class_docstr: DatasetDefinition for Redshift.
  
  With this input, SQL queries will be executed using Redshift to generate datasets to S3.
class_docstr_tok: ["DatasetDefinition","for","Redshift",".","With","this","input",",","SQL","queries","will","be","executed","using","Redshift","to","generate","datasets","to","S3","."]
docstr: Initialize RedshiftDatasetDefinition.
  
  Args:
      cluster_id (str, default=None): The Redshift cluster Identifier.
      database (str, default=None):
          The name of the Redshift database used in Redshift query execution.
      db_user (str, default=None): The database user name used in Redshift query execution.
      query_string (str, default=None): The SQL query statements to be executed.
      cluster_role_arn (str, default=None): The IAM role attached to your Redshift cluster
          that Amazon SageMaker uses to generate datasets.
      output_s3_uri (str, default=None): The location in Amazon S3 where the Redshift query
          results are stored.
      kms_key_id (str, default=None): The AWS Key Management Service (AWS KMS) key that Amazon
          SageMaker uses to encrypt data from a Redshift execution.
      output_format (str, default=None): The data storage format for Redshift query results.
          Valid options are "PARQUET", "CSV"
      output_compression (str, default=None): The compression used for Redshift query results.
          Valid options are "None", "GZIP", "SNAPPY", "ZSTD", "BZIP2"
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code: def __init__(
      self,
      cluster_id=None,
      database=None,
      db_user=None,
      query_string=None,
      cluster_role_arn=None,
      output_s3_uri=None,
      kms_key_id=None,
      output_format=None,
      output_compression=None,
  ):
      """Initialize RedshiftDatasetDefinition.
  
      Args:
          cluster_id (str, default=None): The Redshift cluster Identifier.
          database (str, default=None):
              The name of the Redshift database used in Redshift query execution.
          db_user (str, default=None): The database user name used in Redshift query execution.
          query_string (str, default=None): The SQL query statements to be executed.
          cluster_role_arn (str, default=None): The IAM role attached to your Redshift cluster
              that Amazon SageMaker uses to generate datasets.
          output_s3_uri (str, default=None): The location in Amazon S3 where the Redshift query
              results are stored.
          kms_key_id (str, default=None): The AWS Key Management Service (AWS KMS) key that Amazon
              SageMaker uses to encrypt data from a Redshift execution.
          output_format (str, default=None): The data storage format for Redshift query results.
              Valid options are "PARQUET", "CSV"
          output_compression (str, default=None): The compression used for Redshift query results.
              Valid options are "None", "GZIP", "SNAPPY", "ZSTD", "BZIP2"
      """
      super(RedshiftDatasetDefinition, self).__init__(
          cluster_id=cluster_id,
          database=database,
          db_user=db_user,
          query_string=query_string,
          cluster_role_arn=cluster_role_arn,
          output_s3_uri=output_s3_uri,
          kms_key_id=kms_key_id,
          output_format=output_format,
          output_compression=output_compression,
      )
  
file_path: sagemaker-python-sdk/src/sagemaker/dataset_definition/inputs.py
imports: from __future__ import absolute_import
  from sagemaker.apiutils._base_types import ApiObject
label_desc: Use image node_id 1 to create a new RedshiftDatasetDefinition object from inherited base classes: ApiObject with example: obj = RedshiftDatasetDefinition(cluster_id, database, db_user, query_string, cluster_role_arn, output_s3_uri, kms_key_id, output_format, output_compression)