def METHOD_NAME(long_log_with_features):
    indexer = Indexer()
    df = long_log_with_features.withColumnRenamed("user_idx", "user_id")
    df = df.withColumnRenamed("item_idx", "item_id")
    indexer.fit(df, df)
    res = indexer.transform(df)
    log = indexer.inverse_transform(res)
    sparkDataFrameEqual(log, df)