Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/8973#discussion_r41308029
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/functions.scala
---
@@ -26,7 +26,7 @@ import org.apache.spark.sql.catalyst.dsl.expressions._
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.types._
-case class Average(child: Expression) extends AlgebraicAggregate {
+case class Average(child: Expression) extends ExpressionAggregateFunction {
--- End diff --
@rxin and I think that algebraic aggregate is potentially confusing because
the [Jim Gray Data Cube paper](http://arxiv.org/pdf/cs/0701155.pdf) already
defined the term "algebraic aggregate" to mean something slightly differently
than how we're using it here. Technically, an algebraic aggregate (in the Gray
terminology) could be implemented via an imperative aggregation function.
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