zhengruifeng commented on issue #26803: [SPARK-30178][ML] RobustScaler support large numFeatures URL: https://github.com/apache/spark/pull/26803#issuecomment-564413213 @srowen I impl a simple `treeAggregateByKey` [here](https://github.com/apache/spark/compare/master...zhengruifeng:treeAggByKey?expand=1), and made several local tests like: ```scala val rdd = sc.range(0, 10000, 1, 100) val rdd2 = rdd.map{i => (i % 10, i)} val rdd3 = rdd2.treeAggregateByKey(0.0, new HashPartitioner(3))(_+_, _+_, 2) rdd3.collect ``` and ran successfully.  BTW, it is reasonable to call `compress` before reduce tasks, so maybe a `aggregateByKeyWithinPartitions` is needed? Then we can call `compress` after locally aggregation within each partition. I guess they maybe common functions and we add this method in RDD/PairRDD?
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