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Posted to issues@spark.apache.org by "holdenk (JIRA)" <ji...@apache.org> on 2016/06/11 03:29:21 UTC
[jira] [Updated] (SPARK-15369) Investigate selectively using Jython
for parts of PySpark
[ https://issues.apache.org/jira/browse/SPARK-15369?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
holdenk updated SPARK-15369:
----------------------------
Description: Transferring data from the JVM to the Python executor can be a substantial bottleneck. While Jython is not suitable for all UDFs or map functions, it may be suitable for some simple ones. We should investigate the option of using Jython to accelerate these small functions. (was: Transfering data from the JVM to the Python executor can be a substantial bottleneck. While JYthon is not suitable for all UDFs or map functions, it may be suitable for some simple ones. We should investigate the option of using JYthon to accelerate these small functions.)
> Investigate selectively using Jython for parts of PySpark
> ---------------------------------------------------------
>
> Key: SPARK-15369
> URL: https://issues.apache.org/jira/browse/SPARK-15369
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Reporter: holdenk
> Priority: Minor
>
> Transferring data from the JVM to the Python executor can be a substantial bottleneck. While Jython is not suitable for all UDFs or map functions, it may be suitable for some simple ones. We should investigate the option of using Jython to accelerate these small functions.
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