def METHOD_NAME(spark_session) -> pyspark.DataFrame:
    def generate_ascending_list_of_datetimes(
        n, start_date=datetime.date(2020, 1, 1), end_date=datetime.date(2020, 12, 31)
    ) -> List[datetime.datetime]:
        start_time = datetime.datetime(
            start_date.year, start_date.month, start_date.day
        )
        seconds_between_dates = (end_date - start_date).total_seconds()
        # noinspection PyUnusedLocal
        datetime_list = [
            start_time
            + datetime.timedelta(seconds=random.randrange(int(seconds_between_dates)))
            for i in range(n)
        ]
        datetime_list.sort()
        return datetime_list
    k: int = 120
    random.seed(1)
    timestamp_list: List[datetime.datetime] = generate_ascending_list_of_datetimes(
        n=k, end_date=datetime.date(2020, 1, 31)
    )
    date_list: List[datetime.date] = [
        datetime.date(ts.year, ts.month, ts.day) for ts in timestamp_list
    ]
    # noinspection PyUnusedLocal
    batch_ids: List[int] = [random.randint(0, 10) for i in range(k)]
    batch_ids.sort()
    # noinspection PyUnusedLocal
    session_ids: List[int] = [random.randint(2, 60) for i in range(k)]
    session_ids = [i - random.randint(0, 2) for i in session_ids]
    session_ids.sort()
    # noinspection PyUnusedLocal
    spark_df: pyspark.DataFrame = spark_session.createDataFrame(
        data=pd.DataFrame(
            {
                "id": range(k),
                "batch_id": batch_ids,
                "date": date_list,
                "y": [d.year for d in date_list],
                "m": [d.month for d in date_list],
                "d": [d.day for d in date_list],
                "timestamp": timestamp_list,
                "session_ids": session_ids,
                "event_type": [
                    random.choice(["start", "stop", "continue"]) for i in range(k)
                ],
                "favorite_color": [
                    "#"
                    + "".join(
                        [random.choice(list("0123456789ABCDEF")) for j in range(6)]
                    )
                    for i in range(k)
                ],
            }
        )
    )
    spark_df = spark_df.withColumn(
        "timestamp",
        F.col("timestamp")
        .cast(pyspark.types.IntegerType())
        .cast(pyspark.types.StringType()),
    )
    return spark_df