snowflake.snowpark.DataFrame.cross_join¶

DataFrame.cross_join(right: DataFrame, *, lsuffix: str = '', rsuffix: str = '') → DataFrame[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.16.0/src/snowflake/snowpark/dataframe.py#L2552-L2610)¶

Performs a cross join, which returns the Cartesian product of the current DataFrame and another DataFrame (right).

If the current and right DataFrames have columns with the same name, and you need to refer to one of these columns in the returned DataFrame, use the col() function on the current or right DataFrame to disambiguate references to these columns.

Example:

>>> df1 = session.create_dataframe([[1, 2], [3, 4]], schema=["a", "b"])
>>> df2 = session.create_dataframe([[5, 6], [7, 8]], schema=["c", "d"])
>>> df1.cross_join(df2).sort("a", "b", "c", "d").show()
-------------------------
|"A"  |"B"  |"C"  |"D"  |
-------------------------
|1    |2    |5    |6    |
|1    |2    |7    |8    |
|3    |4    |5    |6    |
|3    |4    |7    |8    |
-------------------------

>>> df3 = session.create_dataframe([[1, 2], [3, 4]], schema=["a", "b"])
>>> df4 = session.create_dataframe([[5, 6], [7, 8]], schema=["a", "b"])
>>> df3.cross_join(df4, lsuffix="_l", rsuffix="_r").sort("a_l", "b_l", "a_r", "b_r").show()
---------------------------------
|"A_L"  |"B_L"  |"A_R"  |"B_R"  |
---------------------------------
|1      |2      |5      |6      |
|1      |2      |7      |8      |
|3      |4      |5      |6      |
|3      |4      |7      |8      |
---------------------------------

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Parameters:

• right – the right DataFrame to join.

• 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

If both lsuffix and rsuffix are empty, the overlapping columns will have random column names in the result DataFrame. If either one is not empty, the overlapping columns won’t have random names.