[jira] [Created] (SPARK-33310) Relax pyspark typing for sql str functions

["Daniel Himmelstein (Jira)" <ji...@apache.org>]

Daniel Himmelstein created SPARK-33310:
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             Summary: Relax pyspark typing for sql str functions
                 Key: SPARK-33310
                 URL: https://issues.apache.org/jira/browse/SPARK-33310
             Project: Spark
          Issue Type: Wish
          Components: PySpark
    Affects Versions: 3.1.0
            Reporter: Daniel Himmelstein
             Fix For: 3.1.0


Several pyspark.sql.functions have overly strict typing, in that the type is more restrictive than the functionality. Specifically, the function allows specifying the column to operate on with a pyspark.sql.Column or a str. This is handled internally by [_to_java_column|https://github.com/apache/spark/blob/491a0fb08b0c57a99894a0b33c5814854db8de3d/python/pyspark/sql/column.py#L39-L50], which accepts a Column or string.

There is a pre-existing type for this: [ColumnOrName|https://github.com/apache/spark/blob/72ad9dcd5d484a8dd64c08889de85ef9de2a6077/python/pyspark/sql/_typing.pyi#L37]. ColumnOrName is used for many of the type definitions of pyspark.sql.functions arguments, but [not for|https://github.com/apache/spark/blob/72ad9dcd5d484a8dd64c08889de85ef9de2a6077/python/pyspark/sql/functions.pyi#L158-L162] locate, lpad, rpad, repeat, and split.
{code:java}
def locate(substr: str, str: Column, pos: int = ...) -> Column: ...
def lpad(col: Column, len: int, pad: str) -> Column: ...
def rpad(col: Column, len: int, pad: str) -> Column: ...
def repeat(col: Column, n: int) -> Column: ...
def split(str: Column, pattern: str, limit: int = ...) -> Column: ...{code}
ColumnOrName was not added by [~zero323] since Maciej "was concerned that this might be confusing or ambiguous", because these functions take a column to operate on as well strings which are used in the operation.

But I think ColumnOrName makes clear that this variable refers to the column and not a string parameter. Also there are other ways to address confusion, such as via the docstring or by changing the argument name for the column to col from str.

Finally, there's considerable convenience for users to not have to wrap column names in pyspark.sql.functions.col. Elsewhere the API seems pretty consistent in its willingness to accept columns by name and not Column object (at least when there is not alternative meaning for a string value, exception would be .when/.otherwise).

For example, we were pyspark.sql.functions.split with a string value for the str argument (specifying which column to split). And I noticed this when we enforced typing with pyspark-stubs in preparation for pyspark 3.1.

Pre-existing PRs to address this:
 * https://github.com/apache/spark/pull/30209
 * https://github.com/zero323/pyspark-stubs/pull/420



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