Github user liancheng commented on the pull request:
https://github.com/apache/spark/pull/862#issuecomment-44348205
Ah, realized what's wrong, I need at lease 1 non-partial aggregation:
```
scala> sql("SELECT AVG(key), COUNT(DISTINCT key) FROM
src1").collect().foreach(println)
...
== Query Plan ==
Aggregate false, [], [AVG(key#672) AS c0#668,COUNT(DISTINCT key#672}) AS
c1#669]
Exchange SinglePartition
HiveTableScan [key#672], (MetastoreRelation default, src1, None), None),
which is now runnable
14/05/28 07:21:31 INFO scheduler.DAGScheduler: Submitting 1 missing tasks
from Stage 12 (SchemaRDD[67] at RDD at SchemaRDD.scala:98
== Query Plan ==
Aggregate false, [], [AVG(key#672) AS c0#668,COUNT(DISTINCT key#672}) AS
c1#669]
Exchange SinglePartition
HiveTableScan [key#672], (MetastoreRelation default, src1, None), None)
...
[142.24,15]
```
And it does lead to the wrong answer.
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