You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2015/05/15 15:16:59 UTC

[jira] [Commented] (SPARK-4808) Spark fails to spill with small number of large objects

    [ https://issues.apache.org/jira/browse/SPARK-4808?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14545464#comment-14545464 ] 

Sean Owen commented on SPARK-4808:
----------------------------------

I think this is considered resolved now for 1.4 after https://github.com/apache/spark/commit/3be92cdac30cf488e09dbdaaa70e5c4cdaa9a099 ? but not 1.3.
Maybe [~andrewor14] can confirm.

> Spark fails to spill with small number of large objects
> -------------------------------------------------------
>
>                 Key: SPARK-4808
>                 URL: https://issues.apache.org/jira/browse/SPARK-4808
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.0.2, 1.1.0, 1.2.0, 1.2.1
>            Reporter: Dennis Lawler
>
> Spillable's maybeSpill does not allow spill to occur until at least 1000 elements have been spilled, and then will only evaluate spill every 32nd element thereafter.  When there is a small number of very large items being tracked, out-of-memory conditions may occur.
> I suspect that this and the every-32nd-element behavior was to reduce the impact of the estimateSize() call.  This method was extracted into SizeTracker, which implements its own exponential backup for size estimation, so now we are only avoiding using the resulting estimated size.



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

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