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2 changes: 1 addition & 1 deletion articles/hdinsight/spark/optimize-memory-usage.md
Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ If you're using Apache Hadoop YARN, then YARN controls the memory used by all co

To address 'out of memory' messages, try:

* Review DAG Management Shuffles. Reduce by map-side reducting, pre-partition (or bucketize) source data, maximize single shuffles, and reduce the amount of data sent.
* Review DAG Management Shuffles. Reduce by map-side reducing, pre-partition (or bucketize) source data, maximize single shuffles, and reduce the amount of data sent.
* Prefer `ReduceByKey` with its fixed memory limit to `GroupByKey`, which provides aggregations, windowing, and other functions but it has ann unbounded memory limit.
* Prefer `TreeReduce`, which does more work on the executors or partitions, to `Reduce`, which does all work on the driver.
* Use DataFrames rather than the lower-level RDD objects.
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