[jira] [Resolved] (SPARK-21923) Avoid calling reserveUnrollMemoryForThisTask for every record

["Wenchen Fan (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-21923?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Wenchen Fan resolved SPARK-21923.
---------------------------------
       Resolution: Fixed
    Fix Version/s: 2.3.0

Issue resolved by pull request 19135
[https://github.com/apache/spark/pull/19135]

> Avoid calling reserveUnrollMemoryForThisTask for every record
> -------------------------------------------------------------
>
>                 Key: SPARK-21923
>                 URL: https://issues.apache.org/jira/browse/SPARK-21923
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 2.2.0
>            Reporter: Xianyang Liu
>             Fix For: 2.3.0
>
>
> When Spark persist data to Unsafe memory, we call  the method `MemoryStore.putIteratorAsBytes`, which need synchronize the `memoryManager` for every record write. This implementation is not necessary, we can apply for more memory at a time to reduce unnecessary synchronization.
> Test case:
> ```scala
> val start = System.currentTimeMillis()
>     val data = sc.parallelize(0 until Integer.MAX_VALUE, 100)
>       .persist(StorageLevel.OFF_HEAP)
>       .count()
>     println(System.currentTimeMillis() - start)
> ```
> Test result:
> before
> |  27647  |  29108  |  28591  |  28264  |  27232  |
> after
> |  26868  |  26358  |  27767  |  26653  |  26693  |



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