[jira] [Created] (SPARK-20994) Alleviate memory pressure in StreamManager

["jin xing (JIRA)" <ji...@apache.org>]

jin xing created SPARK-20994:
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             Summary: 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


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}}

Conceptually, there is no need to send the blocks list in step-1. Client can send the blockId in Step-2. Receiving {{ChunkFetchRequest}}, server can check if the chunkId is in local block manager and send back response. 
Thus memory cost can be improved.



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