVERAGE'|'MAX'|'MIN'
},
'ListAggregation': {
'InputColumnName': 'string',
'Separator': 'string',
'Distinct': True|False
}
},
'NewColumnName': 'string',
'NewColumnId': 'string'
},
]
},
'PivotStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'GroupByColumnNames': [
'string',
],
'ValueColumnConfiguration': {
'AggregationFunction': {
'SimpleAggregation': {
'InputColumnName': 'string',
'FunctionType': 'COUNT'|'DISTINCT_COUNT'|'SUM'|'AVERAGE'|'MAX'|'MIN'
},
'ListAggregation': {
'InputColumnName': 'string',
'Separator': 'string',
'Distinct': True|False
}
}
},
'PivotConfiguration': {
'LabelColumnName': 'string',
'PivotedLabels': [
{
'LabelName': 'string',
'NewColumnName': 'string',
'NewColumnId': 'string'
},
]
}
},
'UnpivotStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ColumnsToUnpivot': [
{
'ColumnName': 'string',
'NewValue': 'string'
},
],
'UnpivotedLabelColumnName': 'string',
'UnpivotedLabelColumnId': 'string',
'UnpivotedValueColumnName': 'string',
'UnpivotedValueColumnId': 'string'
},
'AppendStep': {
'Alias': 'string',
'FirstSource': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'SecondSource': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'AppendedColumns': [
{
'ColumnName': 'string',
'NewColumnId': 'string'
},
]
}
}
},
'DestinationTableMap': {
'string': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string'
}
}
}
},
SemanticModelConfiguration={
'TableMap': {
'string': {
'Alias': 'string',
'DestinationTableId': 'string',
'RowLevelPermissionConfiguration': {
'TagConfiguration': {
'Status': 'ENABLED'|'DISABLED',
'TagRules': [
{
'TagKey': 'string',
'ColumnName': 'string',
'TagMultiValueDelimiter': 'string',
'MatchAllValue': 'string'
},
],
'TagRuleConfigurations': [
[
'string',
],
]
},
'RowLevelPermissionDataSet': {
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
}
}
}
}
}
)
string
[REQUIRED]
The Amazon Web Services account ID.
string
[REQUIRED]
An ID for the dataset that you want to create. This ID is unique per Amazon Web Services Region for each Amazon Web Services account.
string
[REQUIRED]
The display name for the dataset.
dict
[REQUIRED]
Declares the physical tables that are available in the underlying data sources.
(string) --
(dict) --
A view of a data source that contains information about the shape of the data in the underlying source. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
RelationalTable (dict) --
A physical table type for relational data sources.
DataSourceArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) for the data source.
Catalog (string) --
The catalog associated with a table.
Schema (string) --
The schema name. This name applies to certain relational database engines.
Name (string) -- [REQUIRED]
The name of the relational table.
InputColumns (list) -- [REQUIRED]
The column schema of the table.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
CustomSql (dict) --
A physical table type built from the results of the custom SQL query.
DataSourceArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the data source.
Name (string) -- [REQUIRED]
A display name for the SQL query result.
SqlQuery (string) -- [REQUIRED]
The SQL query.
Columns (list) --
The column schema from the SQL query result set.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
S3Source (dict) --
A physical table type for as S3 data source.
DataSourceArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) for the data source.
UploadSettings (dict) --
Information about the format for the S3 source file or files.
Format (string) --
File format.
StartFromRow (integer) --
A row number to start reading data from.
ContainsHeader (boolean) --
Whether the file has a header row, or the files each have a header row.
TextQualifier (string) --
Text qualifier.
Delimiter (string) --
The delimiter between values in the file.
CustomCellAddressRange (string) --
A custom cell address range for Excel files, specifying which cells to import from the spreadsheet.
InputColumns (list) -- [REQUIRED]
A physical table type for an S3 data source.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
SaaSTable (dict) --
A physical table type for Software-as-a-Service (SaaS) sources.
DataSourceArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the SaaS data source.
TablePath (list) -- [REQUIRED]
The hierarchical path to the table within the SaaS data source.
(dict) --
An element in the hierarchical path to a table within a data source, containing both name and identifier.
Name (string) --
The name of the path element.
Id (string) --
The unique identifier of the path element.
InputColumns (list) -- [REQUIRED]
The list of input columns available from the SaaS table.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
dict
Configures the combination and transformation of the data from the physical tables. This parameter is used with the legacy data preparation experience.
(string) --
An identifier for the logical table that is defined in the dataset
(dict) --
A logical table is a unit that joins and that data transformations operate on. A logical table has a source, which can be either a physical table or result of a join. When a logical table points to a physical table, the logical table acts as a mutable copy of that physical table through transform operations.
Alias (string) -- [REQUIRED]
A display name for the logical table.
DataTransforms (list) --
Transform operations that act on this logical table. For this structure to be valid, only one of the attributes can be non-null.
(dict) --
A data transformation on a logical table. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
ProjectOperation (dict) --
An operation that projects columns. Operations that come after a projection can only refer to projected columns.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for column projection.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
ProjectedColumns (list) -- [REQUIRED]
Projected columns.
(string) --
FilterOperation (dict) --
An operation that filters rows based on some condition.
ConditionExpression (string) --
An expression that must evaluate to a Boolean value. Rows for which the expression evaluates to true are kept in the dataset.
StringFilterCondition (dict) --
A string-based filter condition within a filter operation.
ColumnName (string) --
The name of the string column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the string column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as EQUALS, CONTAINS, STARTS_WITH, ENDS_WITH, or their negations.
Value (dict) --
The string value to compare against.
StaticValue (string) --
A static string value used for filtering.
ListFilterCondition (dict) --
A list-based filter condition that includes or excludes values from a specified list.
Operator (string) -- [REQUIRED]
The list operator to use, either INCLUDE to match values in the list or EXCLUDE to filter out values in the list.
Values (dict) --
The list of string values to include or exclude in the filter.
StaticValues (list) --
A list of static string values used for filtering.
(string) --
NumericFilterCondition (dict) --
A numeric-based filter condition within a filter operation.
ColumnName (string) --
The name of the numeric column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the numeric column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as EQUALS, GREATER_THAN, LESS_THAN, or their variants.
Value (dict) --
The numeric value to compare against.
StaticValue (float) --
A static numeric value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the numeric column, filtering values between minimum and maximum numbers.
RangeMinimum (dict) --
The minimum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
RangeMaximum (dict) --
The maximum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
DateFilterCondition (dict) --
A date-based filter condition within a filter operation.
ColumnName (string) --
The name of the date column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the date column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as BEFORE, BEFORE_OR_EQUALS_TO, AFTER, or AFTER_OR_EQUALS_TO.
Value (dict) --
The date value to compare against.
StaticValue (datetime) --
A static date value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the date column, filtering values between minimum and maximum dates.
RangeMinimum (dict) --
The minimum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
RangeMaximum (dict) --
The maximum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
CreateColumnsOperation (dict) --
An operation that creates calculated columns. Columns created in one such operation form a lexical closure.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for creating new calculated columns.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
Columns (list) -- [REQUIRED]
Calculated columns to create.
(dict) --
A calculated column for a dataset.
ColumnName (string) -- [REQUIRED]
Column name.
ColumnId (string) -- [REQUIRED]
A unique ID to identify a calculated column. During a dataset update, if the column ID of a calculated column matches that of an existing calculated column, Quick Sight preserves the existing calculated column.
Expression (string) -- [REQUIRED]
An expression that defines the calculated column.
RenameColumnOperation (dict) --
An operation that renames a column.
ColumnName (string) -- [REQUIRED]
The name of the column to be renamed.
NewColumnName (string) -- [REQUIRED]
The new name for the column.
CastColumnTypeOperation (dict) --
A transform operation that casts a column to a different type.
ColumnName (string) -- [REQUIRED]
Column name.
NewColumnType (string) -- [REQUIRED]
New column data type.
SubType (string) --
The sub data type of the new column. Sub types are only available for decimal columns that are part of a SPICE dataset.
Format (string) --
When casting a column from string to datetime type, you can supply a string in a format supported by Quick Sight to denote the source data format.
TagColumnOperation (dict) --
An operation that tags a column with additional information.
ColumnName (string) -- [REQUIRED]
The column that this operation acts on.
Tags (list) -- [REQUIRED]
The dataset column tag, currently only used for geospatial type tagging.
(dict) --
A tag for a column in a TagColumnOperation structure. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
ColumnGeographicRole (string) --
A geospatial role for a column.
ColumnDescription (dict) --
A description for a column.
Text (string) --
The text of a description for a column.
UntagColumnOperation (dict) --
A transform operation that removes tags associated with a column.
ColumnName (string) -- [REQUIRED]
The column that this operation acts on.
TagNames (list) -- [REQUIRED]
The column tags to remove from this column.
(string) --
OverrideDatasetParameterOperation (dict) --
A transform operation that overrides the dataset parameter values that are defined in another dataset.
ParameterName (string) -- [REQUIRED]
The name of the parameter to be overridden with different values.
NewParameterName (string) --
The new name for the parameter.
NewDefaultValues (dict) --
The new default values for the parameter.
StringStaticValues (list) --
A list of static default values for a given string parameter.
(string) --
The default value for the string parameter.
DecimalStaticValues (list) --
A list of static default values for a given decimal parameter.
(float) --
The default value for the decimal parameter.
DateTimeStaticValues (list) --
A list of static default values for a given date time parameter.
(datetime) --
The default value for the date time parameter.
IntegerStaticValues (list) --
A list of static default values for a given integer parameter.
(integer) --
The default value for the integer parameter.
Source (dict) -- [REQUIRED]
Source of this logical table.
JoinInstruction (dict) --
Specifies the result of a join of two logical tables.
LeftOperand (string) -- [REQUIRED]
The operand on the left side of a join.
RightOperand (string) -- [REQUIRED]
The operand on the right side of a join.
LeftJoinKeyProperties (dict) --
Join key properties of the left operand.
UniqueKey (boolean) --
A value that indicates that a row in a table is uniquely identified by the columns in a join key. This is used by Quick Sight to optimize query performance.
RightJoinKeyProperties (dict) --
Join key properties of the right operand.
UniqueKey (boolean) --
A value that indicates that a row in a table is uniquely identified by the columns in a join key. This is used by Quick Sight to optimize query performance.
Type (string) -- [REQUIRED]
The type of join that it is.
OnClause (string) -- [REQUIRED]
The join instructions provided in the ON clause of a join.
PhysicalTableId (string) --
Physical table ID.
DataSetArn (string) --
The Amazon Resource Number (ARN) of the parent dataset.
string
[REQUIRED]
Indicates whether you want to import the data into SPICE.
list
Groupings of columns that work together in certain Amazon Quick Sight features. Currently, only geospatial hierarchy is supported.
(dict) --
Groupings of columns that work together in certain Quick Sight features. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
GeoSpatialColumnGroup (dict) --
Geospatial column group that denotes a hierarchy.
Name (string) -- [REQUIRED]
A display name for the hierarchy.
CountryCode (string) --
Country code.
Columns (list) -- [REQUIRED]
Columns in this hierarchy.
(string) --
dict
The folder that contains fields and nested subfolders for your dataset.
(string) --
(dict) --
A FieldFolder element is a folder that contains fields and nested subfolders.
description (string) --
The description for a field folder.
columns (list) --
A folder has a list of columns. A column can only be in one folder.
(string) --
list
A list of resource permissions on the dataset.
(dict) --
Permission for the resource.
Principal (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the principal. This can be one of the following:
The ARN of an Quick Sight user or group associated with a data source or dataset. (This is common.)
The ARN of an Quick Sight user, group, or namespace associated with an analysis, dashboard, template, or theme. Namespace sharing is not supported for action connectors. (This is common.)
The ARN of an Amazon Web Services account root: This is an IAM ARN rather than a Quick Sight ARN. Use this option only to share resources (templates) across Amazon Web Services accounts. Account root sharing is not supported for action connectors. (This is less common.)
Actions (list) -- [REQUIRED]
The IAM action to grant or revoke permissions on.
(string) --
dict
The row-level security configuration for the data that you want to create. This parameter is used with the legacy data preparation experience.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) -- [REQUIRED]
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
dict
The configuration of tags on a dataset to set row-level security. Row-level security tags are currently supported for anonymous embedding only. This parameter is used with the legacy data preparation experience.
Status (string) --
The status of row-level security tags. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
TagRules (list) -- [REQUIRED]
A set of rules associated with row-level security, such as the tag names and columns that they are assigned to.
(dict) --
A set of rules associated with a tag.
TagKey (string) -- [REQUIRED]
The unique key for a tag.
ColumnName (string) -- [REQUIRED]
The column name that a tag key is assigned to.
TagMultiValueDelimiter (string) --
A string that you want to use to delimit the values when you pass the values at run time. For example, you can delimit the values with a comma.
MatchAllValue (string) --
A string that you want to use to filter by all the values in a column in the dataset and don’t want to list the values one by one. For example, you can use an asterisk as your match all value.
TagRuleConfigurations (list) --
A list of tag configuration rules to apply to a dataset. All tag configurations have the OR condition. Tags within each tile will be joined (AND). At least one rule in this structure must have all tag values assigned to it to apply Row-level security (RLS) to the dataset.
(list) --
(string) --
list
A set of one or more definitions of a ``ColumnLevelPermissionRule ``.
(dict) --
A rule defined to grant access on one or more restricted columns. Each dataset can have multiple rules. To create a restricted column, you add it to one or more rules. Each rule must contain at least one column and at least one user or group. To be able to see a restricted column, a user or group needs to be added to a rule for that column.
Principals (list) --
An array of Amazon Resource Names (ARNs) for Quick Sight users or groups.
(string) --
ColumnNames (list) --
An array of column names.
(string) --
list
Contains a map of the key-value pairs for the resource tag or tags assigned to the dataset.
(dict) --
The key or keys of the key-value pairs for the resource tag or tags assigned to the resource.
Key (string) -- [REQUIRED]
Tag key.
Value (string) -- [REQUIRED]
Tag value.
dict
The usage configuration to apply to child datasets that reference this dataset as a source.
DisableUseAsDirectQuerySource (boolean) --
An option that controls whether a child dataset of a direct query can use this dataset as a source.
DisableUseAsImportedSource (boolean) --
An option that controls whether a child dataset that's stored in Quick Sight can use this dataset as a source.
list
The parameter declarations of the dataset.
(dict) --
A parameter that is created in a dataset. The parameter can be a string, integer, decimal, or datetime data type.
StringDatasetParameter (dict) --
A string parameter that is created in the dataset.
Id (string) -- [REQUIRED]
An identifier for the string parameter that is created in the dataset.
Name (string) -- [REQUIRED]
The name of the string parameter that is created in the dataset.
ValueType (string) -- [REQUIRED]
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given string dataset parameter type. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given string parameter.
(string) --
The default value for the string parameter.
DecimalDatasetParameter (dict) --
A decimal parameter that is created in the dataset.
Id (string) -- [REQUIRED]
An identifier for the decimal parameter created in the dataset.
Name (string) -- [REQUIRED]
The name of the decimal parameter that is created in the dataset.
ValueType (string) -- [REQUIRED]
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given decimal parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given decimal parameter.
(float) --
The default value for the decimal parameter.
IntegerDatasetParameter (dict) --
An integer parameter that is created in the dataset.
Id (string) -- [REQUIRED]
An identifier for the integer parameter created in the dataset.
Name (string) -- [REQUIRED]
The name of the integer parameter that is created in the dataset.
ValueType (string) -- [REQUIRED]
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given integer parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given integer parameter.
(integer) --
The default value for the integer parameter.
DateTimeDatasetParameter (dict) --
A date time parameter that is created in the dataset.
Id (string) -- [REQUIRED]
An identifier for the parameter that is created in the dataset.
Name (string) -- [REQUIRED]
The name of the date time parameter that is created in the dataset.
ValueType (string) -- [REQUIRED]
The value type of the dataset parameter. Valid values are single value or multi value.
TimeGranularity (string) --
The time granularity of the date time parameter.
DefaultValues (dict) --
A list of default values for a given date time parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given date time parameter.
(datetime) --
The default value for the date time parameter.
list
When you create the dataset, Amazon Quick Sight adds the dataset to these folders.
(string) --
dict
The configuration for the performance optimization of the dataset that contains a UniqueKey configuration.
UniqueKeys (list) --
A UniqueKey configuration.
(dict) --
A UniqueKey configuration that references a dataset column.
ColumnNames (list) -- [REQUIRED]
The name of the column that is referenced in the UniqueKey configuration.
(string) --
string
The usage of the dataset. RLS_RULES must be specified for RLS permission datasets.
dict
The data preparation configuration for the dataset. This configuration defines the source tables, transformation steps, and destination tables used to prepare the data. Required when using the new data preparation experience.
