Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/3109#discussion_r20390957
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
---
@@ -262,7 +262,7 @@ object NullPropagation extends Rule[LogicalPlan] {
*/
object ConstantFolding extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
- case q: LogicalPlan => q transformExpressionsDown {
+ case q: LogicalPlan => q transformExpressionsUp {
--- End diff --
Ah, sorry now I read the PR description more carefully and I think I
understand. However, this now seems kind of hacky to me. We are now leaving
the analysis phase with a tree that isn't actually valid and then hoping that
constant folding is going to fix things down the road. This breaks the
contract that it should be safe to inspect dataTypes once analysis is done.
Is this query valid in Hive? If so, I'd almost rather add more rules/logic
to analysis (maybe we need to have a notion of "resolved" for HiveUDFs and
attempt to constant fold them if they aren't resolved? What do you think?
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