Github user chenghao-intel commented on the pull request:
https://github.com/apache/spark/pull/867#issuecomment-47871283
This is very helpful when the partition can not fit in memory. However, I
think we'd better keep previous implementation; Aggregator in spark is for very
typical scenario, but we do have many algorithms / ways to optimize the
aggregation in SQL for performance, hence tightly coupled with Spark Aggregator
may not a good idea for further improvement.
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