SourceTableMap (dict) -- [REQUIRED]
A map of source tables that provide information about underlying sources.
(string) --
(dict) --
A source table that provides initial data from either a physical table or parent dataset.
PhysicalTableId (string) --
The identifier of the physical table that serves as the data source.
DataSet (dict) --
A parent dataset that serves as the data source instead of a physical table.
DataSetArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the parent dataset.
InputColumns (list) -- [REQUIRED]
The list of input columns available from the parent dataset.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
TransformStepMap (dict) -- [REQUIRED]
A map of transformation steps that process the data.
(string) --
(dict) --
A step in data preparation that performs a specific operation on the data.
ImportTableStep (dict) --
A transform step that brings data from a source table.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source configuration that specifies which source table to import and any column mappings.
SourceTableId (string) -- [REQUIRED]
The identifier of the source table to import data from.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers during the import.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
ProjectStep (dict) --
A transform operation that projects columns. Operations that come after a projection can only refer to projected columns.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for column projection.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
ProjectedColumns (list) -- [REQUIRED]
Projected columns.
(string) --
FiltersStep (dict) --
A transform step that applies filter conditions.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for filtering.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
FilterOperations (list) -- [REQUIRED]
The list of filter operations to apply.
(dict) --
A transform operation that filters rows based on a condition.
ConditionExpression (string) --
An expression that must evaluate to a Boolean value. Rows for which the expression evaluates to true are kept in the dataset.
StringFilterCondition (dict) --
A string-based filter condition within a filter operation.
ColumnName (string) --
The name of the string column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the string column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as EQUALS, CONTAINS, STARTS_WITH, ENDS_WITH, or their negations.
Value (dict) --
The string value to compare against.
StaticValue (string) --
A static string value used for filtering.
ListFilterCondition (dict) --
A list-based filter condition that includes or excludes values from a specified list.
Operator (string) -- [REQUIRED]
The list operator to use, either INCLUDE to match values in the list or EXCLUDE to filter out values in the list.
Values (dict) --
The list of string values to include or exclude in the filter.
StaticValues (list) --
A list of static string values used for filtering.
(string) --
NumericFilterCondition (dict) --
A numeric-based filter condition within a filter operation.
ColumnName (string) --
The name of the numeric column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the numeric column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as EQUALS, GREATER_THAN, LESS_THAN, or their variants.
Value (dict) --
The numeric value to compare against.
StaticValue (float) --
A static numeric value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the numeric column, filtering values between minimum and maximum numbers.
RangeMinimum (dict) --
The minimum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
RangeMaximum (dict) --
The maximum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
DateFilterCondition (dict) --
A date-based filter condition within a filter operation.
ColumnName (string) --
The name of the date column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the date column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as BEFORE, BEFORE_OR_EQUALS_TO, AFTER, or AFTER_OR_EQUALS_TO.
Value (dict) --
The date value to compare against.
StaticValue (datetime) --
A static date value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the date column, filtering values between minimum and maximum dates.
RangeMinimum (dict) --
The minimum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
RangeMaximum (dict) --
The maximum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
CreateColumnsStep (dict) --
A transform operation that creates calculated columns. Columns created in one such operation form a lexical closure.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for creating new calculated columns.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
Columns (list) -- [REQUIRED]
Calculated columns to create.
(dict) --
A calculated column for a dataset.
ColumnName (string) -- [REQUIRED]
Column name.
ColumnId (string) -- [REQUIRED]
A unique ID to identify a calculated column. During a dataset update, if the column ID of a calculated column matches that of an existing calculated column, Quick Sight preserves the existing calculated column.
Expression (string) -- [REQUIRED]
An expression that defines the calculated column.
RenameColumnsStep (dict) --
A transform step that changes the names of one or more columns.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for column renaming.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
RenameColumnOperations (list) -- [REQUIRED]
The list of column rename operations to perform, specifying old and new column names.
(dict) --
A transform operation that renames a column.
ColumnName (string) -- [REQUIRED]
The name of the column to be renamed.
NewColumnName (string) -- [REQUIRED]
The new name for the column.
CastColumnTypesStep (dict) --
A transform step that changes the data types of one or more columns.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for the type casting.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
CastColumnTypeOperations (list) -- [REQUIRED]
The list of column type casting operations to perform.
(dict) --
A transform operation that casts a column to a different type.
ColumnName (string) -- [REQUIRED]
Column name.
NewColumnType (string) -- [REQUIRED]
New column data type.
SubType (string) --
The sub data type of the new column. Sub types are only available for decimal columns that are part of a SPICE dataset.
Format (string) --
When casting a column from string to datetime type, you can supply a string in a format supported by Quick Sight to denote the source data format.
JoinStep (dict) --
A transform step that combines data from two sources based on specified join conditions.
Alias (string) -- [REQUIRED]
Alias for this operation.
LeftOperand (dict) -- [REQUIRED]
The left operand for the join operation.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
RightOperand (dict) -- [REQUIRED]
The right operand for the join operation.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
Type (string) -- [REQUIRED]
The type of join to perform, such as INNER, LEFT, RIGHT, or OUTER.
OnClause (string) -- [REQUIRED]
The join condition that specifies how to match rows between the left and right operands.
LeftOperandProperties (dict) --
Properties that control how the left operand's columns are handled in the join result.
OutputColumnNameOverrides (list) -- [REQUIRED]
A list of column name overrides to apply to the join operand's output columns.
(dict) --
Specifies a mapping to override the name of an output column from a transform operation.
SourceColumnName (string) --
The original name of the column from the source transform operation.
OutputColumnName (string) -- [REQUIRED]
The new name to assign to the column in the output.
RightOperandProperties (dict) --
Properties that control how the right operand's columns are handled in the join result.
OutputColumnNameOverrides (list) -- [REQUIRED]
A list of column name overrides to apply to the join operand's output columns.
(dict) --
Specifies a mapping to override the name of an output column from a transform operation.
SourceColumnName (string) --
The original name of the column from the source transform operation.
OutputColumnName (string) -- [REQUIRED]
The new name to assign to the column in the output.
AggregateStep (dict) --
A transform step that groups data and applies aggregation functions to calculate summary values.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for the aggregation.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
GroupByColumnNames (list) --
The list of column names to group by when performing the aggregation. Rows with the same values in these columns will be grouped together.
(string) --
Aggregations (list) -- [REQUIRED]
The list of aggregation functions to apply to the grouped data, such as SUM, COUNT, or AVERAGE.
(dict) --
Defines an aggregation function to be applied to grouped data, creating a new column with the calculated result.
AggregationFunction (dict) -- [REQUIRED]
The aggregation function to apply, such as SUM, COUNT, AVERAGE, MIN, MAX
SimpleAggregation (dict) --
A simple aggregation function such as SUM, COUNT, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
InputColumnName (string) --
The name of the column on which to perform the aggregation function.
FunctionType (string) -- [REQUIRED]
The type of aggregation function to perform, such as COUNT, SUM, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
ListAggregation (dict) --
A list aggregation function that concatenates values from multiple rows into a single delimited string.
InputColumnName (string) --
The name of the column containing values to be concatenated.
Separator (string) -- [REQUIRED]
The string used to separate values in the concatenated result.
Distinct (boolean) -- [REQUIRED]
Whether to include only distinct values in the concatenated result, removing duplicates.
NewColumnName (string) -- [REQUIRED]
The name for the new column that will contain the aggregated values.
NewColumnId (string) -- [REQUIRED]
A unique identifier for the new column that will contain the aggregated values.
PivotStep (dict) --
A transform step that converts row values into columns to reshape the data structure.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for pivoting.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
GroupByColumnNames (list) --
The list of column names to group by when performing the pivot operation.
(string) --
ValueColumnConfiguration (dict) -- [REQUIRED]
Configuration for how to aggregate values when multiple rows map to the same pivoted column.
AggregationFunction (dict) --
The aggregation function to apply when multiple values map to the same pivoted cell.
SimpleAggregation (dict) --
A simple aggregation function such as SUM, COUNT, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
InputColumnName (string) --
The name of the column on which to perform the aggregation function.
FunctionType (string) -- [REQUIRED]
The type of aggregation function to perform, such as COUNT, SUM, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
ListAggregation (dict) --
A list aggregation function that concatenates values from multiple rows into a single delimited string.
InputColumnName (string) --
The name of the column containing values to be concatenated.
Separator (string) -- [REQUIRED]
The string used to separate values in the concatenated result.
Distinct (boolean) -- [REQUIRED]
Whether to include only distinct values in the concatenated result, removing duplicates.
PivotConfiguration (dict) -- [REQUIRED]
Configuration that specifies which labels to pivot and how to structure the resulting columns.
LabelColumnName (string) --
The name of the column that contains the labels to be pivoted into separate columns.
PivotedLabels (list) -- [REQUIRED]
The list of specific label values to pivot into separate columns.
(dict) --
Specifies a label value to be pivoted into a separate column, including the new column name and identifier.
LabelName (string) -- [REQUIRED]
The label value from the source data to be pivoted.
NewColumnName (string) -- [REQUIRED]
The name for the new column created from this pivoted label.
NewColumnId (string) -- [REQUIRED]
A unique identifier for the new column created from this pivoted label.
UnpivotStep (dict) --
A transform step that converts columns into rows to normalize the data structure.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for unpivoting.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
ColumnsToUnpivot (list) -- [REQUIRED]
The list of columns to unpivot from the source data.
(dict) --
Specifies a column to be unpivoted, transforming it from a column into rows with associated values.
ColumnName (string) --
The name of the column to unpivot from the source data.
NewValue (string) --
The value to assign to this column in the unpivoted result, typically the column name or a descriptive label.
UnpivotedLabelColumnName (string) -- [REQUIRED]
The name for the new column that will contain the unpivoted column names.
UnpivotedLabelColumnId (string) -- [REQUIRED]
A unique identifier for the new column that will contain the unpivoted column names.
UnpivotedValueColumnName (string) -- [REQUIRED]
The name for the new column that will contain the unpivoted values.
UnpivotedValueColumnId (string) -- [REQUIRED]
A unique identifier for the new column that will contain the unpivoted values.
AppendStep (dict) --
A transform step that combines rows from multiple sources by stacking them vertically.
Alias (string) -- [REQUIRED]
Alias for this operation.
FirstSource (dict) --
The first data source to be included in the append operation.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
SecondSource (dict) --
The second data source to be appended to the first source.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
AppendedColumns (list) -- [REQUIRED]
The list of columns to include in the appended result, mapping columns from both sources.
(dict) --
Represents a column that will be included in the result of an append operation, combining data from multiple sources.
ColumnName (string) -- [REQUIRED]
The name of the column to include in the appended result.
NewColumnId (string) -- [REQUIRED]
A unique identifier for the column in the appended result.
DestinationTableMap (dict) -- [REQUIRED]
A map of destination tables that receive the final prepared data.
(string) --
(dict) --
Defines a destination table in data preparation that receives the final transformed data.
Alias (string) -- [REQUIRED]
Alias for the destination table.
Source (dict) -- [REQUIRED]
The source configuration that specifies which transform operation provides data to this destination table.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides data to the destination table.
dict
The semantic model configuration for the dataset. This configuration defines how the prepared data is structured for an analysis, including table mappings and row-level security configurations. Required when using the new data preparation experience.
TableMap (dict) --
A map of semantic tables that define the analytical structure.
(string) --
(dict) --
A semantic table that represents the final analytical structure of the data.
Alias (string) -- [REQUIRED]
Alias for the semantic table.
DestinationTableId (string) -- [REQUIRED]
The identifier of the destination table from data preparation that provides data to this semantic table.
RowLevelPermissionConfiguration (dict) --
Configuration for row level security that control data access for this semantic table.
TagConfiguration (dict) --
The configuration of tags on a dataset to set row-level security.
Status (string) --
The status of row-level security tags. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
TagRules (list) -- [REQUIRED]
A set of rules associated with row-level security, such as the tag names and columns that they are assigned to.
(dict) --
A set of rules associated with a tag.
TagKey (string) -- [REQUIRED]
The unique key for a tag.
ColumnName (string) -- [REQUIRED]
The column name that a tag key is assigned to.
TagMultiValueDelimiter (string) --
A string that you want to use to delimit the values when you pass the values at run time. For example, you can delimit the values with a comma.
MatchAllValue (string) --
A string that you want to use to filter by all the values in a column in the dataset and don’t want to list the values one by one. For example, you can use an asterisk as your match all value.
TagRuleConfigurations (list) --
A list of tag configuration rules to apply to a dataset. All tag configurations have the OR condition. Tags within each tile will be joined (AND). At least one rule in this structure must have all tag values assigned to it to apply Row-level security (RLS) to the dataset.
(list) --
(string) --
RowLevelPermissionDataSet (dict) --
Information about a dataset that contains permissions for row-level security (RLS). The permissions dataset maps fields to users or groups. For more information, see Using Row-Level Security (RLS) to Restrict Access to a Dataset in the Quick Sight User Guide.
The option to deny permissions by setting PermissionPolicy to DENY_ACCESS is not supported for new RLS datasets.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) -- [REQUIRED]
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
dict
Response Syntax
{
'Arn': 'string',
'DataSetId': 'string',
'IngestionArn': 'string',
'IngestionId': 'string',
'RequestId': 'string',
'Status': 123
}
Response Structure
(dict) --
Arn (string) --
The Amazon Resource Name (ARN) of the dataset.
DataSetId (string) --
The ID for the dataset that you want to create. This ID is unique per Amazon Web Services Region for each Amazon Web Services account.
IngestionArn (string) --
The ARN for the ingestion, which is triggered as a result of dataset creation if the import mode is SPICE.
IngestionId (string) --
The ID of the ingestion, which is triggered as a result of dataset creation if the import mode is SPICE.
RequestId (string) --
The Amazon Web Services request ID for this operation.
Status (integer) --
The HTTP status of the request.
