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Posted to issues@spark.apache.org by "Cheng Lian (JIRA)" <ji...@apache.org> on 2015/09/23 02:38:04 UTC
[jira] [Updated] (SPARK-10705) Stop converting internal rows to
external rows in DataFrame.toJSON
[ https://issues.apache.org/jira/browse/SPARK-10705?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Cheng Lian updated SPARK-10705:
-------------------------------
Assignee: Liang-Chi Hsieh
> Stop converting internal rows to external rows in DataFrame.toJSON
> ------------------------------------------------------------------
>
> Key: SPARK-10705
> URL: https://issues.apache.org/jira/browse/SPARK-10705
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.3.1, 1.4.1, 1.5.0
> Reporter: Cheng Lian
> Assignee: Liang-Chi Hsieh
>
> {{DataFrame.toJSON}} uses {{DataFrame.mapPartitions}}, which converts internal rows to external rows. We can use {{queryExecution.toRdd.mapPartitions}} instead for better performance.
> Another issue is that, for UDT values, {{serialize}} produces internal types. So currently we must deal with both internal and external types within {{toJSON}} (see [here|https://github.com/apache/spark/pull/8806/files#diff-0f04c36e499d4dcf6931fbd62b3aa012R77]), which is pretty weird.
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