[ 
https://issues.apache.org/jira/browse/SPARK-4452?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14218289#comment-14218289
 ] 

Tianshuo Deng commented on SPARK-4452:
--------------------------------------

Hi,
While I'm working on this ticket, I have an related question:
I noticed an extra constraint in the usage of ExternalAppendOnlyMap. 
Even in the current implementation(master), If an ExternalAppendOnlyMap 
exported a iterator(spilled), you can not get the iterator again, since the 
memory iterator is destructive.
But in our unit tests, the constraint seems to be ignored... many tests are 
calling iterator multiple times. It works because the data is small and does 
not trigger the spilling in unit test.

But I just want to confirm, if it's ok I explicitly adding this constraint to 
the code and unit test: Iterator of an ExternalAppendOnlyMap can only be 
exported once

> Shuffle data structures can starve others on the same thread for memory 
> ------------------------------------------------------------------------
>
>                 Key: SPARK-4452
>                 URL: https://issues.apache.org/jira/browse/SPARK-4452
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.1.0
>            Reporter: Tianshuo Deng
>            Assignee: Tianshuo Deng
>            Priority: Critical
>
> When an Aggregator is used with ExternalSorter in a task, spark will create 
> many small files and could cause too many files open error during merging.
> Currently, ShuffleMemoryManager does not work well when there are 2 spillable 
> objects in a thread, which are ExternalSorter and ExternalAppendOnlyMap(used 
> by Aggregator) in this case. Here is an example: Due to the usage of mapside 
> aggregation, ExternalAppendOnlyMap is created first to read the RDD. It may 
> ask as much memory as it can, which is totalMem/numberOfThreads. Then later 
> on when ExternalSorter is created in the same thread, the 
> ShuffleMemoryManager could refuse to allocate more memory to it, since the 
> memory is already given to the previous requested 
> object(ExternalAppendOnlyMap). That causes the ExternalSorter keeps spilling 
> small files(due to the lack of memory)
> I'm currently working on a PR to address these two issues. It will include 
> following changes:
> 1. The ShuffleMemoryManager should not only track the memory usage for each 
> thread, but also the object who holds the memory
> 2. The ShuffleMemoryManager should be able to trigger the spilling of a 
> spillable object. In this way, if a new object in a thread is requesting 
> memory, the old occupant could be evicted/spilled. Previously the spillable 
> objects trigger spilling by themselves. So one may not trigger spilling even 
> if another object in the same thread needs more memory. After this change The 
> ShuffleMemoryManager could trigger the spilling of an object if it needs to.
> 3. Make the iterator of ExternalAppendOnlyMap spillable. Previously 
> ExternalAppendOnlyMap returns an destructive iterator and can not be spilled 
> after the iterator is returned. This should be changed so that even after the 
> iterator is returned, the ShuffleMemoryManager can still spill it.
> Currently, I have a working branch in progress: 
> https://github.com/tsdeng/spark/tree/enhance_memory_manager. Already made 
> change 3 and have a prototype of change 1 and 2 to evict spillable from 
> memory manager, still in progress. I will send a PR when it's done.
> Any feedback or thoughts on this change is highly appreciated !



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to