Github user jeanlyn commented on a diff in the pull request:
https://github.com/apache/spark/pull/7535#discussion_r38289221
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
---
@@ -129,6 +128,14 @@ trait CheckAnalysis {
failAnalysis(
s"unresolved operator ${operator.simpleString}")
+ case o if o.expressions.exists(!_.deterministic) &&
+ !o.isInstanceOf[Project] && !o.isInstanceOf[Filter] =>
+ failAnalysis(
--- End diff --
Hi, @cloud-fan .Can it support for join operation? Sometimes we can use
some `non deterministic ` expression to eval some pointless join keys(with
respect to business logic) avoiding data skew.
For example
```sql
SELECT src.key, src.value, src1.value
FROM src
JOIN src1
ON UPPER((CASE WHEN (src.key IS NULL OR src.key = '' ) THEN CAST( (-RAND()
* 10000000 ) AS string ) ELSE src.key END )) = UPPER(src1.key)
```
What do you think?
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