sunchao commented on code in PR #5558:
URL: https://github.com/apache/datafusion-comet/pull/5558#discussion_r3916755645
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spark/src/main/scala/org/apache/comet/serde/arrays.scala:
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@@ -352,7 +350,9 @@ object CometArrayJoin
if (hasNonDefaultStringCollation(expr.array.dataType)) {
Incompatible(Some(collationReason))
} else {
- Incompatible(Some(incompatReason))
+ // Null handling matched Spark once the nullReplacement guard in
convert() landed (#3178);
+ // collation is the only remaining deviation.
+ Compatible()
Review Comment:
[P2] Follow-up on the remaining null-array case
Thanks, the original column-based delimiter example is guarded now. Could
the guard selection also distinguish literal values from surviving foldable
expressions? With Parquet columns `flag = true` and `arr = NULL`, consider
`SELECT IF(flag, array_join(arr, element_at(array(','), 0)), NULL) FROM t`.
Spark's `ConstantFolding` deliberately retains a foldable expression that
throws inside a conditional branch, so this does not require disabling the
optimizer. The delimiter remains foldable, which makes the new
`afterArray.exists(!_.foldable)` test omit the array guard. Spark's
two-argument generated path returns NULL without evaluating it, while the
native scalar-function path evaluates `ListExtract` and raises
`INVALID_INDEX_OF_ZERO`.
Could the guard also protect a surviving foldable delimiter, with a
regression using normal constant folding? This is the remaining part of this
null-array issue, based on the maintained Spark 3.5/4.0 sources and the current
native path. I have not executed the query.
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