Minor Description
We should avoid the same aggregate function being evaluated more than once, and this is what has been stated in the code comment below (patterns.scala:206). However things didn't work as expected.
// 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
// be used to re-write expressions so that they reference the single copy of the
// aggregate function which actually gets computed.
For example, the physical plan of
SELECT a, max(b+1), max(b+1) + 1 FROM testData2 GROUP BY a
was
HashAggregate(keys=[a#23], functions=[max((b#24 + 1)), max((b#24 + 1))], output=[a#23, max((b + 1))#223, (max((b + 1)) + 1)#224]) +- HashAggregate(keys=[a#23], functions=[partial_max((b#24 + 1)), partial_max((b#24 + 1))], output=[a#23, max#231, max#232]) +- SerializeFromObject [assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData2, true]).a AS a#23, assertnotnull(input[0, org.apache.spark.sql.test.SQLTestData$TestData2, true]).b AS b#24] +- Scan ExternalRDDScan[obj#22]
, where in each HashAggregate there were two identical aggregate functions "max(b#24 + 1)".
