amaliujia opened a new pull request #35404:
URL: https://github.com/apache/spark/pull/35404
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### What changes were proposed in this pull request?
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```
with t as (select true c)
3select t.c
4from t
5group by t.c
6having mean(t.c) > 0 {code}
```
This query throws `Column 't.c' does not exist. Did you mean one of the
following? [t.c]`
However, mean(boolean) is not a supported function signature, thus error
result should be `cannot resolve 'mean(t.c)' due to data type mismatch:
function average requires numeric or interval types, not boolean`
This is because
1. The mean(boolean) in HAVING was not marked as resolved in
`ResolveFunctions` rule.
2. Thus in `ResolveAggregationFunctions`, the `TempResolvedColumn` as a
wrapper in `mean(TempResolvedColumn(t.c))` cannot be removed (only resolved AGG
can remove its’s `TempResolvedColumn`).
3. Thus in a later batch rule applying, `TempResolvedColumn` was reverted
and it becomes mean(`t.c`), so mean loses the information about t.c.
4. Thus at the last step, the analyzer can only report t.c not found.
mean(boolean) in HAVING is not marked as resolved in {{ResolveFunctions}}
rule because
1. It uses Expression default `resolved` field population code
{code:java}
lazy val resolved: Boolean = childrenResolved &&
checkInputDataTypes().isSuccess {code}
2. During the analyzing, mean(boolean) is mean(TempResolveColumn(boolean),
thus childrenResolved is true.
3. however checkInputDataTypes() will be false
([Average.scala#L55|[https://github.com/apache/spark/blob/74ebef243c18e7a8f32bf90ea75ab6afed9e3132/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Average.scala#L55])]
4. Thus eventually Average's `resolved` will be false, but it leads to
wrong error message.
### Why are the changes needed?
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Improve error message so users can better debug their query.
### Does this PR introduce _any_ user-facing change?
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Yes. This will change user-facing error message.
### How was this patch tested?
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Unit Test
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