Github user rednaxelafx commented on a diff in the pull request: https://github.com/apache/spark/pull/19488#discussion_r144651235 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/planning/patterns.scala --- @@ -205,14 +205,17 @@ 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 => + // aggregate function which actually gets computed. Note that aggregate expressions + // should always be deterministic, so we can use its canonicalized expression as its --- End diff -- @cloud-fan Agreed. e.g. `first()` in Spark SQL is marked as nondeterministic right now (although for the case of `first()` I'd actually believe we should make it deterministic instead, but that's for another story)
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