{'DataSet': {'DataPrepConfiguration': {'DestinationTableMap': {'string': {'Alias': 'string',
'Source': {'TransformOperationId': 'string'}}},
'SourceTableMap': {'string': {'DataSet': {'DataSetArn': 'string',
'InputColumns': [{'Id': 'string',
'Name': 'string',
'SubType': 'FLOAT '
'| '
'FIXED',
'Type': 'STRING '
'| '
'INTEGER '
'| '
'DECIMAL '
'| '
'DATETIME '
'| '
'BIT '
'| '
'BOOLEAN '
'| '
'JSON'}]},
'PhysicalTableId': 'string'}},
'TransformStepMap': {'string': {'AggregateStep': {'Aggregations': [{'AggregationFunction': {'ListAggregation': {'Distinct': 'boolean',
'InputColumnName': 'string',
'Separator': 'string'},
'SimpleAggregation': {'FunctionType': 'COUNT '
'| '
'DISTINCT_COUNT '
'| '
'SUM '
'| '
'AVERAGE '
'| '
'MAX '
'| '
'MIN',
'InputColumnName': 'string'}},
'NewColumnId': 'string',
'NewColumnName': 'string'}],
'Alias': 'string',
'GroupByColumnNames': ['string'],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'AppendStep': {'Alias': 'string',
'AppendedColumns': [{'ColumnName': 'string',
'NewColumnId': 'string'}],
'FirstSource': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'SecondSource': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'CastColumnTypesStep': {'Alias': 'string',
'CastColumnTypeOperations': [{'ColumnName': 'string',
'Format': 'string',
'NewColumnType': 'STRING '
'| '
'INTEGER '
'| '
'DECIMAL '
'| '
'DATETIME',
'SubType': 'FLOAT '
'| '
'FIXED'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'CreateColumnsStep': {'Alias': 'string',
'Columns': [{'ColumnId': 'string',
'ColumnName': 'string',
'Expression': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'FiltersStep': {'Alias': 'string',
'FilterOperations': [{'ConditionExpression': 'string',
'DateFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'BEFORE '
'| '
'BEFORE_OR_EQUALS_TO '
'| '
'AFTER '
'| '
'AFTER_OR_EQUALS_TO',
'Value': {'StaticValue': 'timestamp'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'timestamp'},
'RangeMinimum': {'StaticValue': 'timestamp'}}},
'NumericFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'GREATER_THAN '
'| '
'GREATER_THAN_OR_EQUALS_TO '
'| '
'LESS_THAN '
'| '
'LESS_THAN_OR_EQUALS_TO',
'Value': {'StaticValue': 'double'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'double'},
'RangeMinimum': {'StaticValue': 'double'}}},
'StringFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'CONTAINS '
'| '
'DOES_NOT_CONTAIN '
'| '
'STARTS_WITH '
'| '
'ENDS_WITH',
'Value': {'StaticValue': 'string'}},
'ListFilterCondition': {'Operator': 'INCLUDE '
'| '
'EXCLUDE',
'Values': {'StaticValues': ['string']}}}}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'ImportTableStep': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'SourceTableId': 'string'}},
'JoinStep': {'Alias': 'string',
'LeftOperand': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'LeftOperandProperties': {'OutputColumnNameOverrides': [{'OutputColumnName': 'string',
'SourceColumnName': 'string'}]},
'OnClause': 'string',
'RightOperand': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'RightOperandProperties': {'OutputColumnNameOverrides': [{'OutputColumnName': 'string',
'SourceColumnName': 'string'}]},
'Type': 'INNER '
'| '
'OUTER '
'| '
'LEFT '
'| '
'RIGHT'},
'PivotStep': {'Alias': 'string',
'GroupByColumnNames': ['string'],
'PivotConfiguration': {'LabelColumnName': 'string',
'PivotedLabels': [{'LabelName': 'string',
'NewColumnId': 'string',
'NewColumnName': 'string'}]},
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'ValueColumnConfiguration': {'AggregationFunction': {'ListAggregation': {'Distinct': 'boolean',
'InputColumnName': 'string',
'Separator': 'string'},
'SimpleAggregation': {'FunctionType': 'COUNT '
'| '
'DISTINCT_COUNT '
'| '
'SUM '
'| '
'AVERAGE '
'| '
'MAX '
'| '
'MIN',
'InputColumnName': 'string'}}}},
'ProjectStep': {'Alias': 'string',
'ProjectedColumns': ['string'],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'RenameColumnsStep': {'Alias': 'string',
'RenameColumnOperations': [{'ColumnName': 'string',
'NewColumnName': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'UnpivotStep': {'Alias': 'string',
'ColumnsToUnpivot': [{'ColumnName': 'string',
'NewValue': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'UnpivotedLabelColumnId': 'string',
'UnpivotedLabelColumnName': 'string',
'UnpivotedValueColumnId': 'string',
'UnpivotedValueColumnName': 'string'}}}},
'LogicalTableMap': {'DataTransforms': {'CreateColumnsOperation': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'FilterOperation': {'DateFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'BEFORE '
'| '
'BEFORE_OR_EQUALS_TO '
'| '
'AFTER '
'| '
'AFTER_OR_EQUALS_TO',
'Value': {'StaticValue': 'timestamp'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'timestamp'},
'RangeMinimum': {'StaticValue': 'timestamp'}}},
'NumericFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'GREATER_THAN '
'| '
'GREATER_THAN_OR_EQUALS_TO '
'| '
'LESS_THAN '
'| '
'LESS_THAN_OR_EQUALS_TO',
'Value': {'StaticValue': 'double'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'double'},
'RangeMinimum': {'StaticValue': 'double'}}},
'StringFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'CONTAINS '
'| '
'DOES_NOT_CONTAIN '
'| '
'STARTS_WITH '
'| '
'ENDS_WITH',
'Value': {'StaticValue': 'string'}},
'ListFilterCondition': {'Operator': 'INCLUDE '
'| '
'EXCLUDE',
'Values': {'StaticValues': ['string']}}}},
'ProjectOperation': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}}}},
'OutputColumns': {'Id': 'string'},
'PhysicalTableMap': {'CustomSql': {'Columns': {'Id': 'string'}},
'RelationalTable': {'InputColumns': {'Id': 'string'}},
'S3Source': {'InputColumns': {'Id': 'string'},
'UploadSettings': {'CustomCellAddressRange': 'string'}},
'SaaSTable': {'DataSourceArn': 'string',
'InputColumns': [{'Id': 'string',
'Name': 'string',
'SubType': 'FLOAT '
'| '
'FIXED',
'Type': 'STRING '
'| '
'INTEGER '
'| '
'DECIMAL '
'| '
'DATETIME '
'| '
'BIT '
'| '
'BOOLEAN '
'| '
'JSON'}],
'TablePath': [{'Id': 'string',
'Name': 'string'}]}},
'SemanticModelConfiguration': {'TableMap': {'string': {'Alias': 'string',
'DestinationTableId': 'string',
'RowLevelPermissionConfiguration': {'RowLevelPermissionDataSet': {'Arn': 'string',
'FormatVersion': 'VERSION_1 '
'| '
'VERSION_2',
'Namespace': 'string',
'PermissionPolicy': 'GRANT_ACCESS '
'| '
'DENY_ACCESS',
'Status': 'ENABLED '
'| '
'DISABLED'},
'TagConfiguration': {'Status': 'ENABLED '
'| '
'DISABLED',
'TagRuleConfigurations': [['string']],
'TagRules': [{'ColumnName': 'string',
'MatchAllValue': 'string',
'TagKey': 'string',
'TagMultiValueDelimiter': 'string'}]}}}}}}}
Describes a dataset. This operation doesn't support datasets that include uploaded files as a source.
See also: AWS API Documentation
Request Syntax
client.describe_data_set(
AwsAccountId='string',
DataSetId='string'
)
string
[REQUIRED]
The Amazon Web Services account ID.
string
[REQUIRED]
The ID for the dataset that you want to describe. This ID is unique per Amazon Web Services Region for each Amazon Web Services account.
dict
Response Syntax
{
'DataSet': {
'Arn': 'string',
'DataSetId': 'string',
'Name': 'string',
'CreatedTime': datetime(2015, 1, 1),
'LastUpdatedTime': datetime(2015, 1, 1),
'PhysicalTableMap': {
'string': {
'RelationalTable': {
'DataSourceArn': 'string',
'Catalog': 'string',
'Schema': 'string',
'Name': 'string',
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'CustomSql': {
'DataSourceArn': 'string',
'Name': 'string',
'SqlQuery': 'string',
'Columns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'S3Source': {
'DataSourceArn': 'string',
'UploadSettings': {
'Format': 'CSV'|'TSV'|'CLF'|'ELF'|'XLSX'|'JSON',
'StartFromRow': 123,
'ContainsHeader': True|False,
'TextQualifier': 'DOUBLE_QUOTE'|'SINGLE_QUOTE',
'Delimiter': 'string',
'CustomCellAddressRange': 'string'
},
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'SaaSTable': {
'DataSourceArn': 'string',
'TablePath': [
{
'Name': 'string',
'Id': 'string'
},
],
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
}
}
},
'LogicalTableMap': {
'string': {
'Alias': 'string',
'DataTransforms': [
{
'ProjectOperation': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ProjectedColumns': [
'string',
]
},
'FilterOperation': {
'ConditionExpression': 'string',
'StringFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'CONTAINS'|'DOES_NOT_CONTAIN'|'STARTS_WITH'|'ENDS_WITH',
'Value': {
'StaticValue': 'string'
}
},
'ListFilterCondition': {
'Operator': 'INCLUDE'|'EXCLUDE',
'Values': {
'StaticValues': [
'string',
]
}
}
},
'NumericFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'GREATER_THAN'|'GREATER_THAN_OR_EQUALS_TO'|'LESS_THAN'|'LESS_THAN_OR_EQUALS_TO',
'Value': {
'StaticValue': 123.0
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': 123.0
},
'RangeMaximum': {
'StaticValue': 123.0
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
},
'DateFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'BEFORE'|'BEFORE_OR_EQUALS_TO'|'AFTER'|'AFTER_OR_EQUALS_TO',
'Value': {
'StaticValue': datetime(2015, 1, 1)
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': datetime(2015, 1, 1)
},
'RangeMaximum': {
'StaticValue': datetime(2015, 1, 1)
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
}
},
'CreateColumnsOperation': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Columns': [
{
'ColumnName': 'string',
'ColumnId': 'string',
'Expression': 'string'
},
]
},
'RenameColumnOperation': {
'ColumnName': 'string',
'NewColumnName': 'string'
},
'CastColumnTypeOperation': {
'ColumnName': 'string',
'NewColumnType': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME',
'SubType': 'FLOAT'|'FIXED',
'Format': 'string'
},
'TagColumnOperation': {
'ColumnName': 'string',
'Tags': [
{
'ColumnGeographicRole': 'COUNTRY'|'STATE'|'COUNTY'|'CITY'|'POSTCODE'|'LONGITUDE'|'LATITUDE',
'ColumnDescription': {
'Text': 'string'
}
},
]
},
'UntagColumnOperation': {
'ColumnName': 'string',
'TagNames': [
'COLUMN_GEOGRAPHIC_ROLE'|'COLUMN_DESCRIPTION',
]
},
'OverrideDatasetParameterOperation': {
'ParameterName': 'string',
'NewParameterName': 'string',
'NewDefaultValues': {
'StringStaticValues': [
'string',
],
'DecimalStaticValues': [
123.0,
],
'DateTimeStaticValues': [
datetime(2015, 1, 1),
],
'IntegerStaticValues': [
123,
]
}
}
},
],
'Source': {
'JoinInstruction': {
'LeftOperand': 'string',
'RightOperand': 'string',
'LeftJoinKeyProperties': {
'UniqueKey': True|False
},
'RightJoinKeyProperties': {
'UniqueKey': True|False
},
'Type': 'INNER'|'OUTER'|'LEFT'|'RIGHT',
'OnClause': 'string'
},
'PhysicalTableId': 'string',
'DataSetArn': 'string'
}
}
},
'OutputColumns': [
{
'Name': 'string',
'Id': 'string',
'Description': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME',
'SubType': 'FLOAT'|'FIXED'
},
],
'ImportMode': 'SPICE'|'DIRECT_QUERY',
'ConsumedSpiceCapacityInBytes': 123,
'ColumnGroups': [
{
'GeoSpatialColumnGroup': {
'Name': 'string',
'CountryCode': 'US',
'Columns': [
'string',
]
}
},
],
'FieldFolders': {
'string': {
'description': 'string',
'columns': [
'string',
]
}
},
'RowLevelPermissionDataSet': {
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
},
'RowLevelPermissionTagConfiguration': {
'Status': 'ENABLED'|'DISABLED',
'TagRules': [
{
'TagKey': 'string',
'ColumnName': 'string',
'TagMultiValueDelimiter': 'string',
'MatchAllValue': 'string'
},
],
'TagRuleConfigurations': [
[
'string',
],
]
},
'ColumnLevelPermissionRules': [
{
'Principals': [
'string',
],
'ColumnNames': [
'string',
]
},
],
'DataSetUsageConfiguration': {
'DisableUseAsDirectQuerySource': True|False,
'DisableUseAsImportedSource': True|False
},
'DatasetParameters': [
{
'StringDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
'string',
]
}
},
'DecimalDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
123.0,
]
}
},
'IntegerDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
123,
]
}
},
'DateTimeDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'TimeGranularity': 'YEAR'|'QUARTER'|'MONTH'|'WEEK'|'DAY'|'HOUR'|'MINUTE'|'SECOND'|'MILLISECOND',
'DefaultValues': {
'StaticValues': [
datetime(2015, 1, 1),
]
}
}
},
],
'PerformanceConfiguration': {
'UniqueKeys': [
{
'ColumnNames': [
'string',
]
},
]
},
'UseAs': 'RLS_RULES',
'DataPrepConfiguration': {
'SourceTableMap': {
'string': {
'PhysicalTableId': 'string',
'DataSet': {
'DataSetArn': 'string',
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
}
}
},
'TransformStepMap': {
'string': {
'ImportTableStep': {
'Alias': 'string',
'Source': {
'SourceTableId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
}
},
'ProjectStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ProjectedColumns': [
'string',
]
},
'FiltersStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'FilterOperations': [
{
'ConditionExpression': 'string',
'StringFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'CONTAINS'|'DOES_NOT_CONTAIN'|'STARTS_WITH'|'ENDS_WITH',
'Value': {
'StaticValue': 'string'
}
},
'ListFilterCondition': {
'Operator': 'INCLUDE'|'EXCLUDE',
'Values': {
'StaticValues': [
'string',
]
}
}
},
'NumericFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'GREATER_THAN'|'GREATER_THAN_OR_EQUALS_TO'|'LESS_THAN'|'LESS_THAN_OR_EQUALS_TO',
'Value': {
'StaticValue': 123.0
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': 123.0
},
'RangeMaximum': {
'StaticValue': 123.0
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
},
'DateFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'BEFORE'|'BEFORE_OR_EQUALS_TO'|'AFTER'|'AFTER_OR_EQUALS_TO',
'Value': {
'StaticValue': datetime(2015, 1, 1)
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': datetime(2015, 1, 1)
},
'RangeMaximum': {
'StaticValue': datetime(2015, 1, 1)
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
}
},
]
},
'CreateColumnsStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Columns': [
{
'ColumnName': 'string',
'ColumnId': 'string',
'Expression': 'string'
},
]
},
'RenameColumnsStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'RenameColumnOperations': [
{
'ColumnName': 'string',
'NewColumnName': 'string'
},
]
},
'CastColumnTypesStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'CastColumnTypeOperations': [
{
'ColumnName': 'string',
'NewColumnType': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME',
'SubType': 'FLOAT'|'FIXED',
'Format': 'string'
},
]
},
'JoinStep': {
'Alias': 'string',
'LeftOperand': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'RightOperand': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Type': 'INNER'|'OUTER'|'LEFT'|'RIGHT',
'OnClause': 'string',
'LeftOperandProperties': {
'OutputColumnNameOverrides': [
{
'SourceColumnName': 'string',
'OutputColumnName': 'string'
},
]
},
'RightOperandProperties': {
'OutputColumnNameOverrides': [
{
'SourceColumnName': 'string',
'OutputColumnName': 'string'
},
]
}
},
'AggregateStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'GroupByColumnNames': [
'string',
],
'Aggregations': [
{
'AggregationFunction': {
'SimpleAggregation': {
'InputColumnName': 'string',
'FunctionType': 'COUNT'|'DISTINCT_COUNT'|'SUM'|'AVERAGE'|'MAX'|'MIN'
},
'ListAggregation': {
'InputColumnName': 'string',
'Separator': 'string',
'Distinct': True|False
}
},
'NewColumnName': 'string',
'NewColumnId': 'string'
},
]
},
'PivotStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'GroupByColumnNames': [
'string',
],
'ValueColumnConfiguration': {
'AggregationFunction': {
'SimpleAggregation': {
'InputColumnName': 'string',
'FunctionType': 'COUNT'|'DISTINCT_COUNT'|'SUM'|'AVERAGE'|'MAX'|'MIN'
},
'ListAggregation': {
'InputColumnName': 'string',
'Separator': 'string',
'Distinct': True|False
}
}
},
'PivotConfiguration': {
'LabelColumnName': 'string',
'PivotedLabels': [
{
'LabelName': 'string',
'NewColumnName': 'string',
'NewColumnId': 'string'
},
]
}
},
'UnpivotStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ColumnsToUnpivot': [
{
'ColumnName': 'string',
'NewValue': 'string'
},
],
'UnpivotedLabelColumnName': 'string',
'UnpivotedLabelColumnId': 'string',
'UnpivotedValueColumnName': 'string',
'UnpivotedValueColumnId': 'string'
},
'AppendStep': {
'Alias': 'string',
'FirstSource': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'SecondSource': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'AppendedColumns': [
{
'ColumnName': 'string',
'NewColumnId': 'string'
},
]
}
}
},
'DestinationTableMap': {
'string': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string'
}
}
}
},
'SemanticModelConfiguration': {
'TableMap': {
'string': {
'Alias': 'string',
'DestinationTableId': 'string',
'RowLevelPermissionConfiguration': {
'TagConfiguration': {
'Status': 'ENABLED'|'DISABLED',
'TagRules': [
{
'TagKey': 'string',
'ColumnName': 'string',
'TagMultiValueDelimiter': 'string',
'MatchAllValue': 'string'
},
],
'TagRuleConfigurations': [
[
'string',
],
]
},
'RowLevelPermissionDataSet': {
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
}
}
}
}
}
},
'RequestId': 'string',
'Status': 123
}
Response Structure
(dict) --
DataSet (dict) --
Information on the dataset.
Arn (string) --
The Amazon Resource Name (ARN) of the resource.
DataSetId (string) --
The ID of the dataset. Limited to 96 characters.
Name (string) --
A display name for the dataset.
CreatedTime (datetime) --
The time that this dataset was created.
LastUpdatedTime (datetime) --
The last time that this dataset was updated.
PhysicalTableMap (dict) --
Declares the physical tables that are available in the underlying data sources.
(string) --
(dict) --
A view of a data source that contains information about the shape of the data in the underlying source. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
RelationalTable (dict) --
A physical table type for relational data sources.
DataSourceArn (string) --
The Amazon Resource Name (ARN) for the data source.
Catalog (string) --
The catalog associated with a table.
