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https://issues.apache.org/jira/browse/SPARK-19244?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15823965#comment-15823965
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Apache Spark commented on SPARK-19244:
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User 'viirya' has created a pull request for this issue:
https://github.com/apache/spark/pull/16603
> Sort MemoryConsumers according to their memory usage when spilling
> ------------------------------------------------------------------
>
> Key: SPARK-19244
> URL: https://issues.apache.org/jira/browse/SPARK-19244
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Reporter: Liang-Chi Hsieh
>
> In `TaskMemoryManager `, when we acquire memory by calling
> `acquireExecutionMemory` and we can't acquire required memory, we will try to
> spill other memory consumers.
> Currently, we simply iterates the memory consumers in a hash set. Normally
> each time the consumer will be iterated in the same order.
> The first issue is that we might spill additional consumers. For example, if
> consumer 1 uses 10MB, consumer 2 uses 50MB, then consumer 3 acquires 100MB
> but we can only get 60MB and spilling is needed. We might spill both consumer
> 1 and consumer 2. But we actually just need to spill consumer 2 and get the
> required 100MB.
> The second issue is that if we spill consumer 1 in first time spilling. After
> a while, consumer 1 now uses 5MB. Then consumer 4 may acquire some memory and
> spilling is needed again. Because we iterate the memory consumers in the same
> order, we will spill consumer 1 again. So for consumer 1, we will produce
> many small spilling files.
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