snowflake.snowpark.DataFrame.lateral_join

DataFrame.lateral_join(right: DataFrame, on: Optional[Column] = None, *, lsuffix: str = '', rsuffix: str = '') → DataFrame[source]

Performs an inner lateral join with the current DataFrame and another DataFrame (right).

Parameters:

  • right – The other DataFrame to join.

  • on – A Column expression for the lateral join condition. This condition will be used to filter the right DataFrame in the lateral subquery (e.g., WHERE t1.a = t2.a).

  • lsuffix – Suffix to add to the overlapping columns of the left DataFrame.

  • rsuffix – Suffix to add to the overlapping columns of the right DataFrame.

Note

When both lsuffix and rsuffix are empty, the overlapping columns will have random column names in the resulting DataFrame. You can reference to these randomly named columns using Column.alias().

Examples::
>>> df1 = session.create_dataframe([[1, 2], [3, 4], [5, 6]], schema=["a", "b"])
>>> df2 = session.create_dataframe([[1, 7], [3, 8]], schema=["a", "c"])
>>> df1.lateral_join(df2, df1.a == df2.a).select(df1.a.alias("a_1"), df2.a.alias("a_2"), df1.b, df2.c).show()
-----------------------------
|"A_1"  |"A_2"  |"B"  |"C"  |
-----------------------------
|1      |1      |2    |7    |
|3      |3      |4    |8    |
-----------------------------
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>>> # With lsuffix and rsuffix for column disambiguation
>>> df1.lateral_join(df2, df1.b * 2 > df2.c, lsuffix="_l", rsuffix="_r").select("*").show()
-----------------------------
|"A_L"  |"B"  |"A_R"  |"C"  |
-----------------------------
|3      |4    |1      |7    |
|5      |6    |1      |7    |
|5      |6    |3      |8    |
-----------------------------
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