Schema (string) --
The schema name. This name applies to certain relational database engines.
Name (string) --
The name of the relational table.
InputColumns (list) --
The column schema of the table.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) --
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) --
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
CustomSql (dict) --
A physical table type built from the results of the custom SQL query.
DataSourceArn (string) --
The Amazon Resource Name (ARN) of the data source.
Name (string) --
A display name for the SQL query result.
SqlQuery (string) --
The SQL query.
Columns (list) --
The column schema from the SQL query result set.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) --
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) --
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
S3Source (dict) --
A physical table type for as S3 data source.
DataSourceArn (string) --
The Amazon Resource Name (ARN) for the data source.
UploadSettings (dict) --
Information about the format for the S3 source file or files.
Format (string) --
File format.
StartFromRow (integer) --
A row number to start reading data from.
ContainsHeader (boolean) --
Whether the file has a header row, or the files each have a header row.
TextQualifier (string) --
Text qualifier.
Delimiter (string) --
The delimiter between values in the file.
CustomCellAddressRange (string) --
A custom cell address range for Excel files, specifying which cells to import from the spreadsheet.
InputColumns (list) --
A physical table type for an S3 data source.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) --
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) --
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
SaaSTable (dict) --
A physical table type for Software-as-a-Service (SaaS) sources.
DataSourceArn (string) --
The Amazon Resource Name (ARN) of the SaaS data source.
TablePath (list) --
The hierarchical path to the table within the SaaS data source.
(dict) --
An element in the hierarchical path to a table within a data source, containing both name and identifier.
Name (string) --
The name of the path element.
Id (string) --
The unique identifier of the path element.
InputColumns (list) --
The list of input columns available from the SaaS table.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) --
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) --
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
LogicalTableMap (dict) --
Configures the combination and transformation of the data from the physical tables.
(string) --
An identifier for the logical table that is defined in the dataset
(dict) --
A logical table is a unit that joins and that data transformations operate on. A logical table has a source, which can be either a physical table or result of a join. When a logical table points to a physical table, the logical table acts as a mutable copy of that physical table through transform operations.
Alias (string) --
A display name for the logical table.
DataTransforms (list) --
Transform operations that act on this logical table. For this structure to be valid, only one of the attributes can be non-null.
(dict) --
A data transformation on a logical table. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
ProjectOperation (dict) --
An operation that projects columns. Operations that come after a projection can only refer to projected columns.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for column projection.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
ProjectedColumns (list) --
Projected columns.
(string) --
FilterOperation (dict) --
An operation that filters rows based on some condition.
ConditionExpression (string) --
An expression that must evaluate to a Boolean value. Rows for which the expression evaluates to true are kept in the dataset.
StringFilterCondition (dict) --
A string-based filter condition within a filter operation.
ColumnName (string) --
The name of the string column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the string column.
Operator (string) --
The comparison operator to use, such as EQUALS, CONTAINS, STARTS_WITH, ENDS_WITH, or their negations.
Value (dict) --
The string value to compare against.
StaticValue (string) --
A static string value used for filtering.
ListFilterCondition (dict) --
A list-based filter condition that includes or excludes values from a specified list.
Operator (string) --
The list operator to use, either INCLUDE to match values in the list or EXCLUDE to filter out values in the list.
Values (dict) --
The list of string values to include or exclude in the filter.
StaticValues (list) --
A list of static string values used for filtering.
(string) --
NumericFilterCondition (dict) --
A numeric-based filter condition within a filter operation.
ColumnName (string) --
The name of the numeric column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the numeric column.
Operator (string) --
The comparison operator to use, such as EQUALS, GREATER_THAN, LESS_THAN, or their variants.
Value (dict) --
The numeric value to compare against.
StaticValue (float) --
A static numeric value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the numeric column, filtering values between minimum and maximum numbers.
RangeMinimum (dict) --
The minimum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
RangeMaximum (dict) --
The maximum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
DateFilterCondition (dict) --
A date-based filter condition within a filter operation.
ColumnName (string) --
The name of the date column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the date column.
Operator (string) --
The comparison operator to use, such as BEFORE, BEFORE_OR_EQUALS_TO, AFTER, or AFTER_OR_EQUALS_TO.
Value (dict) --
The date value to compare against.
StaticValue (datetime) --
A static date value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the date column, filtering values between minimum and maximum dates.
RangeMinimum (dict) --
The minimum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
RangeMaximum (dict) --
The maximum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
CreateColumnsOperation (dict) --
An operation that creates calculated columns. Columns created in one such operation form a lexical closure.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for creating new calculated columns.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
Columns (list) --
Calculated columns to create.
(dict) --
A calculated column for a dataset.
ColumnName (string) --
Column name.
ColumnId (string) --
A unique ID to identify a calculated column. During a dataset update, if the column ID of a calculated column matches that of an existing calculated column, Quick Sight preserves the existing calculated column.
Expression (string) --
An expression that defines the calculated column.
RenameColumnOperation (dict) --
An operation that renames a column.
ColumnName (string) --
The name of the column to be renamed.
NewColumnName (string) --
The new name for the column.
CastColumnTypeOperation (dict) --
A transform operation that casts a column to a different type.
ColumnName (string) --
Column name.
NewColumnType (string) --
New column data type.
SubType (string) --
The sub data type of the new column. Sub types are only available for decimal columns that are part of a SPICE dataset.
Format (string) --
When casting a column from string to datetime type, you can supply a string in a format supported by Quick Sight to denote the source data format.
TagColumnOperation (dict) --
An operation that tags a column with additional information.
ColumnName (string) --
The column that this operation acts on.
Tags (list) --
The dataset column tag, currently only used for geospatial type tagging.
(dict) --
A tag for a column in a TagColumnOperation structure. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
ColumnGeographicRole (string) --
A geospatial role for a column.
ColumnDescription (dict) --
A description for a column.
Text (string) --
The text of a description for a column.
UntagColumnOperation (dict) --
A transform operation that removes tags associated with a column.
ColumnName (string) --
The column that this operation acts on.
TagNames (list) --
The column tags to remove from this column.
(string) --
OverrideDatasetParameterOperation (dict) --
A transform operation that overrides the dataset parameter values that are defined in another dataset.
ParameterName (string) --
The name of the parameter to be overridden with different values.
NewParameterName (string) --
The new name for the parameter.
NewDefaultValues (dict) --
The new default values for the parameter.
StringStaticValues (list) --
A list of static default values for a given string parameter.
(string) --
The default value for the string parameter.
DecimalStaticValues (list) --
A list of static default values for a given decimal parameter.
(float) --
The default value for the decimal parameter.
DateTimeStaticValues (list) --
A list of static default values for a given date time parameter.
(datetime) --
The default value for the date time parameter.
IntegerStaticValues (list) --
A list of static default values for a given integer parameter.
(integer) --
The default value for the integer parameter.
Source (dict) --
Source of this logical table.
JoinInstruction (dict) --
Specifies the result of a join of two logical tables.
LeftOperand (string) --
The operand on the left side of a join.
RightOperand (string) --
The operand on the right side of a join.
LeftJoinKeyProperties (dict) --
Join key properties of the left operand.
UniqueKey (boolean) --
A value that indicates that a row in a table is uniquely identified by the columns in a join key. This is used by Quick Sight to optimize query performance.
RightJoinKeyProperties (dict) --
Join key properties of the right operand.
UniqueKey (boolean) --
A value that indicates that a row in a table is uniquely identified by the columns in a join key. This is used by Quick Sight to optimize query performance.
Type (string) --
The type of join that it is.
OnClause (string) --
The join instructions provided in the ON clause of a join.
PhysicalTableId (string) --
Physical table ID.
DataSetArn (string) --
The Amazon Resource Number (ARN) of the parent dataset.
OutputColumns (list) --
The list of columns after all transforms. These columns are available in templates, analyses, and dashboards.
(dict) --
Output column.
Name (string) --
The display name of the column..
Id (string) --
A unique identifier for the output column.
Description (string) --
A description for a column.
Type (string) --
The data type of the column.
SubType (string) --
The sub data type of the column.
ImportMode (string) --
A value that indicates whether you want to import the data into SPICE.
ConsumedSpiceCapacityInBytes (integer) --
The amount of SPICE capacity used by this dataset. This is 0 if the dataset isn't imported into SPICE.
ColumnGroups (list) --
Groupings of columns that work together in certain Quick Sight features. Currently, only geospatial hierarchy is supported.
(dict) --
Groupings of columns that work together in certain Quick Sight features. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
GeoSpatialColumnGroup (dict) --
Geospatial column group that denotes a hierarchy.
Name (string) --
A display name for the hierarchy.
CountryCode (string) --
Country code.
Columns (list) --
Columns in this hierarchy.
(string) --
FieldFolders (dict) --
The folder that contains fields and nested subfolders for your dataset.
(string) --
(dict) --
A FieldFolder element is a folder that contains fields and nested subfolders.
description (string) --
The description for a field folder.
columns (list) --
A folder has a list of columns. A column can only be in one folder.
(string) --
RowLevelPermissionDataSet (dict) --
The row-level security configuration for the dataset.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) --
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) --
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
RowLevelPermissionTagConfiguration (dict) --
The element you can use to define tags for row-level security.
Status (string) --
The status of row-level security tags. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
TagRules (list) --
A set of rules associated with row-level security, such as the tag names and columns that they are assigned to.
(dict) --
A set of rules associated with a tag.
TagKey (string) --
The unique key for a tag.
ColumnName (string) --
The column name that a tag key is assigned to.
TagMultiValueDelimiter (string) --
A string that you want to use to delimit the values when you pass the values at run time. For example, you can delimit the values with a comma.
MatchAllValue (string) --
A string that you want to use to filter by all the values in a column in the dataset and don’t want to list the values one by one. For example, you can use an asterisk as your match all value.
TagRuleConfigurations (list) --
A list of tag configuration rules to apply to a dataset. All tag configurations have the OR condition. Tags within each tile will be joined (AND). At least one rule in this structure must have all tag values assigned to it to apply Row-level security (RLS) to the dataset.
(list) --
(string) --
ColumnLevelPermissionRules (list) --
A set of one or more definitions of a ``ColumnLevelPermissionRule ``.
(dict) --
A rule defined to grant access on one or more restricted columns. Each dataset can have multiple rules. To create a restricted column, you add it to one or more rules. Each rule must contain at least one column and at least one user or group. To be able to see a restricted column, a user or group needs to be added to a rule for that column.
Principals (list) --
An array of Amazon Resource Names (ARNs) for Quick Sight users or groups.
(string) --
ColumnNames (list) --
An array of column names.
(string) --
DataSetUsageConfiguration (dict) --
The usage configuration to apply to child datasets that reference this dataset as a source.
DisableUseAsDirectQuerySource (boolean) --
An option that controls whether a child dataset of a direct query can use this dataset as a source.
DisableUseAsImportedSource (boolean) --
An option that controls whether a child dataset that's stored in Quick Sight can use this dataset as a source.
DatasetParameters (list) --
The parameters that are declared in a dataset.
(dict) --
A parameter that is created in a dataset. The parameter can be a string, integer, decimal, or datetime data type.
StringDatasetParameter (dict) --
A string parameter that is created in the dataset.
Id (string) --
An identifier for the string parameter that is created in the dataset.
Name (string) --
The name of the string parameter that is created in the dataset.
ValueType (string) --
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given string dataset parameter type. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given string parameter.
(string) --
The default value for the string parameter.
DecimalDatasetParameter (dict) --
A decimal parameter that is created in the dataset.
Id (string) --
An identifier for the decimal parameter created in the dataset.
Name (string) --
The name of the decimal parameter that is created in the dataset.
ValueType (string) --
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given decimal parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given decimal parameter.
(float) --
The default value for the decimal parameter.
IntegerDatasetParameter (dict) --
An integer parameter that is created in the dataset.
Id (string) --
An identifier for the integer parameter created in the dataset.
Name (string) --
The name of the integer parameter that is created in the dataset.
ValueType (string) --
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given integer parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given integer parameter.
(integer) --
The default value for the integer parameter.
DateTimeDatasetParameter (dict) --
A date time parameter that is created in the dataset.
Id (string) --
An identifier for the parameter that is created in the dataset.
Name (string) --
The name of the date time parameter that is created in the dataset.
ValueType (string) --
The value type of the dataset parameter. Valid values are single value or multi value.
TimeGranularity (string) --
The time granularity of the date time parameter.
DefaultValues (dict) --
A list of default values for a given date time parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given date time parameter.
(datetime) --
The default value for the date time parameter.
PerformanceConfiguration (dict) --
The performance optimization configuration of a dataset.
UniqueKeys (list) --
A UniqueKey configuration.
(dict) --
A UniqueKey configuration that references a dataset column.
ColumnNames (list) --
The name of the column that is referenced in the UniqueKey configuration.
(string) --
UseAs (string) --
The usage of the dataset.
DataPrepConfiguration (dict) --
The data preparation configuration associated with this dataset.
SourceTableMap (dict) --
A map of source tables that provide information about underlying sources.
(string) --
(dict) --
A source table that provides initial data from either a physical table or parent dataset.
PhysicalTableId (string) --
The identifier of the physical table that serves as the data source.
DataSet (dict) --
A parent dataset that serves as the data source instead of a physical table.
DataSetArn (string) --
The Amazon Resource Name (ARN) of the parent dataset.
InputColumns (list) --
The list of input columns available from the parent dataset.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) --
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) --
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
TransformStepMap (dict) --
A map of transformation steps that process the data.
(string) --
(dict) --
A step in data preparation that performs a specific operation on the data.
ImportTableStep (dict) --
A transform step that brings data from a source table.
Alias (string) --
Alias for this operation.
Source (dict) --
The source configuration that specifies which source table to import and any column mappings.
SourceTableId (string) --
The identifier of the source table to import data from.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers during the import.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
ProjectStep (dict) --
A transform operation that projects columns. Operations that come after a projection can only refer to projected columns.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for column projection.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
ProjectedColumns (list) --
Projected columns.
(string) --
FiltersStep (dict) --
A transform step that applies filter conditions.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for filtering.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
FilterOperations (list) --
The list of filter operations to apply.
(dict) --
A transform operation that filters rows based on a condition.
ConditionExpression (string) --
An expression that must evaluate to a Boolean value. Rows for which the expression evaluates to true are kept in the dataset.
StringFilterCondition (dict) --
A string-based filter condition within a filter operation.
ColumnName (string) --
The name of the string column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the string column.
Operator (string) --
The comparison operator to use, such as EQUALS, CONTAINS, STARTS_WITH, ENDS_WITH, or their negations.
Value (dict) --
The string value to compare against.
StaticValue (string) --
A static string value used for filtering.
ListFilterCondition (dict) --
A list-based filter condition that includes or excludes values from a specified list.
Operator (string) --
The list operator to use, either INCLUDE to match values in the list or EXCLUDE to filter out values in the list.
Values (dict) --
The list of string values to include or exclude in the filter.
StaticValues (list) --
A list of static string values used for filtering.
(string) --
NumericFilterCondition (dict) --
A numeric-based filter condition within a filter operation.
ColumnName (string) --
The name of the numeric column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the numeric column.
Operator (string) --
The comparison operator to use, such as EQUALS, GREATER_THAN, LESS_THAN, or their variants.
Value (dict) --
The numeric value to compare against.
StaticValue (float) --
A static numeric value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the numeric column, filtering values between minimum and maximum numbers.
RangeMinimum (dict) --
The minimum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
RangeMaximum (dict) --
The maximum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
DateFilterCondition (dict) --
A date-based filter condition within a filter operation.
ColumnName (string) --
The name of the date column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the date column.
Operator (string) --
The comparison operator to use, such as BEFORE, BEFORE_OR_EQUALS_TO, AFTER, or AFTER_OR_EQUALS_TO.
Value (dict) --
The date value to compare against.
StaticValue (datetime) --
A static date value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the date column, filtering values between minimum and maximum dates.
RangeMinimum (dict) --
The minimum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
RangeMaximum (dict) --
The maximum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
CreateColumnsStep (dict) --
A transform operation that creates calculated columns. Columns created in one such operation form a lexical closure.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for creating new calculated columns.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
Columns (list) --
Calculated columns to create.
(dict) --
A calculated column for a dataset.
ColumnName (string) --
Column name.
ColumnId (string) --
A unique ID to identify a calculated column. During a dataset update, if the column ID of a calculated column matches that of an existing calculated column, Quick Sight preserves the existing calculated column.
Expression (string) --
An expression that defines the calculated column.
RenameColumnsStep (dict) --
A transform step that changes the names of one or more columns.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for column renaming.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
RenameColumnOperations (list) --
The list of column rename operations to perform, specifying old and new column names.
(dict) --
A transform operation that renames a column.
