Github user rkarimi commented on the issue:
https://github.com/apache/spark/pull/17972
perhaps related:
Big Random Forest Models (example: 100 or more trees with depth of around
20):
Big models can be trained effectively even on machines with limited RAM
(such
Github user rkarimi closed the pull request at:
https://github.com/apache/spark/pull/16838
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GitHub user rkarimi opened a pull request:
https://github.com/apache/spark/pull/16838
Branch 2.1
Fix Execution Plan:
Remove unnecessary steps of sort from execution plan:
df.sort(...).count()
It should not do the sort! It should be absolutely fast if
