jchen5 opened a new pull request, #43068:
URL: https://github.com/apache/spark/pull/43068

   ### What changes were proposed in this pull request?
   Enables the correctness fixes for `null IN (empty list)` expressions
   
   `null IN (empty list)` incorrectly evaluates to null, when it should 
evaluate to false. (The reason it should be false is because a IN (b1, b2) is 
defined as a = b1 OR a = b2, and an empty IN list is treated as an empty OR 
which is false. This is specified by ANSI SQL.)
   
   Many places in Spark execution (In, InSet, InSubquery) and optimization 
(OptimizeIn, NullPropagation) implemented this wrong behavior. This is a 
longstanding correctness issue which has existed since null support for IN 
expressions was first added to Spark.
   
   See previous PRs where the fixes were implemented: 
https://github.com/apache/spark/pull/42007 and 
https://github.com/apache/spark/pull/42163.
   
   The behavior is under a flag. This PR enables the new behavior by default 
under ANSI, while under non-ANSI the old behavior remains the default for now. 
Later, we should switch the new behavior to default in both cases.
   
   See [this 
doc](https://docs.google.com/document/d/1k8AY8oyT-GI04SnP7eXttPDnDj-Ek-c3luF2zL6DPNU/edit)
 for more information.
   
   ### Why are the changes needed?
   Fix wrong SQL semantics
   
   ### Does this PR introduce _any_ user-facing change?
   Yes, fix wrong SQL semantics
   
   ### How was this patch tested?
   Unit tests
   
   ### Was this patch authored or co-authored using generative AI tooling?
   No


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