def METHOD_NAME(
    empty_data_context: AbstractDataContext,
    persist,
    spark_session,
):
    spark_config: SparkConfig | None = {
        "spark.sql.catalogImplementation": "in-memory",
        "spark.app.name": "gx_spark_fluent_datasource_test",
        "spark.default.parallelism": 4,
        "spark.driver.memory": "16g",
        "spark.executor.memory": 471859200,
        "spark.master": "local[*]",
    }
    datasource = empty_data_context.sources.add_spark(
        name="my_spark_datasource",
        spark_config=spark_config,
        force_reuse_spark_context=False,
        persist=persist,
    )
    spark_config = json.loads(json.dumps(spark_config), parse_int=str, parse_float=str)
    assert is_candidate_subset_of_target(
        candidate=spark_config,
        target=datasource.get_execution_engine().config["spark_config"],
    )