Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/17191#discussion_r112173197
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -161,6 +161,8 @@ class Analyzer(
HandleNullInputsForUDF),
Batch("FixNullability", Once,
FixNullability),
+ Batch("ResolveAggAliasInGroupBy", Once,
+ ResolveAggAliasInGroupBy),
--- End diff --
Finally, I found we couldn't easily put the two rule outside `Resolution`
batch. If we put them outside `Resolution` batch, upper operators depending on
`Aggregate` resolutions (that is, `Aggregate.resolved`) cannot resolve their
own expressions because grouping keys are unresolved during processing
`Resolution` batch. IIUC since `ResolveOrdinalInOrderByAndGroupBy` has the same
limitation, we put it inside `Resolution` batch. For example, if we put the two
rule outside `Resolution` batch, we could get an exception below;
```
scala> sql("""select a as k, count(b) from (select 1 as a, 1 as b) group by
k having k = 1""").show
org.apache.spark.sql.AnalysisException: cannot resolve '`k`' given input
columns: [k, count(b)]; line 1 pos 71;
'Filter ('k = 1)
+- Aggregate [a#71], [a#71 AS k#73, count(b#72) AS count(b)#75L]
+- Project [1 AS a#71, 1 AS b#72]
+- OneRowRelation$
```
So, we put back `ResolveAggAliasInGroupBy` inside `Resolution` batch and
add a test case for that.
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