ColumnName (string) --
The name of the column to be renamed.
NewColumnName (string) --
The new name for the column.
CastColumnTypesStep (dict) --
A transform step that changes the data types of one or more columns.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for the type casting.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
CastColumnTypeOperations (list) --
The list of column type casting operations to perform.
(dict) --
A transform operation that casts a column to a different type.
ColumnName (string) --
Column name.
NewColumnType (string) --
New column data type.
SubType (string) --
The sub data type of the new column. Sub types are only available for decimal columns that are part of a SPICE dataset.
Format (string) --
When casting a column from string to datetime type, you can supply a string in a format supported by Quick Sight to denote the source data format.
JoinStep (dict) --
A transform step that combines data from two sources based on specified join conditions.
Alias (string) --
Alias for this operation.
LeftOperand (dict) --
The left operand for the join operation.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
RightOperand (dict) --
The right operand for the join operation.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
Type (string) --
The type of join to perform, such as INNER, LEFT, RIGHT, or OUTER.
OnClause (string) --
The join condition that specifies how to match rows between the left and right operands.
LeftOperandProperties (dict) --
Properties that control how the left operand's columns are handled in the join result.
OutputColumnNameOverrides (list) --
A list of column name overrides to apply to the join operand's output columns.
(dict) --
Specifies a mapping to override the name of an output column from a transform operation.
SourceColumnName (string) --
The original name of the column from the source transform operation.
OutputColumnName (string) --
The new name to assign to the column in the output.
RightOperandProperties (dict) --
Properties that control how the right operand's columns are handled in the join result.
OutputColumnNameOverrides (list) --
A list of column name overrides to apply to the join operand's output columns.
(dict) --
Specifies a mapping to override the name of an output column from a transform operation.
SourceColumnName (string) --
The original name of the column from the source transform operation.
OutputColumnName (string) --
The new name to assign to the column in the output.
AggregateStep (dict) --
A transform step that groups data and applies aggregation functions to calculate summary values.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for the aggregation.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
GroupByColumnNames (list) --
The list of column names to group by when performing the aggregation. Rows with the same values in these columns will be grouped together.
(string) --
Aggregations (list) --
The list of aggregation functions to apply to the grouped data, such as SUM, COUNT, or AVERAGE.
(dict) --
Defines an aggregation function to be applied to grouped data, creating a new column with the calculated result.
AggregationFunction (dict) --
The aggregation function to apply, such as SUM, COUNT, AVERAGE, MIN, MAX
SimpleAggregation (dict) --
A simple aggregation function such as SUM, COUNT, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
InputColumnName (string) --
The name of the column on which to perform the aggregation function.
FunctionType (string) --
The type of aggregation function to perform, such as COUNT, SUM, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
ListAggregation (dict) --
A list aggregation function that concatenates values from multiple rows into a single delimited string.
InputColumnName (string) --
The name of the column containing values to be concatenated.
Separator (string) --
The string used to separate values in the concatenated result.
Distinct (boolean) --
Whether to include only distinct values in the concatenated result, removing duplicates.
NewColumnName (string) --
The name for the new column that will contain the aggregated values.
NewColumnId (string) --
A unique identifier for the new column that will contain the aggregated values.
PivotStep (dict) --
A transform step that converts row values into columns to reshape the data structure.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for pivoting.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
GroupByColumnNames (list) --
The list of column names to group by when performing the pivot operation.
(string) --
ValueColumnConfiguration (dict) --
Configuration for how to aggregate values when multiple rows map to the same pivoted column.
AggregationFunction (dict) --
The aggregation function to apply when multiple values map to the same pivoted cell.
SimpleAggregation (dict) --
A simple aggregation function such as SUM, COUNT, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
InputColumnName (string) --
The name of the column on which to perform the aggregation function.
FunctionType (string) --
The type of aggregation function to perform, such as COUNT, SUM, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
ListAggregation (dict) --
A list aggregation function that concatenates values from multiple rows into a single delimited string.
InputColumnName (string) --
The name of the column containing values to be concatenated.
Separator (string) --
The string used to separate values in the concatenated result.
Distinct (boolean) --
Whether to include only distinct values in the concatenated result, removing duplicates.
PivotConfiguration (dict) --
Configuration that specifies which labels to pivot and how to structure the resulting columns.
LabelColumnName (string) --
The name of the column that contains the labels to be pivoted into separate columns.
PivotedLabels (list) --
The list of specific label values to pivot into separate columns.
(dict) --
Specifies a label value to be pivoted into a separate column, including the new column name and identifier.
LabelName (string) --
The label value from the source data to be pivoted.
NewColumnName (string) --
The name for the new column created from this pivoted label.
NewColumnId (string) --
A unique identifier for the new column created from this pivoted label.
UnpivotStep (dict) --
A transform step that converts columns into rows to normalize the data structure.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for unpivoting.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
ColumnsToUnpivot (list) --
The list of columns to unpivot from the source data.
(dict) --
Specifies a column to be unpivoted, transforming it from a column into rows with associated values.
ColumnName (string) --
The name of the column to unpivot from the source data.
NewValue (string) --
The value to assign to this column in the unpivoted result, typically the column name or a descriptive label.
UnpivotedLabelColumnName (string) --
The name for the new column that will contain the unpivoted column names.
UnpivotedLabelColumnId (string) --
A unique identifier for the new column that will contain the unpivoted column names.
UnpivotedValueColumnName (string) --
The name for the new column that will contain the unpivoted values.
UnpivotedValueColumnId (string) --
A unique identifier for the new column that will contain the unpivoted values.
AppendStep (dict) --
A transform step that combines rows from multiple sources by stacking them vertically.
Alias (string) --
Alias for this operation.
FirstSource (dict) --
The first data source to be included in the append operation.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
SecondSource (dict) --
The second data source to be appended to the first source.
TransformOperationId (string) --
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) --
Source column ID.
TargetColumnId (string) --
Target column ID.
AppendedColumns (list) --
The list of columns to include in the appended result, mapping columns from both sources.
(dict) --
Represents a column that will be included in the result of an append operation, combining data from multiple sources.
ColumnName (string) --
The name of the column to include in the appended result.
NewColumnId (string) --
A unique identifier for the column in the appended result.
DestinationTableMap (dict) --
A map of destination tables that receive the final prepared data.
(string) --
(dict) --
Defines a destination table in data preparation that receives the final transformed data.
Alias (string) --
Alias for the destination table.
Source (dict) --
The source configuration that specifies which transform operation provides data to this destination table.
TransformOperationId (string) --
The identifier of the transform operation that provides data to the destination table.
SemanticModelConfiguration (dict) --
The semantic model configuration associated with this dataset.
TableMap (dict) --
A map of semantic tables that define the analytical structure.
(string) --
(dict) --
A semantic table that represents the final analytical structure of the data.
Alias (string) --
Alias for the semantic table.
DestinationTableId (string) --
The identifier of the destination table from data preparation that provides data to this semantic table.
RowLevelPermissionConfiguration (dict) --
Configuration for row level security that control data access for this semantic table.
TagConfiguration (dict) --
The configuration of tags on a dataset to set row-level security.
Status (string) --
The status of row-level security tags. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
TagRules (list) --
A set of rules associated with row-level security, such as the tag names and columns that they are assigned to.
(dict) --
A set of rules associated with a tag.
TagKey (string) --
The unique key for a tag.
ColumnName (string) --
The column name that a tag key is assigned to.
TagMultiValueDelimiter (string) --
A string that you want to use to delimit the values when you pass the values at run time. For example, you can delimit the values with a comma.
MatchAllValue (string) --
A string that you want to use to filter by all the values in a column in the dataset and don’t want to list the values one by one. For example, you can use an asterisk as your match all value.
TagRuleConfigurations (list) --
A list of tag configuration rules to apply to a dataset. All tag configurations have the OR condition. Tags within each tile will be joined (AND). At least one rule in this structure must have all tag values assigned to it to apply Row-level security (RLS) to the dataset.
(list) --
(string) --
RowLevelPermissionDataSet (dict) --
Information about a dataset that contains permissions for row-level security (RLS). The permissions dataset maps fields to users or groups. For more information, see Using Row-Level Security (RLS) to Restrict Access to a Dataset in the Quick Sight User Guide.
The option to deny permissions by setting PermissionPolicy to DENY_ACCESS is not supported for new RLS datasets.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) --
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) --
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
RequestId (string) --
The Amazon Web Services request ID for this operation.
Status (integer) --
The HTTP status of the request.
{'DataSetSummaries': {'RowLevelPermissionDataSetMap': {'string': {'Arn': 'string',
'FormatVersion': 'VERSION_1 '
'| '
'VERSION_2',
'Namespace': 'string',
'PermissionPolicy': 'GRANT_ACCESS '
'| '
'DENY_ACCESS',
'Status': 'ENABLED '
'| '
'DISABLED'}}}}
Lists all of the datasets belonging to the current Amazon Web Services account in an Amazon Web Services Region.
The permissions resource is arn:aws:quicksight:region:aws-account-id:dataset/*.
See also: AWS API Documentation
Request Syntax
client.list_data_sets(
AwsAccountId='string',
NextToken='string',
MaxResults=123
)
string
[REQUIRED]
The Amazon Web Services account ID.
string
The token for the next set of results, or null if there are no more results.
integer
The maximum number of results to be returned per request.
dict
Response Syntax
{
'DataSetSummaries': [
{
'Arn': 'string',
'DataSetId': 'string',
'Name': 'string',
'CreatedTime': datetime(2015, 1, 1),
'LastUpdatedTime': datetime(2015, 1, 1),
'ImportMode': 'SPICE'|'DIRECT_QUERY',
'RowLevelPermissionDataSet': {
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
},
'RowLevelPermissionDataSetMap': {
'string': {
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
}
},
'RowLevelPermissionTagConfigurationApplied': True|False,
'ColumnLevelPermissionRulesApplied': True|False,
'UseAs': 'RLS_RULES'
},
],
'NextToken': 'string',
'RequestId': 'string',
'Status': 123
}
Response Structure
(dict) --
DataSetSummaries (list) --
The list of dataset summaries.
(dict) --
Dataset summary.
Arn (string) --
The Amazon Resource Name (ARN) of the dataset.
DataSetId (string) --
The ID of the dataset.
Name (string) --
A display name for the dataset.
CreatedTime (datetime) --
The time that this dataset was created.
LastUpdatedTime (datetime) --
The last time that this dataset was updated.
ImportMode (string) --
A value that indicates whether you want to import the data into SPICE.
RowLevelPermissionDataSet (dict) --
The row-level security configuration for the dataset in the legacy data preparation experience.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) --
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) --
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
RowLevelPermissionDataSetMap (dict) --
The row-level security configuration for the dataset in the new data preparation experience.
(string) --
(dict) --
Information about a dataset that contains permissions for row-level security (RLS). The permissions dataset maps fields to users or groups. For more information, see Using Row-Level Security (RLS) to Restrict Access to a Dataset in the Quick Sight User Guide.
The option to deny permissions by setting PermissionPolicy to DENY_ACCESS is not supported for new RLS datasets.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) --
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) --
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
RowLevelPermissionTagConfigurationApplied (boolean) --
Whether or not the row level permission tags are applied.
ColumnLevelPermissionRulesApplied (boolean) --
A value that indicates if the dataset has column level permission configured.
UseAs (string) --
The usage of the dataset.
NextToken (string) --
The token for the next set of results, or null if there are no more results.
RequestId (string) --
The Amazon Web Services request ID for this operation.
Status (integer) --
The HTTP status of the request.
{'DataSetSummaries': {'RowLevelPermissionDataSetMap': {'string': {'Arn': 'string',
'FormatVersion': 'VERSION_1 '
'| '
'VERSION_2',
'Namespace': 'string',
'PermissionPolicy': 'GRANT_ACCESS '
'| '
'DENY_ACCESS',
'Status': 'ENABLED '
'| '
'DISABLED'}}}}
Use the SearchDataSets operation to search for datasets that belong to an account.
See also: AWS API Documentation
Request Syntax
client.search_data_sets(
AwsAccountId='string',
Filters=[
{
'Operator': 'StringEquals'|'StringLike',
'Name': 'QUICKSIGHT_VIEWER_OR_OWNER'|'QUICKSIGHT_OWNER'|'DIRECT_QUICKSIGHT_VIEWER_OR_OWNER'|'DIRECT_QUICKSIGHT_OWNER'|'DIRECT_QUICKSIGHT_SOLE_OWNER'|'DATASET_NAME',
'Value': 'string'
},
],
NextToken='string',
MaxResults=123
)
string
[REQUIRED]
The Amazon Web Services account ID.
list
[REQUIRED]
The filters to apply to the search.
(dict) --
A filter that you apply when searching for datasets.
Operator (string) -- [REQUIRED]
The comparison operator that you want to use as a filter, for example "Operator": "StringEquals". Valid values are "StringEquals" and "StringLike".
If you set the operator value to "StringEquals", you need to provide an ownership related filter in the "NAME" field and the arn of the user or group whose datasets you want to search in the "Value" field. For example, "Name":"QUICKSIGHT_OWNER", "Operator": "StringEquals", "Value": "arn:aws:quicksight:us-east- 1:1:user/default/UserName1".
If you set the value to "StringLike", you need to provide the name of the datasets you are searching for. For example, "Name":"DATASET_NAME", "Operator": "StringLike", "Value": "Test". The "StringLike" operator only supports the NAME value DATASET_NAME.
Name (string) -- [REQUIRED]
The name of the value that you want to use as a filter, for example, "Name": "QUICKSIGHT_OWNER".
Valid values are defined as follows:
QUICKSIGHT_VIEWER_OR_OWNER: Provide an ARN of a user or group, and any datasets with that ARN listed as one of the dataset owners or viewers are returned. Implicit permissions from folders or groups are considered.
QUICKSIGHT_OWNER: Provide an ARN of a user or group, and any datasets with that ARN listed as one of the owners of the dataset are returned. Implicit permissions from folders or groups are considered.
DIRECT_QUICKSIGHT_SOLE_OWNER: Provide an ARN of a user or group, and any datasets with that ARN listed as the only owner of the dataset are returned. Implicit permissions from folders or groups are not considered.
DIRECT_QUICKSIGHT_OWNER: Provide an ARN of a user or group, and any datasets with that ARN listed as one of the owners if the dataset are returned. Implicit permissions from folders or groups are not considered.
DIRECT_QUICKSIGHT_VIEWER_OR_OWNER: Provide an ARN of a user or group, and any datasets with that ARN listed as one of the owners or viewers of the dataset are returned. Implicit permissions from folders or groups are not considered.
DATASET_NAME: Any datasets whose names have a substring match to this value will be returned.
Value (string) -- [REQUIRED]
The value of the named item, in this case QUICKSIGHT_OWNER, that you want to use as a filter, for example, "Value": "arn:aws:quicksight:us-east-1:1:user/default/UserName1".
string
A pagination token that can be used in a subsequent request.
integer
The maximum number of results to be returned per request.
dict
Response Syntax
{
'DataSetSummaries': [
{
'Arn': 'string',
'DataSetId': 'string',
'Name': 'string',
'CreatedTime': datetime(2015, 1, 1),
'LastUpdatedTime': datetime(2015, 1, 1),
'ImportMode': 'SPICE'|'DIRECT_QUERY',
'RowLevelPermissionDataSet': {
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
},
'RowLevelPermissionDataSetMap': {
'string': {
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
}
},
'RowLevelPermissionTagConfigurationApplied': True|False,
'ColumnLevelPermissionRulesApplied': True|False,
'UseAs': 'RLS_RULES'
},
],
'NextToken': 'string',
'Status': 123,
'RequestId': 'string'
}
Response Structure
(dict) --
DataSetSummaries (list) --
A DataSetSummaries object that returns a summary of a dataset.
(dict) --
Dataset summary.
Arn (string) --
The Amazon Resource Name (ARN) of the dataset.
DataSetId (string) --
The ID of the dataset.
Name (string) --
A display name for the dataset.
CreatedTime (datetime) --
The time that this dataset was created.
LastUpdatedTime (datetime) --
The last time that this dataset was updated.
ImportMode (string) --
A value that indicates whether you want to import the data into SPICE.
RowLevelPermissionDataSet (dict) --
The row-level security configuration for the dataset in the legacy data preparation experience.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) --
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) --
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
RowLevelPermissionDataSetMap (dict) --
The row-level security configuration for the dataset in the new data preparation experience.
(string) --
(dict) --
Information about a dataset that contains permissions for row-level security (RLS). The permissions dataset maps fields to users or groups. For more information, see Using Row-Level Security (RLS) to Restrict Access to a Dataset in the Quick Sight User Guide.
