[jira] [Assigned] (SPARK-25062) Clean up BlockLocations in FileStatus objects

["Apache Spark (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-25062?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-25062:
------------------------------------

    Assignee: Apache Spark

> Clean up BlockLocations in FileStatus objects
> ---------------------------------------------
>
>                 Key: SPARK-25062
>                 URL: https://issues.apache.org/jira/browse/SPARK-25062
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.2.2
>            Reporter: andrzej.stankevich@gmail.com
>            Assignee: Apache Spark
>            Priority: Major
>
> When Spark lists collection of files it does it on a driver or creates tasks to list files depending on number of files. here [https://github.com/apache/spark/blob/branch-2.2/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InMemoryFileIndex.scala#L170]
> If spark creates tasks to list files each task creates one FileStatus object per file. Before sending  FileStatus to a driver Spark converts FileStatus to SerializableFileStatus. On driver side Spark turns SerializableFileStatus back to FileStatus and it also creates BlockLocation object for each FileStatus using 
>  
> {code:java}
> new BlockLocation(loc.names, loc.hosts, loc.offset, loc.length) 
> {code}
>  
> After deserialization on a driver side BlockLocation doesn't have a lot of information that original HDFSBlockLocation had.
>  
> If Spark does listing on a driver side FileStatus object has HSDFBlockLocation objects and they have a lot of info that Spark doesn't use. Because of this FileStatus objects takes more memory than if it would created on executor side.
>  
> Later Spark puts all this objects into _SharedInMemoryCache_ and that cache takes 2.2x more memory if files were listed on driver side than if they were listed on executor side.
>  
> In our case _SharedInMemoryCache_ takes 125M when we do scan on executors  and 270M when we do it on a driver. It is for about 19000 files.



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