code: def test_create_dataset_with_dataframe(sagemaker_session_mock):
      feature_store = FeatureStore(
          sagemaker_session=sagemaker_session_mock
      )
      dataset_builder = feature_store.create_dataset(
          base=DATAFRAME,
          record_identifier_feature_name="feature_1",
          event_time_identifier_feature_name="feature_2",
          included_feature_names=["feature_1", "feature_2"],
          output_path="file/to/path",
          kms_key_id="kms-key-id",
      )
      assert (
          dataset_builder._sagemaker_session == sagemaker_session_mock
      )
      assert dataset_builder._base.equals(DATAFRAME)
      assert (
          dataset_builder._record_identifier_feature_name == "feature_1"
      )
      assert (
          dataset_builder._event_time_identifier_feature_name
          == "feature_2"
      )
      assert dataset_builder._included_feature_names == [
          "feature_1",
          "feature_2",
      ]
      assert dataset_builder._output_path == "file/to/path"
      assert dataset_builder._kms_key_id == "kms-key-id"
  
file_path: sagemaker-python-sdk/tests/unit/sagemaker/feature_store/test_feature_store.py
imports: from __future__ import absolute_import
  import datetime
  import pandas
  import pytest
  from mock import Mock
  from sagemaker.feature_store.feature_store import FeatureStore
  from sagemaker.feature_store.inputs import Filter, FilterOperatorEnum, ResourceEnum, SearchOperatorEnum, SortOrderEnum, Identifier
label_desc: Use image node_id 5 for calling a global function with example usage: test_create_dataset_with_dataframe(sagemaker_session_mock) without return types