The option to deny permissions by setting PermissionPolicy to DENY_ACCESS is not supported for new RLS datasets.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) --
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) --
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
RowLevelPermissionTagConfigurationApplied (boolean) --
Whether or not the row level permission tags are applied.
ColumnLevelPermissionRulesApplied (boolean) --
A value that indicates if the dataset has column level permission configured.
UseAs (string) --
The usage of the dataset.
NextToken (string) --
A pagination token that can be used in a subsequent request.
Status (integer) --
The HTTP status of the request.
RequestId (string) --
The Amazon Web Services request ID for this operation.
{'DataPrepConfiguration': {'DestinationTableMap': {'string': {'Alias': 'string',
'Source': {'TransformOperationId': 'string'}}},
'SourceTableMap': {'string': {'DataSet': {'DataSetArn': 'string',
'InputColumns': [{'Id': 'string',
'Name': 'string',
'SubType': 'FLOAT '
'| '
'FIXED',
'Type': 'STRING '
'| '
'INTEGER '
'| '
'DECIMAL '
'| '
'DATETIME '
'| '
'BIT '
'| '
'BOOLEAN '
'| '
'JSON'}]},
'PhysicalTableId': 'string'}},
'TransformStepMap': {'string': {'AggregateStep': {'Aggregations': [{'AggregationFunction': {'ListAggregation': {'Distinct': 'boolean',
'InputColumnName': 'string',
'Separator': 'string'},
'SimpleAggregation': {'FunctionType': 'COUNT '
'| '
'DISTINCT_COUNT '
'| '
'SUM '
'| '
'AVERAGE '
'| '
'MAX '
'| '
'MIN',
'InputColumnName': 'string'}},
'NewColumnId': 'string',
'NewColumnName': 'string'}],
'Alias': 'string',
'GroupByColumnNames': ['string'],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'AppendStep': {'Alias': 'string',
'AppendedColumns': [{'ColumnName': 'string',
'NewColumnId': 'string'}],
'FirstSource': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'SecondSource': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'CastColumnTypesStep': {'Alias': 'string',
'CastColumnTypeOperations': [{'ColumnName': 'string',
'Format': 'string',
'NewColumnType': 'STRING '
'| '
'INTEGER '
'| '
'DECIMAL '
'| '
'DATETIME',
'SubType': 'FLOAT '
'| '
'FIXED'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'CreateColumnsStep': {'Alias': 'string',
'Columns': [{'ColumnId': 'string',
'ColumnName': 'string',
'Expression': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'FiltersStep': {'Alias': 'string',
'FilterOperations': [{'ConditionExpression': 'string',
'DateFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'BEFORE '
'| '
'BEFORE_OR_EQUALS_TO '
'| '
'AFTER '
'| '
'AFTER_OR_EQUALS_TO',
'Value': {'StaticValue': 'timestamp'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'timestamp'},
'RangeMinimum': {'StaticValue': 'timestamp'}}},
'NumericFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'GREATER_THAN '
'| '
'GREATER_THAN_OR_EQUALS_TO '
'| '
'LESS_THAN '
'| '
'LESS_THAN_OR_EQUALS_TO',
'Value': {'StaticValue': 'double'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'double'},
'RangeMinimum': {'StaticValue': 'double'}}},
'StringFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'CONTAINS '
'| '
'DOES_NOT_CONTAIN '
'| '
'STARTS_WITH '
'| '
'ENDS_WITH',
'Value': {'StaticValue': 'string'}},
'ListFilterCondition': {'Operator': 'INCLUDE '
'| '
'EXCLUDE',
'Values': {'StaticValues': ['string']}}}}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'ImportTableStep': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'SourceTableId': 'string'}},
'JoinStep': {'Alias': 'string',
'LeftOperand': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'LeftOperandProperties': {'OutputColumnNameOverrides': [{'OutputColumnName': 'string',
'SourceColumnName': 'string'}]},
'OnClause': 'string',
'RightOperand': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'RightOperandProperties': {'OutputColumnNameOverrides': [{'OutputColumnName': 'string',
'SourceColumnName': 'string'}]},
'Type': 'INNER '
'| '
'OUTER '
'| '
'LEFT '
'| '
'RIGHT'},
'PivotStep': {'Alias': 'string',
'GroupByColumnNames': ['string'],
'PivotConfiguration': {'LabelColumnName': 'string',
'PivotedLabels': [{'LabelName': 'string',
'NewColumnId': 'string',
'NewColumnName': 'string'}]},
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'ValueColumnConfiguration': {'AggregationFunction': {'ListAggregation': {'Distinct': 'boolean',
'InputColumnName': 'string',
'Separator': 'string'},
'SimpleAggregation': {'FunctionType': 'COUNT '
'| '
'DISTINCT_COUNT '
'| '
'SUM '
'| '
'AVERAGE '
'| '
'MAX '
'| '
'MIN',
'InputColumnName': 'string'}}}},
'ProjectStep': {'Alias': 'string',
'ProjectedColumns': ['string'],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'RenameColumnsStep': {'Alias': 'string',
'RenameColumnOperations': [{'ColumnName': 'string',
'NewColumnName': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'UnpivotStep': {'Alias': 'string',
'ColumnsToUnpivot': [{'ColumnName': 'string',
'NewValue': 'string'}],
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'},
'UnpivotedLabelColumnId': 'string',
'UnpivotedLabelColumnName': 'string',
'UnpivotedValueColumnId': 'string',
'UnpivotedValueColumnName': 'string'}}}},
'LogicalTableMap': {'DataTransforms': {'CreateColumnsOperation': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}},
'FilterOperation': {'DateFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'BEFORE '
'| '
'BEFORE_OR_EQUALS_TO '
'| '
'AFTER '
'| '
'AFTER_OR_EQUALS_TO',
'Value': {'StaticValue': 'timestamp'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'timestamp'},
'RangeMinimum': {'StaticValue': 'timestamp'}}},
'NumericFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'GREATER_THAN '
'| '
'GREATER_THAN_OR_EQUALS_TO '
'| '
'LESS_THAN '
'| '
'LESS_THAN_OR_EQUALS_TO',
'Value': {'StaticValue': 'double'}},
'RangeFilterCondition': {'IncludeMaximum': 'boolean',
'IncludeMinimum': 'boolean',
'RangeMaximum': {'StaticValue': 'double'},
'RangeMinimum': {'StaticValue': 'double'}}},
'StringFilterCondition': {'ColumnName': 'string',
'ComparisonFilterCondition': {'Operator': 'EQUALS '
'| '
'DOES_NOT_EQUAL '
'| '
'CONTAINS '
'| '
'DOES_NOT_CONTAIN '
'| '
'STARTS_WITH '
'| '
'ENDS_WITH',
'Value': {'StaticValue': 'string'}},
'ListFilterCondition': {'Operator': 'INCLUDE '
'| '
'EXCLUDE',
'Values': {'StaticValues': ['string']}}}},
'ProjectOperation': {'Alias': 'string',
'Source': {'ColumnIdMappings': [{'SourceColumnId': 'string',
'TargetColumnId': 'string'}],
'TransformOperationId': 'string'}}}},
'PhysicalTableMap': {'CustomSql': {'Columns': {'Id': 'string'}},
'RelationalTable': {'InputColumns': {'Id': 'string'}},
'S3Source': {'InputColumns': {'Id': 'string'},
'UploadSettings': {'CustomCellAddressRange': 'string'}},
'SaaSTable': {'DataSourceArn': 'string',
'InputColumns': [{'Id': 'string',
'Name': 'string',
'SubType': 'FLOAT | '
'FIXED',
'Type': 'STRING | '
'INTEGER | '
'DECIMAL | '
'DATETIME | BIT '
'| BOOLEAN | '
'JSON'}],
'TablePath': [{'Id': 'string',
'Name': 'string'}]}},
'SemanticModelConfiguration': {'TableMap': {'string': {'Alias': 'string',
'DestinationTableId': 'string',
'RowLevelPermissionConfiguration': {'RowLevelPermissionDataSet': {'Arn': 'string',
'FormatVersion': 'VERSION_1 '
'| '
'VERSION_2',
'Namespace': 'string',
'PermissionPolicy': 'GRANT_ACCESS '
'| '
'DENY_ACCESS',
'Status': 'ENABLED '
'| '
'DISABLED'},
'TagConfiguration': {'Status': 'ENABLED '
'| '
'DISABLED',
'TagRuleConfigurations': [['string']],
'TagRules': [{'ColumnName': 'string',
'MatchAllValue': 'string',
'TagKey': 'string',
'TagMultiValueDelimiter': 'string'}]}}}}}}
Updates a dataset. This operation doesn't support datasets that include uploaded files as a source. Partial updates are not supported by this operation.
See also: AWS API Documentation
Request Syntax
client.update_data_set(
AwsAccountId='string',
DataSetId='string',
Name='string',
PhysicalTableMap={
'string': {
'RelationalTable': {
'DataSourceArn': 'string',
'Catalog': 'string',
'Schema': 'string',
'Name': 'string',
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'CustomSql': {
'DataSourceArn': 'string',
'Name': 'string',
'SqlQuery': 'string',
'Columns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'S3Source': {
'DataSourceArn': 'string',
'UploadSettings': {
'Format': 'CSV'|'TSV'|'CLF'|'ELF'|'XLSX'|'JSON',
'StartFromRow': 123,
'ContainsHeader': True|False,
'TextQualifier': 'DOUBLE_QUOTE'|'SINGLE_QUOTE',
'Delimiter': 'string',
'CustomCellAddressRange': 'string'
},
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
},
'SaaSTable': {
'DataSourceArn': 'string',
'TablePath': [
{
'Name': 'string',
'Id': 'string'
},
],
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
}
}
},
LogicalTableMap={
'string': {
'Alias': 'string',
'DataTransforms': [
{
'ProjectOperation': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ProjectedColumns': [
'string',
]
},
'FilterOperation': {
'ConditionExpression': 'string',
'StringFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'CONTAINS'|'DOES_NOT_CONTAIN'|'STARTS_WITH'|'ENDS_WITH',
'Value': {
'StaticValue': 'string'
}
},
'ListFilterCondition': {
'Operator': 'INCLUDE'|'EXCLUDE',
'Values': {
'StaticValues': [
'string',
]
}
}
},
'NumericFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'GREATER_THAN'|'GREATER_THAN_OR_EQUALS_TO'|'LESS_THAN'|'LESS_THAN_OR_EQUALS_TO',
'Value': {
'StaticValue': 123.0
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': 123.0
},
'RangeMaximum': {
'StaticValue': 123.0
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
},
'DateFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'BEFORE'|'BEFORE_OR_EQUALS_TO'|'AFTER'|'AFTER_OR_EQUALS_TO',
'Value': {
'StaticValue': datetime(2015, 1, 1)
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': datetime(2015, 1, 1)
},
'RangeMaximum': {
'StaticValue': datetime(2015, 1, 1)
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
}
},
'CreateColumnsOperation': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Columns': [
{
'ColumnName': 'string',
'ColumnId': 'string',
'Expression': 'string'
},
]
},
'RenameColumnOperation': {
'ColumnName': 'string',
'NewColumnName': 'string'
},
'CastColumnTypeOperation': {
'ColumnName': 'string',
'NewColumnType': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME',
'SubType': 'FLOAT'|'FIXED',
'Format': 'string'
},
'TagColumnOperation': {
'ColumnName': 'string',
'Tags': [
{
'ColumnGeographicRole': 'COUNTRY'|'STATE'|'COUNTY'|'CITY'|'POSTCODE'|'LONGITUDE'|'LATITUDE',
'ColumnDescription': {
'Text': 'string'
}
},
]
},
'UntagColumnOperation': {
'ColumnName': 'string',
'TagNames': [
'COLUMN_GEOGRAPHIC_ROLE'|'COLUMN_DESCRIPTION',
]
},
'OverrideDatasetParameterOperation': {
'ParameterName': 'string',
'NewParameterName': 'string',
'NewDefaultValues': {
'StringStaticValues': [
'string',
],
'DecimalStaticValues': [
123.0,
],
'DateTimeStaticValues': [
datetime(2015, 1, 1),
],
'IntegerStaticValues': [
123,
]
}
}
},
],
'Source': {
'JoinInstruction': {
'LeftOperand': 'string',
'RightOperand': 'string',
'LeftJoinKeyProperties': {
'UniqueKey': True|False
},
'RightJoinKeyProperties': {
'UniqueKey': True|False
},
'Type': 'INNER'|'OUTER'|'LEFT'|'RIGHT',
'OnClause': 'string'
},
'PhysicalTableId': 'string',
'DataSetArn': 'string'
}
}
},
ImportMode='SPICE'|'DIRECT_QUERY',
ColumnGroups=[
{
'GeoSpatialColumnGroup': {
'Name': 'string',
'CountryCode': 'US',
'Columns': [
'string',
]
}
},
],
FieldFolders={
'string': {
'description': 'string',
'columns': [
'string',
]
}
},
RowLevelPermissionDataSet={
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
},
RowLevelPermissionTagConfiguration={
'Status': 'ENABLED'|'DISABLED',
'TagRules': [
{
'TagKey': 'string',
'ColumnName': 'string',
'TagMultiValueDelimiter': 'string',
'MatchAllValue': 'string'
},
],
'TagRuleConfigurations': [
[
'string',
],
]
},
ColumnLevelPermissionRules=[
{
'Principals': [
'string',
],
'ColumnNames': [
'string',
]
},
],
DataSetUsageConfiguration={
'DisableUseAsDirectQuerySource': True|False,
'DisableUseAsImportedSource': True|False
},
DatasetParameters=[
{
'StringDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
'string',
]
}
},
'DecimalDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
123.0,
]
}
},
'IntegerDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'DefaultValues': {
'StaticValues': [
123,
]
}
},
'DateTimeDatasetParameter': {
'Id': 'string',
'Name': 'string',
'ValueType': 'MULTI_VALUED'|'SINGLE_VALUED',
'TimeGranularity': 'YEAR'|'QUARTER'|'MONTH'|'WEEK'|'DAY'|'HOUR'|'MINUTE'|'SECOND'|'MILLISECOND',
'DefaultValues': {
'StaticValues': [
datetime(2015, 1, 1),
]
}
}
},
],
PerformanceConfiguration={
'UniqueKeys': [
{
'ColumnNames': [
'string',
]
},
]
},
DataPrepConfiguration={
'SourceTableMap': {
'string': {
'PhysicalTableId': 'string',
'DataSet': {
'DataSetArn': 'string',
'InputColumns': [
{
'Name': 'string',
'Id': 'string',
'Type': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME'|'BIT'|'BOOLEAN'|'JSON',
'SubType': 'FLOAT'|'FIXED'
},
]
}
}
},
'TransformStepMap': {
'string': {
'ImportTableStep': {
'Alias': 'string',
'Source': {
'SourceTableId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
}
},
'ProjectStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ProjectedColumns': [
'string',
]
},
'FiltersStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'FilterOperations': [
{
'ConditionExpression': 'string',
'StringFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'CONTAINS'|'DOES_NOT_CONTAIN'|'STARTS_WITH'|'ENDS_WITH',
'Value': {
'StaticValue': 'string'
}
},
'ListFilterCondition': {
'Operator': 'INCLUDE'|'EXCLUDE',
'Values': {
'StaticValues': [
'string',
]
}
}
},
'NumericFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'EQUALS'|'DOES_NOT_EQUAL'|'GREATER_THAN'|'GREATER_THAN_OR_EQUALS_TO'|'LESS_THAN'|'LESS_THAN_OR_EQUALS_TO',
'Value': {
'StaticValue': 123.0
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': 123.0
},
'RangeMaximum': {
'StaticValue': 123.0
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
},
'DateFilterCondition': {
'ColumnName': 'string',
'ComparisonFilterCondition': {
'Operator': 'BEFORE'|'BEFORE_OR_EQUALS_TO'|'AFTER'|'AFTER_OR_EQUALS_TO',
'Value': {
'StaticValue': datetime(2015, 1, 1)
}
},
'RangeFilterCondition': {
'RangeMinimum': {
'StaticValue': datetime(2015, 1, 1)
},
'RangeMaximum': {
'StaticValue': datetime(2015, 1, 1)
},
'IncludeMinimum': True|False,
'IncludeMaximum': True|False
}
}
},
]
},
'CreateColumnsStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Columns': [
{
'ColumnName': 'string',
'ColumnId': 'string',
'Expression': 'string'
},
]
},
'RenameColumnsStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'RenameColumnOperations': [
{
'ColumnName': 'string',
'NewColumnName': 'string'
},
]
},
'CastColumnTypesStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'CastColumnTypeOperations': [
{
'ColumnName': 'string',
'NewColumnType': 'STRING'|'INTEGER'|'DECIMAL'|'DATETIME',
'SubType': 'FLOAT'|'FIXED',
'Format': 'string'
},
]
},
'JoinStep': {
'Alias': 'string',
'LeftOperand': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'RightOperand': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'Type': 'INNER'|'OUTER'|'LEFT'|'RIGHT',
'OnClause': 'string',
'LeftOperandProperties': {
'OutputColumnNameOverrides': [
{
'SourceColumnName': 'string',
'OutputColumnName': 'string'
},
]
},
'RightOperandProperties': {
'OutputColumnNameOverrides': [
{
'SourceColumnName': 'string',
'OutputColumnName': 'string'
},
]
}
},
'AggregateStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'GroupByColumnNames': [
'string',
],
'Aggregations': [
{
'AggregationFunction': {
'SimpleAggregation': {
'InputColumnName': 'string',
'FunctionType': 'COUNT'|'DISTINCT_COUNT'|'SUM'|'AVERAGE'|'MAX'|'MIN'
},
'ListAggregation': {
'InputColumnName': 'string',
'Separator': 'string',
'Distinct': True|False
}
},
'NewColumnName': 'string',
'NewColumnId': 'string'
},
]
},
'PivotStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'GroupByColumnNames': [
'string',
],
'ValueColumnConfiguration': {
'AggregationFunction': {
'SimpleAggregation': {
'InputColumnName': 'string',
'FunctionType': 'COUNT'|'DISTINCT_COUNT'|'SUM'|'AVERAGE'|'MAX'|'MIN'
},
'ListAggregation': {
'InputColumnName': 'string',
'Separator': 'string',
'Distinct': True|False
}
}
},
'PivotConfiguration': {
'LabelColumnName': 'string',
'PivotedLabels': [
{
'LabelName': 'string',
'NewColumnName': 'string',
'NewColumnId': 'string'
},
]
}
},
'UnpivotStep': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'ColumnsToUnpivot': [
{
'ColumnName': 'string',
'NewValue': 'string'
},
],
'UnpivotedLabelColumnName': 'string',
'UnpivotedLabelColumnId': 'string',
'UnpivotedValueColumnName': 'string',
'UnpivotedValueColumnId': 'string'
},
'AppendStep': {
'Alias': 'string',
'FirstSource': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'SecondSource': {
'TransformOperationId': 'string',
'ColumnIdMappings': [
{
'SourceColumnId': 'string',
'TargetColumnId': 'string'
},
]
},
'AppendedColumns': [
{
'ColumnName': 'string',
'NewColumnId': 'string'
},
]
}
}
},
'DestinationTableMap': {
'string': {
'Alias': 'string',
'Source': {
'TransformOperationId': 'string'
}
}
}
},
SemanticModelConfiguration={
'TableMap': {
'string': {
'Alias': 'string',
'DestinationTableId': 'string',
'RowLevelPermissionConfiguration': {
'TagConfiguration': {
'Status': 'ENABLED'|'DISABLED',
'TagRules': [
{
'TagKey': 'string',
'ColumnName': 'string',
'TagMultiValueDelimiter': 'string',
'MatchAllValue': 'string'
},
],
'TagRuleConfigurations': [
[
'string',
],
]
},
'RowLevelPermissionDataSet': {
'Namespace': 'string',
'Arn': 'string',
'PermissionPolicy': 'GRANT_ACCESS'|'DENY_ACCESS',
'FormatVersion': 'VERSION_1'|'VERSION_2',
'Status': 'ENABLED'|'DISABLED'
}
}
}
}
}
)
string
[REQUIRED]
The Amazon Web Services account ID.
