peter-toth commented on code in PR #59749:
URL: https://github.com/apache/spark/pull/59749#discussion_r4360189465
##########
sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala:
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@@ -6211,6 +6211,32 @@ class DataFrameFunctionsSuite extends SharedSparkSession
{
)
}
+ test("SPARK-60508: nested higher-order functions capturing different lambda
variables") {
Review Comment:
**Finding 1.** The description also fixes the Python UDF example, which only
the manual run covers. `ExtractPythonUDFFromLambdaSuite` checks the lifting on
the optimized plan with dummy UDFs, so it needs no Python worker. This passes
here and fails on `master` without the fix, where the two calls are merged into
one lifted UDF:
```scala
test("SPARK-60508: calls capturing different lambda variables are lifted
distinctly") {
val df = Seq((Seq(1, 2), Seq(10, 20), Seq(0, 5, 15))).toDF("l", "r",
"c").select(
zip_with(col("l"), col("r"), (a, b) =>
pythonUDF(filter(col("c"), y => y < a)) ||
pythonUDF(filter(col("c"), y => y < b)))
.as("res"))
assert(udfsInsideLambda(df).isEmpty)
assert(liftedUDFs(df).size == 2)
}
```
It needs `filter` in the suite's `functions` import.
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