itholic commented on code in PR #46063:
URL: https://github.com/apache/spark/pull/46063#discussion_r1568413626
##########
python/pyspark/sql/column.py:
##########
@@ -175,46 +175,13 @@ def _bin_op(
["Column", Union["Column", "LiteralType", "DecimalLiteral",
"DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
- binary_operator_map = {
- "plus": "+",
- "minus": "-",
- "divide": "/",
- "multiply": "*",
- "mod": "%",
- "equalTo": "=",
- "lt": "<",
- "leq": "<=",
- "geq": ">=",
- "gt": ">",
- "eqNullSafe": "<=>",
- "bitwiseOR": "|",
- "bitwiseAND": "&",
- "bitwiseXOR": "^",
- # Just following JVM rule even if the names of source and target are
the same.
- "and": "and",
- "or": "or",
- }
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral",
"DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
- if name in binary_operator_map:
- from pyspark.sql import SparkSession
-
- spark = SparkSession._getActiveSessionOrCreate()
- stack = list(reversed(inspect.stack()))
- depth = int(
- spark.conf.get("spark.sql.stackTracesInDataFrameContext") #
type: ignore[arg-type]
Review Comment:
Oh, yes we should. Just updated code to respect the config.
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