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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2019/06/19 22:23:00 UTC
[jira] [Assigned] (SPARK-28112) Fix Kryo exception perf. bottleneck
in tests due to absence of ML/MLlib classes
[ https://issues.apache.org/jira/browse/SPARK-28112?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-28112:
------------------------------------
Assignee: Apache Spark (was: Josh Rosen)
> Fix Kryo exception perf. bottleneck in tests due to absence of ML/MLlib classes
> -------------------------------------------------------------------------------
>
> Key: SPARK-28112
> URL: https://issues.apache.org/jira/browse/SPARK-28112
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core, Tests
> Affects Versions: 3.0.0
> Reporter: Xiao Li
> Assignee: Apache Spark
> Priority: Major
>
> In a nutshell, it looks like the absence of ML / MLlib classes on the classpath causes code in KryoSerializer to throw and catch ClassNotFoundExceptions whenever instantiating a new serializer in {{newInstance()}}. This isn't a performance problem in production (since MLlib is on the classpath there) but it's a huge issue in tests and appears to account for an enormous amount of test time
> We can address this problem by reducing the total number of ClassNotFoundExceptions by performing the class existence checks once and storing the results in KryoSerializer instances rather than repeating the checks on each {{newInstance()}} call.
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