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Posted to issues@spark.apache.org by "Nick Pentreath (JIRA)" <ji...@apache.org> on 2017/05/09 08:08:04 UTC
[jira] [Assigned] (SPARK-11968) ALS recommend all methods spend
most of time in GC
[ https://issues.apache.org/jira/browse/SPARK-11968?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Nick Pentreath reassigned SPARK-11968:
--------------------------------------
Assignee: Peng Meng (was: Nick Pentreath)
> ALS recommend all methods spend most of time in GC
> --------------------------------------------------
>
> Key: SPARK-11968
> URL: https://issues.apache.org/jira/browse/SPARK-11968
> Project: Spark
> Issue Type: Improvement
> Components: ML, MLlib
> Affects Versions: 1.5.2, 1.6.0
> Reporter: Joseph K. Bradley
> Assignee: Peng Meng
> Fix For: 2.2.1
>
>
> After adding recommendUsersForProducts and recommendProductsForUsers to ALS in spark-perf, I noticed that it takes much longer than ALS itself. Looking at the monitoring page, I can see it is spending about 8min doing GC for each 10min task. That sounds fixable. Looking at the implementation, there is clearly an opportunity to avoid extra allocations: [https://github.com/apache/spark/blob/e6dd237463d2de8c506f0735dfdb3f43e8122513/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala#L283]
> CC: [~mengxr]
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