def METHOD_NAME():
    pd_es = EntitySet(id="pd_es")
    spark_es = EntitySet(id="spark_es")
    sessions = pd.DataFrame(
        {
            "id": [0, 1, 2, 3],
            "user": [1, 2, 1, 3],
            "time": [
                pd.to_datetime("2019-01-10"),
                pd.to_datetime("2019-02-03"),
                pd.to_datetime("2019-01-01"),
                pd.to_datetime("2017-08-25"),
            ],
            "strings": ["I am a string", "23", "abcdef ghijk", ""],
        },
    )
    sessions_spark = ps.from_pandas(sessions)
    sessions_logical_types = {
        "id": Integer,
        "user": Integer,
        "strings": NaturalLanguage,
        "time": Datetime,
    }
    transactions = pd.DataFrame(
        {
            "id": [0, 1, 2, 3, 4, 5],
            "session_id": [0, 0, 1, 2, 2, 3],
            "amount": [1.23, 5.24, 123.52, 67.93, 40.34, 50.13],
            "time": [
                pd.to_datetime("2019-01-10 03:53"),
                pd.to_datetime("2019-01-10 04:12"),
                pd.to_datetime("2019-02-03 10:34"),
                pd.to_datetime("2019-01-01 12:35"),
                pd.to_datetime("2019-01-01 12:49"),
                pd.to_datetime("2017-08-25 04:53"),
            ],
        },
    )
    transactions_spark = ps.from_pandas(transactions)
    transactions_logical_types = {
        "id": Integer,
        "session_id": Integer,
        "amount": Double,
        "time": Datetime,
    }
    pd_es.add_dataframe(
        dataframe_name="sessions",
        dataframe=sessions,
        index="id",
        time_index="time",
    )
    spark_es.add_dataframe(
        dataframe_name="sessions",
        dataframe=sessions_spark,
        index="id",
        time_index="time",
        logical_types=sessions_logical_types,
    )
    pd_es.add_dataframe(
        dataframe_name="transactions",
        dataframe=transactions,
        index="id",
        time_index="time",
    )
    spark_es.add_dataframe(
        dataframe_name="transactions",
        dataframe=transactions_spark,
        index="id",
        time_index="time",
        logical_types=transactions_logical_types,
    )
    pd_es = pd_es.add_relationship("sessions", "id", "transactions", "session_id")
    spark_es = spark_es.add_relationship("sessions", "id", "transactions", "session_id")
    assert "foreign_key" in pd_es["transactions"].ww.semantic_tags["session_id"]
    assert "foreign_key" in spark_es["transactions"].ww.semantic_tags["session_id"]
    assert pd_es["sessions"].ww.metadata.get("last_time_index") is None
    assert spark_es["sessions"].ww.metadata.get("last_time_index") is None
    pd_es.add_last_time_indexes()
    spark_es.add_last_time_indexes()
    pd_lti_name = pd_es["sessions"].ww.metadata.get("last_time_index")
    spark_lti_name = spark_es["sessions"].ww.metadata.get("last_time_index")
    assert pd_lti_name == spark_lti_name
    pd.testing.assert_series_equal(
        pd_es["sessions"][pd_lti_name].sort_index(),
        spark_es["sessions"][spark_lti_name].to_pandas().sort_index(),
        check_names=False,
    )