HyukjinKwon commented on a change in pull request #32955:
URL: https://github.com/apache/spark/pull/32955#discussion_r655853638
##########
File path: python/pyspark/pandas/spark/functions.py
##########
@@ -32,6 +41,22 @@ def repeat(col: Column, n: Union[int, Column]) -> Column:
return _call_udf(sc, "repeat", _to_java_column(col), n)
+def lit(literal: Any) -> Column:
+ """
+ Creates a Column of literal value.
+ """
+ if isinstance(literal, np.int64):
Review comment:
@xinrong-databricks, I think we can just support this natively all
across PySpark. Can you add an input converter here
(https://github.com/apache/spark/blob/20750a3f9e13a2f02860859f87bbc38a18cba85e/python/pyspark/sql/types.py#L1608-L1622)
and see if it works?
Also, I think we can simplify it by `item()`
(https://stackoverflow.com/a/11389998/2438480) with `np.generic` type check
(https://numpy.org/doc/stable/reference/arrays.scalars.html).
cc @ueshin @itholic too
##########
File path: python/pyspark/pandas/spark/functions.py
##########
@@ -32,6 +41,22 @@ def repeat(col: Column, n: Union[int, Column]) -> Column:
return _call_udf(sc, "repeat", _to_java_column(col), n)
+def lit(literal: Any) -> Column:
+ """
+ Creates a Column of literal value.
+ """
+ if isinstance(literal, np.int64):
Review comment:
cc @mengxr too FYI
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