string
[REQUIRED]
The ID for the dataset that you want to update. This ID is unique per Amazon Web Services Region for each Amazon Web Services account.
string
[REQUIRED]
The display name for the dataset.
dict
[REQUIRED]
Declares the physical tables that are available in the underlying data sources.
(string) --
(dict) --
A view of a data source that contains information about the shape of the data in the underlying source. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
RelationalTable (dict) --
A physical table type for relational data sources.
DataSourceArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) for the data source.
Catalog (string) --
The catalog associated with a table.
Schema (string) --
The schema name. This name applies to certain relational database engines.
Name (string) -- [REQUIRED]
The name of the relational table.
InputColumns (list) -- [REQUIRED]
The column schema of the table.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
CustomSql (dict) --
A physical table type built from the results of the custom SQL query.
DataSourceArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the data source.
Name (string) -- [REQUIRED]
A display name for the SQL query result.
SqlQuery (string) -- [REQUIRED]
The SQL query.
Columns (list) --
The column schema from the SQL query result set.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
S3Source (dict) --
A physical table type for as S3 data source.
DataSourceArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) for the data source.
UploadSettings (dict) --
Information about the format for the S3 source file or files.
Format (string) --
File format.
StartFromRow (integer) --
A row number to start reading data from.
ContainsHeader (boolean) --
Whether the file has a header row, or the files each have a header row.
TextQualifier (string) --
Text qualifier.
Delimiter (string) --
The delimiter between values in the file.
CustomCellAddressRange (string) --
A custom cell address range for Excel files, specifying which cells to import from the spreadsheet.
InputColumns (list) -- [REQUIRED]
A physical table type for an S3 data source.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
SaaSTable (dict) --
A physical table type for Software-as-a-Service (SaaS) sources.
DataSourceArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the SaaS data source.
TablePath (list) -- [REQUIRED]
The hierarchical path to the table within the SaaS data source.
(dict) --
An element in the hierarchical path to a table within a data source, containing both name and identifier.
Name (string) --
The name of the path element.
Id (string) --
The unique identifier of the path element.
InputColumns (list) -- [REQUIRED]
The list of input columns available from the SaaS table.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
dict
Configures the combination and transformation of the data from the physical tables. This parameter is used with the legacy data preparation experience.
(string) --
An identifier for the logical table that is defined in the dataset
(dict) --
A logical table is a unit that joins and that data transformations operate on. A logical table has a source, which can be either a physical table or result of a join. When a logical table points to a physical table, the logical table acts as a mutable copy of that physical table through transform operations.
Alias (string) -- [REQUIRED]
A display name for the logical table.
DataTransforms (list) --
Transform operations that act on this logical table. For this structure to be valid, only one of the attributes can be non-null.
(dict) --
A data transformation on a logical table. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
ProjectOperation (dict) --
An operation that projects columns. Operations that come after a projection can only refer to projected columns.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for column projection.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
ProjectedColumns (list) -- [REQUIRED]
Projected columns.
(string) --
FilterOperation (dict) --
An operation that filters rows based on some condition.
ConditionExpression (string) --
An expression that must evaluate to a Boolean value. Rows for which the expression evaluates to true are kept in the dataset.
StringFilterCondition (dict) --
A string-based filter condition within a filter operation.
ColumnName (string) --
The name of the string column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the string column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as EQUALS, CONTAINS, STARTS_WITH, ENDS_WITH, or their negations.
Value (dict) --
The string value to compare against.
StaticValue (string) --
A static string value used for filtering.
ListFilterCondition (dict) --
A list-based filter condition that includes or excludes values from a specified list.
Operator (string) -- [REQUIRED]
The list operator to use, either INCLUDE to match values in the list or EXCLUDE to filter out values in the list.
Values (dict) --
The list of string values to include or exclude in the filter.
StaticValues (list) --
A list of static string values used for filtering.
(string) --
NumericFilterCondition (dict) --
A numeric-based filter condition within a filter operation.
ColumnName (string) --
The name of the numeric column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the numeric column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as EQUALS, GREATER_THAN, LESS_THAN, or their variants.
Value (dict) --
The numeric value to compare against.
StaticValue (float) --
A static numeric value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the numeric column, filtering values between minimum and maximum numbers.
RangeMinimum (dict) --
The minimum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
RangeMaximum (dict) --
The maximum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
DateFilterCondition (dict) --
A date-based filter condition within a filter operation.
ColumnName (string) --
The name of the date column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the date column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as BEFORE, BEFORE_OR_EQUALS_TO, AFTER, or AFTER_OR_EQUALS_TO.
Value (dict) --
The date value to compare against.
StaticValue (datetime) --
A static date value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the date column, filtering values between minimum and maximum dates.
RangeMinimum (dict) --
The minimum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
RangeMaximum (dict) --
The maximum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
CreateColumnsOperation (dict) --
An operation that creates calculated columns. Columns created in one such operation form a lexical closure.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for creating new calculated columns.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
Columns (list) -- [REQUIRED]
Calculated columns to create.
(dict) --
A calculated column for a dataset.
ColumnName (string) -- [REQUIRED]
Column name.
ColumnId (string) -- [REQUIRED]
A unique ID to identify a calculated column. During a dataset update, if the column ID of a calculated column matches that of an existing calculated column, Quick Sight preserves the existing calculated column.
Expression (string) -- [REQUIRED]
An expression that defines the calculated column.
RenameColumnOperation (dict) --
An operation that renames a column.
ColumnName (string) -- [REQUIRED]
The name of the column to be renamed.
NewColumnName (string) -- [REQUIRED]
The new name for the column.
CastColumnTypeOperation (dict) --
A transform operation that casts a column to a different type.
ColumnName (string) -- [REQUIRED]
Column name.
NewColumnType (string) -- [REQUIRED]
New column data type.
SubType (string) --
The sub data type of the new column. Sub types are only available for decimal columns that are part of a SPICE dataset.
Format (string) --
When casting a column from string to datetime type, you can supply a string in a format supported by Quick Sight to denote the source data format.
TagColumnOperation (dict) --
An operation that tags a column with additional information.
ColumnName (string) -- [REQUIRED]
The column that this operation acts on.
Tags (list) -- [REQUIRED]
The dataset column tag, currently only used for geospatial type tagging.
(dict) --
A tag for a column in a TagColumnOperation structure. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
ColumnGeographicRole (string) --
A geospatial role for a column.
ColumnDescription (dict) --
A description for a column.
Text (string) --
The text of a description for a column.
UntagColumnOperation (dict) --
A transform operation that removes tags associated with a column.
ColumnName (string) -- [REQUIRED]
The column that this operation acts on.
TagNames (list) -- [REQUIRED]
The column tags to remove from this column.
(string) --
OverrideDatasetParameterOperation (dict) --
A transform operation that overrides the dataset parameter values that are defined in another dataset.
ParameterName (string) -- [REQUIRED]
The name of the parameter to be overridden with different values.
NewParameterName (string) --
The new name for the parameter.
NewDefaultValues (dict) --
The new default values for the parameter.
StringStaticValues (list) --
A list of static default values for a given string parameter.
(string) --
The default value for the string parameter.
DecimalStaticValues (list) --
A list of static default values for a given decimal parameter.
(float) --
The default value for the decimal parameter.
DateTimeStaticValues (list) --
A list of static default values for a given date time parameter.
(datetime) --
The default value for the date time parameter.
IntegerStaticValues (list) --
A list of static default values for a given integer parameter.
(integer) --
The default value for the integer parameter.
Source (dict) -- [REQUIRED]
Source of this logical table.
JoinInstruction (dict) --
Specifies the result of a join of two logical tables.
LeftOperand (string) -- [REQUIRED]
The operand on the left side of a join.
RightOperand (string) -- [REQUIRED]
The operand on the right side of a join.
LeftJoinKeyProperties (dict) --
Join key properties of the left operand.
UniqueKey (boolean) --
A value that indicates that a row in a table is uniquely identified by the columns in a join key. This is used by Quick Sight to optimize query performance.
RightJoinKeyProperties (dict) --
Join key properties of the right operand.
UniqueKey (boolean) --
A value that indicates that a row in a table is uniquely identified by the columns in a join key. This is used by Quick Sight to optimize query performance.
Type (string) -- [REQUIRED]
The type of join that it is.
OnClause (string) -- [REQUIRED]
The join instructions provided in the ON clause of a join.
PhysicalTableId (string) --
Physical table ID.
DataSetArn (string) --
The Amazon Resource Number (ARN) of the parent dataset.
string
[REQUIRED]
Indicates whether you want to import the data into SPICE.
list
Groupings of columns that work together in certain Amazon Quick Sight features. Currently, only geospatial hierarchy is supported.
(dict) --
Groupings of columns that work together in certain Quick Sight features. This is a variant type structure. For this structure to be valid, only one of the attributes can be non-null.
GeoSpatialColumnGroup (dict) --
Geospatial column group that denotes a hierarchy.
Name (string) -- [REQUIRED]
A display name for the hierarchy.
CountryCode (string) --
Country code.
Columns (list) -- [REQUIRED]
Columns in this hierarchy.
(string) --
dict
The folder that contains fields and nested subfolders for your dataset.
(string) --
(dict) --
A FieldFolder element is a folder that contains fields and nested subfolders.
description (string) --
The description for a field folder.
columns (list) --
A folder has a list of columns. A column can only be in one folder.
(string) --
dict
The row-level security configuration for the data you want to create. This parameter is used with the legacy data preparation experience.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) -- [REQUIRED]
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
dict
The configuration of tags on a dataset to set row-level security. Row-level security tags are currently supported for anonymous embedding only. This parameter is used with the legacy data preparation experience.
Status (string) --
The status of row-level security tags. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
TagRules (list) -- [REQUIRED]
A set of rules associated with row-level security, such as the tag names and columns that they are assigned to.
(dict) --
A set of rules associated with a tag.
TagKey (string) -- [REQUIRED]
The unique key for a tag.
ColumnName (string) -- [REQUIRED]
The column name that a tag key is assigned to.
TagMultiValueDelimiter (string) --
A string that you want to use to delimit the values when you pass the values at run time. For example, you can delimit the values with a comma.
MatchAllValue (string) --
A string that you want to use to filter by all the values in a column in the dataset and don’t want to list the values one by one. For example, you can use an asterisk as your match all value.
TagRuleConfigurations (list) --
A list of tag configuration rules to apply to a dataset. All tag configurations have the OR condition. Tags within each tile will be joined (AND). At least one rule in this structure must have all tag values assigned to it to apply Row-level security (RLS) to the dataset.
(list) --
(string) --
list
A set of one or more definitions of a ``ColumnLevelPermissionRule ``.
(dict) --
A rule defined to grant access on one or more restricted columns. Each dataset can have multiple rules. To create a restricted column, you add it to one or more rules. Each rule must contain at least one column and at least one user or group. To be able to see a restricted column, a user or group needs to be added to a rule for that column.
Principals (list) --
An array of Amazon Resource Names (ARNs) for Quick Sight users or groups.
(string) --
ColumnNames (list) --
An array of column names.
(string) --
dict
The usage configuration to apply to child datasets that reference this dataset as a source.
DisableUseAsDirectQuerySource (boolean) --
An option that controls whether a child dataset of a direct query can use this dataset as a source.
DisableUseAsImportedSource (boolean) --
An option that controls whether a child dataset that's stored in Quick Sight can use this dataset as a source.
list
The parameter declarations of the dataset.
(dict) --
A parameter that is created in a dataset. The parameter can be a string, integer, decimal, or datetime data type.
StringDatasetParameter (dict) --
A string parameter that is created in the dataset.
Id (string) -- [REQUIRED]
An identifier for the string parameter that is created in the dataset.
Name (string) -- [REQUIRED]
The name of the string parameter that is created in the dataset.
ValueType (string) -- [REQUIRED]
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given string dataset parameter type. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given string parameter.
(string) --
The default value for the string parameter.
DecimalDatasetParameter (dict) --
A decimal parameter that is created in the dataset.
Id (string) -- [REQUIRED]
An identifier for the decimal parameter created in the dataset.
Name (string) -- [REQUIRED]
The name of the decimal parameter that is created in the dataset.
ValueType (string) -- [REQUIRED]
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given decimal parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given decimal parameter.
(float) --
The default value for the decimal parameter.
IntegerDatasetParameter (dict) --
An integer parameter that is created in the dataset.
Id (string) -- [REQUIRED]
An identifier for the integer parameter created in the dataset.
Name (string) -- [REQUIRED]
The name of the integer parameter that is created in the dataset.
ValueType (string) -- [REQUIRED]
The value type of the dataset parameter. Valid values are single value or multi value.
DefaultValues (dict) --
A list of default values for a given integer parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given integer parameter.
(integer) --
The default value for the integer parameter.
DateTimeDatasetParameter (dict) --
A date time parameter that is created in the dataset.
Id (string) -- [REQUIRED]
An identifier for the parameter that is created in the dataset.
Name (string) -- [REQUIRED]
The name of the date time parameter that is created in the dataset.
ValueType (string) -- [REQUIRED]
The value type of the dataset parameter. Valid values are single value or multi value.
TimeGranularity (string) --
The time granularity of the date time parameter.
