[jira] [Created] (SPARK-21591) Implement treeAggregate on Dataset API

["Yanbo Liang (JIRA)" <ji...@apache.org>]

Yanbo Liang created SPARK-21591:
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             Summary: Implement treeAggregate on Dataset API
                 Key: SPARK-21591
                 URL: https://issues.apache.org/jira/browse/SPARK-21591
             Project: Spark
          Issue Type: New Feature
          Components: SQL
    Affects Versions: 2.2.0
            Reporter: Yanbo Liang


The Tungsten execution engine substantially improved the efficiency of memory and CPU for Spark application. However, in MLlib we still not migrate the internal computing workload from {{RDD}} to {{DataFrame}}.
The main block issue is there is no {{treeAggregate}} on {{DataFrame}}. As we all know, {{RDD}} based {{treeAggregate}} reduces the aggregation time by an order of magnitude for  lots of MLlib algorithms(https://databricks.com/blog/2014/09/22/spark-1-1-mllib-performance-improvements.html).
I open this JIRA to discuss to implement {{treeAggregate}} on {{DataFrame}} API and do the performance benchmark related issues.



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