zunwen you created SPARK-18946:
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Summary: treeAggregate will be low effficiency when aggregate high
dimension vector in ML algorithm
Key: SPARK-18946
URL: https://issues.apache.org/jira/browse/SPARK-18946
Project: Spark
Issue Type: Improvement
Components: ML, MLlib
Reporter: zunwen you
In many machine learning algorithms, we have to treeAggregate large
vectors/arrays due to the large number of features. Unfortunately, the
treeAggregate operation of RDD will be low efficiency when the dimension of
vectors/arrays is bigger than million. Because high dimension of vector/array
always occupy more than 100MB Memory, transferring a 100MB element among
executors is pretty low efficiency in Spark.
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