Minor Description
Right now, we use transformDown explicitly at https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/utils.scala#L105 and https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/utils.scala#L130. We also need to be very clear on using transformDown at https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/utils.scala#L300 and https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/utils.scala#L334 (right now transform means transformDown). The reason we need to use transformDown is when we rewrite final aggregate results, we should always match aggregate functions first. If we use transformUp, it is possible that we match grouping expression first if we use grouping expressions as children of aggregate functions.
There is nothing wrong with our master. We just want to make sure we will not have bugs if we change the behavior of transform (change it from transformDown to Up.), which I think is very unlikely (but just incase).