DefaultValues (dict) --
A list of default values for a given date time parameter. This structure only accepts static values.
StaticValues (list) --
A list of static default values for a given date time parameter.
(datetime) --
The default value for the date time parameter.
dict
The configuration for the performance optimization of the dataset that contains a UniqueKey configuration.
UniqueKeys (list) --
A UniqueKey configuration.
(dict) --
A UniqueKey configuration that references a dataset column.
ColumnNames (list) -- [REQUIRED]
The name of the column that is referenced in the UniqueKey configuration.
(string) --
dict
The data preparation configuration for the dataset. This configuration defines the source tables, transformation steps, and destination tables used to prepare the data. Required when using the new data preparation experience.
SourceTableMap (dict) -- [REQUIRED]
A map of source tables that provide information about underlying sources.
(string) --
(dict) --
A source table that provides initial data from either a physical table or parent dataset.
PhysicalTableId (string) --
The identifier of the physical table that serves as the data source.
DataSet (dict) --
A parent dataset that serves as the data source instead of a physical table.
DataSetArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the parent dataset.
InputColumns (list) -- [REQUIRED]
The list of input columns available from the parent dataset.
(dict) --
Metadata for a column that is used as the input of a transform operation.
Name (string) -- [REQUIRED]
The name of this column in the underlying data source.
Id (string) --
A unique identifier for the input column.
Type (string) -- [REQUIRED]
The data type of the column.
SubType (string) --
The sub data type of the column. Sub types are only available for decimal columns that are part of a SPICE dataset.
TransformStepMap (dict) -- [REQUIRED]
A map of transformation steps that process the data.
(string) --
(dict) --
A step in data preparation that performs a specific operation on the data.
ImportTableStep (dict) --
A transform step that brings data from a source table.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source configuration that specifies which source table to import and any column mappings.
SourceTableId (string) -- [REQUIRED]
The identifier of the source table to import data from.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers during the import.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
ProjectStep (dict) --
A transform operation that projects columns. Operations that come after a projection can only refer to projected columns.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for column projection.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
ProjectedColumns (list) -- [REQUIRED]
Projected columns.
(string) --
FiltersStep (dict) --
A transform step that applies filter conditions.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for filtering.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
FilterOperations (list) -- [REQUIRED]
The list of filter operations to apply.
(dict) --
A transform operation that filters rows based on a condition.
ConditionExpression (string) --
An expression that must evaluate to a Boolean value. Rows for which the expression evaluates to true are kept in the dataset.
StringFilterCondition (dict) --
A string-based filter condition within a filter operation.
ColumnName (string) --
The name of the string column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the string column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as EQUALS, CONTAINS, STARTS_WITH, ENDS_WITH, or their negations.
Value (dict) --
The string value to compare against.
StaticValue (string) --
A static string value used for filtering.
ListFilterCondition (dict) --
A list-based filter condition that includes or excludes values from a specified list.
Operator (string) -- [REQUIRED]
The list operator to use, either INCLUDE to match values in the list or EXCLUDE to filter out values in the list.
Values (dict) --
The list of string values to include or exclude in the filter.
StaticValues (list) --
A list of static string values used for filtering.
(string) --
NumericFilterCondition (dict) --
A numeric-based filter condition within a filter operation.
ColumnName (string) --
The name of the numeric column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the numeric column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as EQUALS, GREATER_THAN, LESS_THAN, or their variants.
Value (dict) --
The numeric value to compare against.
StaticValue (float) --
A static numeric value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the numeric column, filtering values between minimum and maximum numbers.
RangeMinimum (dict) --
The minimum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
RangeMaximum (dict) --
The maximum numeric value for the range filter.
StaticValue (float) --
A static numeric value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
DateFilterCondition (dict) --
A date-based filter condition within a filter operation.
ColumnName (string) --
The name of the date column to filter.
ComparisonFilterCondition (dict) --
A comparison-based filter condition for the date column.
Operator (string) -- [REQUIRED]
The comparison operator to use, such as BEFORE, BEFORE_OR_EQUALS_TO, AFTER, or AFTER_OR_EQUALS_TO.
Value (dict) --
The date value to compare against.
StaticValue (datetime) --
A static date value used for filtering.
RangeFilterCondition (dict) --
A range-based filter condition for the date column, filtering values between minimum and maximum dates.
RangeMinimum (dict) --
The minimum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
RangeMaximum (dict) --
The maximum date value for the range filter.
StaticValue (datetime) --
A static date value used for filtering.
IncludeMinimum (boolean) --
Whether to include the minimum value in the filter range.
IncludeMaximum (boolean) --
Whether to include the maximum value in the filter range.
CreateColumnsStep (dict) --
A transform operation that creates calculated columns. Columns created in one such operation form a lexical closure.
Alias (string) --
Alias for this operation.
Source (dict) --
The source transform operation that provides input data for creating new calculated columns.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
Columns (list) -- [REQUIRED]
Calculated columns to create.
(dict) --
A calculated column for a dataset.
ColumnName (string) -- [REQUIRED]
Column name.
ColumnId (string) -- [REQUIRED]
A unique ID to identify a calculated column. During a dataset update, if the column ID of a calculated column matches that of an existing calculated column, Quick Sight preserves the existing calculated column.
Expression (string) -- [REQUIRED]
An expression that defines the calculated column.
RenameColumnsStep (dict) --
A transform step that changes the names of one or more columns.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for column renaming.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
RenameColumnOperations (list) -- [REQUIRED]
The list of column rename operations to perform, specifying old and new column names.
(dict) --
A transform operation that renames a column.
ColumnName (string) -- [REQUIRED]
The name of the column to be renamed.
NewColumnName (string) -- [REQUIRED]
The new name for the column.
CastColumnTypesStep (dict) --
A transform step that changes the data types of one or more columns.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for the type casting.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
CastColumnTypeOperations (list) -- [REQUIRED]
The list of column type casting operations to perform.
(dict) --
A transform operation that casts a column to a different type.
ColumnName (string) -- [REQUIRED]
Column name.
NewColumnType (string) -- [REQUIRED]
New column data type.
SubType (string) --
The sub data type of the new column. Sub types are only available for decimal columns that are part of a SPICE dataset.
Format (string) --
When casting a column from string to datetime type, you can supply a string in a format supported by Quick Sight to denote the source data format.
JoinStep (dict) --
A transform step that combines data from two sources based on specified join conditions.
Alias (string) -- [REQUIRED]
Alias for this operation.
LeftOperand (dict) -- [REQUIRED]
The left operand for the join operation.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
RightOperand (dict) -- [REQUIRED]
The right operand for the join operation.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
Type (string) -- [REQUIRED]
The type of join to perform, such as INNER, LEFT, RIGHT, or OUTER.
OnClause (string) -- [REQUIRED]
The join condition that specifies how to match rows between the left and right operands.
LeftOperandProperties (dict) --
Properties that control how the left operand's columns are handled in the join result.
OutputColumnNameOverrides (list) -- [REQUIRED]
A list of column name overrides to apply to the join operand's output columns.
(dict) --
Specifies a mapping to override the name of an output column from a transform operation.
SourceColumnName (string) --
The original name of the column from the source transform operation.
OutputColumnName (string) -- [REQUIRED]
The new name to assign to the column in the output.
RightOperandProperties (dict) --
Properties that control how the right operand's columns are handled in the join result.
OutputColumnNameOverrides (list) -- [REQUIRED]
A list of column name overrides to apply to the join operand's output columns.
(dict) --
Specifies a mapping to override the name of an output column from a transform operation.
SourceColumnName (string) --
The original name of the column from the source transform operation.
OutputColumnName (string) -- [REQUIRED]
The new name to assign to the column in the output.
AggregateStep (dict) --
A transform step that groups data and applies aggregation functions to calculate summary values.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for the aggregation.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
GroupByColumnNames (list) --
The list of column names to group by when performing the aggregation. Rows with the same values in these columns will be grouped together.
(string) --
Aggregations (list) -- [REQUIRED]
The list of aggregation functions to apply to the grouped data, such as SUM, COUNT, or AVERAGE.
(dict) --
Defines an aggregation function to be applied to grouped data, creating a new column with the calculated result.
AggregationFunction (dict) -- [REQUIRED]
The aggregation function to apply, such as SUM, COUNT, AVERAGE, MIN, MAX
SimpleAggregation (dict) --
A simple aggregation function such as SUM, COUNT, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
InputColumnName (string) --
The name of the column on which to perform the aggregation function.
FunctionType (string) -- [REQUIRED]
The type of aggregation function to perform, such as COUNT, SUM, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
ListAggregation (dict) --
A list aggregation function that concatenates values from multiple rows into a single delimited string.
InputColumnName (string) --
The name of the column containing values to be concatenated.
Separator (string) -- [REQUIRED]
The string used to separate values in the concatenated result.
Distinct (boolean) -- [REQUIRED]
Whether to include only distinct values in the concatenated result, removing duplicates.
NewColumnName (string) -- [REQUIRED]
The name for the new column that will contain the aggregated values.
NewColumnId (string) -- [REQUIRED]
A unique identifier for the new column that will contain the aggregated values.
PivotStep (dict) --
A transform step that converts row values into columns to reshape the data structure.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for pivoting.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
GroupByColumnNames (list) --
The list of column names to group by when performing the pivot operation.
(string) --
ValueColumnConfiguration (dict) -- [REQUIRED]
Configuration for how to aggregate values when multiple rows map to the same pivoted column.
AggregationFunction (dict) --
The aggregation function to apply when multiple values map to the same pivoted cell.
SimpleAggregation (dict) --
A simple aggregation function such as SUM, COUNT, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
InputColumnName (string) --
The name of the column on which to perform the aggregation function.
FunctionType (string) -- [REQUIRED]
The type of aggregation function to perform, such as COUNT, SUM, AVERAGE, MIN, MAX, MEDIAN, VARIANCE, or STANDARD_DEVIATION.
ListAggregation (dict) --
A list aggregation function that concatenates values from multiple rows into a single delimited string.
InputColumnName (string) --
The name of the column containing values to be concatenated.
Separator (string) -- [REQUIRED]
The string used to separate values in the concatenated result.
Distinct (boolean) -- [REQUIRED]
Whether to include only distinct values in the concatenated result, removing duplicates.
PivotConfiguration (dict) -- [REQUIRED]
Configuration that specifies which labels to pivot and how to structure the resulting columns.
LabelColumnName (string) --
The name of the column that contains the labels to be pivoted into separate columns.
PivotedLabels (list) -- [REQUIRED]
The list of specific label values to pivot into separate columns.
(dict) --
Specifies a label value to be pivoted into a separate column, including the new column name and identifier.
LabelName (string) -- [REQUIRED]
The label value from the source data to be pivoted.
NewColumnName (string) -- [REQUIRED]
The name for the new column created from this pivoted label.
NewColumnId (string) -- [REQUIRED]
A unique identifier for the new column created from this pivoted label.
UnpivotStep (dict) --
A transform step that converts columns into rows to normalize the data structure.
Alias (string) -- [REQUIRED]
Alias for this operation.
Source (dict) -- [REQUIRED]
The source transform operation that provides input data for unpivoting.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
ColumnsToUnpivot (list) -- [REQUIRED]
The list of columns to unpivot from the source data.
(dict) --
Specifies a column to be unpivoted, transforming it from a column into rows with associated values.
ColumnName (string) --
The name of the column to unpivot from the source data.
NewValue (string) --
The value to assign to this column in the unpivoted result, typically the column name or a descriptive label.
UnpivotedLabelColumnName (string) -- [REQUIRED]
The name for the new column that will contain the unpivoted column names.
UnpivotedLabelColumnId (string) -- [REQUIRED]
A unique identifier for the new column that will contain the unpivoted column names.
UnpivotedValueColumnName (string) -- [REQUIRED]
The name for the new column that will contain the unpivoted values.
UnpivotedValueColumnId (string) -- [REQUIRED]
A unique identifier for the new column that will contain the unpivoted values.
AppendStep (dict) --
A transform step that combines rows from multiple sources by stacking them vertically.
Alias (string) -- [REQUIRED]
Alias for this operation.
FirstSource (dict) --
The first data source to be included in the append operation.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
SecondSource (dict) --
The second data source to be appended to the first source.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides input data.
ColumnIdMappings (list) --
The mappings between source column identifiers and target column identifiers for this transformation.
(dict) --
Maps a source column identifier to a target column identifier during transform operations.
SourceColumnId (string) -- [REQUIRED]
Source column ID.
TargetColumnId (string) -- [REQUIRED]
Target column ID.
AppendedColumns (list) -- [REQUIRED]
The list of columns to include in the appended result, mapping columns from both sources.
(dict) --
Represents a column that will be included in the result of an append operation, combining data from multiple sources.
ColumnName (string) -- [REQUIRED]
The name of the column to include in the appended result.
NewColumnId (string) -- [REQUIRED]
A unique identifier for the column in the appended result.
DestinationTableMap (dict) -- [REQUIRED]
A map of destination tables that receive the final prepared data.
(string) --
(dict) --
Defines a destination table in data preparation that receives the final transformed data.
Alias (string) -- [REQUIRED]
Alias for the destination table.
Source (dict) -- [REQUIRED]
The source configuration that specifies which transform operation provides data to this destination table.
TransformOperationId (string) -- [REQUIRED]
The identifier of the transform operation that provides data to the destination table.
dict
The semantic model configuration for the dataset. This configuration defines how the prepared data is structured for an analysis, including table mappings and row-level security configurations. Required when using the new data preparation experience.
TableMap (dict) --
A map of semantic tables that define the analytical structure.
(string) --
(dict) --
A semantic table that represents the final analytical structure of the data.
Alias (string) -- [REQUIRED]
Alias for the semantic table.
DestinationTableId (string) -- [REQUIRED]
The identifier of the destination table from data preparation that provides data to this semantic table.
RowLevelPermissionConfiguration (dict) --
Configuration for row level security that control data access for this semantic table.
TagConfiguration (dict) --
The configuration of tags on a dataset to set row-level security.
Status (string) --
The status of row-level security tags. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
TagRules (list) -- [REQUIRED]
A set of rules associated with row-level security, such as the tag names and columns that they are assigned to.
(dict) --
A set of rules associated with a tag.
TagKey (string) -- [REQUIRED]
The unique key for a tag.
ColumnName (string) -- [REQUIRED]
The column name that a tag key is assigned to.
TagMultiValueDelimiter (string) --
A string that you want to use to delimit the values when you pass the values at run time. For example, you can delimit the values with a comma.
MatchAllValue (string) --
A string that you want to use to filter by all the values in a column in the dataset and don’t want to list the values one by one. For example, you can use an asterisk as your match all value.
TagRuleConfigurations (list) --
A list of tag configuration rules to apply to a dataset. All tag configurations have the OR condition. Tags within each tile will be joined (AND). At least one rule in this structure must have all tag values assigned to it to apply Row-level security (RLS) to the dataset.
(list) --
(string) --
RowLevelPermissionDataSet (dict) --
Information about a dataset that contains permissions for row-level security (RLS). The permissions dataset maps fields to users or groups. For more information, see Using Row-Level Security (RLS) to Restrict Access to a Dataset in the Quick Sight User Guide.
The option to deny permissions by setting PermissionPolicy to DENY_ACCESS is not supported for new RLS datasets.
Namespace (string) --
The namespace associated with the dataset that contains permissions for RLS.
Arn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the dataset that contains permissions for RLS.
PermissionPolicy (string) -- [REQUIRED]
The type of permissions to use when interpreting the permissions for RLS. DENY_ACCESS is included for backward compatibility only.
FormatVersion (string) --
The user or group rules associated with the dataset that contains permissions for RLS.
By default, FormatVersion is VERSION_1. When FormatVersion is VERSION_1, UserName and GroupName are required. When FormatVersion is VERSION_2, UserARN and GroupARN are required, and Namespace must not exist.
Status (string) --
The status of the row-level security permission dataset. If enabled, the status is ENABLED. If disabled, the status is DISABLED.
dict
Response Syntax
{
'Arn': 'string',
'DataSetId': 'string',
'IngestionArn': 'string',
'IngestionId': 'string',
'RequestId': 'string',
'Status': 123
}
Response Structure
(dict) --
Arn (string) --
The Amazon Resource Name (ARN) of the dataset.
DataSetId (string) --
The ID for the dataset that you want to update. This ID is unique per Amazon Web Services Region for each Amazon Web Services account.
IngestionArn (string) --
The ARN for the ingestion, which is triggered as a result of dataset creation if the import mode is SPICE.
IngestionId (string) --
The ID of the ingestion, which is triggered as a result of dataset creation if the import mode is SPICE.
RequestId (string) --
The Amazon Web Services request ID for this operation.
Status (integer) --
The HTTP status of the request.