You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@spark.apache.org by "Matei Zaharia (JIRA)" <ji...@apache.org> on 2014/09/10 02:16:28 UTC

[jira] [Created] (SPARK-3467) Python BatchedSerializer should dynamically lower batch size for large objects

Matei Zaharia created SPARK-3467:
------------------------------------

             Summary: Python BatchedSerializer should dynamically lower batch size for large objects
                 Key: SPARK-3467
                 URL: https://issues.apache.org/jira/browse/SPARK-3467
             Project: Spark
          Issue Type: Improvement
          Components: PySpark
            Reporter: Matei Zaharia


If you try caching largish objects in Python, you will get a crash sooner than you would in Scala / Java because Python automatically batches them. I believe the default batch size is 10, though it may be 1024. But maybe we can start by pickling the first object and using a smaller batch size if it is large.



--
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