Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/19488#discussion_r144483555
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/planning/patterns.scala
---
@@ -205,14 +205,15 @@ object PhysicalAggregation {
case logical.Aggregate(groupingExpressions, resultExpressions, child)
=>
// A single aggregate expression might appear multiple times in
resultExpressions.
// In order to avoid evaluating an individual aggregate function
multiple times, we'll
- // build a set of the distinct aggregate expressions and build a
function which can
+ // build a map of the distinct aggregate expressions and build a
function which can
// be used to re-write expressions so that they reference the single
copy of the
// aggregate function which actually gets computed.
- val aggregateExpressions = resultExpressions.flatMap { expr =>
+ val aggregateExpressionMap = resultExpressions.flatMap { expr =>
expr.collect {
- case agg: AggregateExpression => agg
+ case agg: AggregateExpression => (agg.canonicalized,
agg.deterministic) -> agg
--- End diff --
I think non-deterministic functions should not be deduplicated, e.g.
`select max(a + rand()), max(a + rand()) from ...` should still eveluate 2
aggregate funcitions.
my suggestion:
```
val aggregateExpressions = resultExpressions.flatMap { expr =>
expr.collect {
case agg: AggregateExpression => agg
}
}
val aggregateExpressionMap =
aggregateExpressions.filter(_.deterministic).map { agg =>
agg.canonicalized -> agg
}.toMap
```
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