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https://issues.apache.org/jira/browse/SPARK-20994?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan resolved SPARK-20994.
---------------------------------
Resolution: Fixed
Fix Version/s: 2.3.0
Issue resolved by pull request 18231
[https://github.com/apache/spark/pull/18231]
> Alleviate memory pressure in StreamManager
> ------------------------------------------
>
> Key: SPARK-20994
> URL: https://issues.apache.org/jira/browse/SPARK-20994
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 2.1.1
> Reporter: jin xing
> Fix For: 2.3.0
>
>
> In my cluster, we are suffering from OOM of shuffle-service.
> We found that a lot of executors are fetching blocks from a single
> shuffle-service. Analyzing the memory, we found that the
> blockIds({{shuffle_shuffleId_mapId_reduceId}}) takes about 1.5GBytes.
> In current code, chunks are fetched from shuffle service in two steps:
> Step-1. Send {{OpenBlocks}}, which contains the blocks list to to fetch;
> Step-2. Fetch the consecutive chunks from shuffle-service by {{streamId}} and
> {{chunkIndex}}
> Thus memory cost can be improved for step-1.
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