code: def athena_dataset_definition(sagemaker_session):
      return DatasetDefinition(
          local_path="/opt/ml/processing/input/add",
          data_distribution_type="FullyReplicated",
          input_mode="File",
          athena_dataset_definition=AthenaDatasetDefinition(
              catalog="AwsDataCatalog",
              database="default",
              work_group="workgroup",
              query_string='SELECT * FROM "default"."s3_test_table_$STAGE_$REGIONUNDERSCORED";',
              output_s3_uri=f"s3://{sagemaker_session.default_bucket()}/add",
              output_format="JSON",
              output_compression="GZIP",
          ),
      )
  
imports: from __future__ import absolute_import
  import os
  import time
  import pytest
  from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
  from sagemaker.processing import ProcessingInput
  from sagemaker.session import get_execution_role
  from sagemaker.sklearn.processing import SKLearnProcessor
  from sagemaker.dataset_definition.inputs import DatasetDefinition, AthenaDatasetDefinition
  from sagemaker.workflow.execution_variables import ExecutionVariables
  from sagemaker.workflow.functions import Join
  from sagemaker.workflow.parameters import ParameterInteger
  from sagemaker.workflow.pipeline_experiment_config import PipelineExperimentConfig
  from sagemaker.workflow.steps import ProcessingStep
  from sagemaker.workflow.pipeline import Pipeline
  from tests.integ import DATA_DIR
label_desc: Use image node_id 6 for calling a global function with example usage: athena_dataset_definition(sagemaker_session) and returns: DatasetDefinition