You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Dongjoon Hyun (Jira)" <ji...@apache.org> on 2020/03/16 22:51:06 UTC

[jira] [Updated] (SPARK-30474) Writing data to parquet with dynamic partitionOverwriteMode should not do the folder rename in commitjob stage

     [ https://issues.apache.org/jira/browse/SPARK-30474?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Dongjoon Hyun updated SPARK-30474:
----------------------------------
    Affects Version/s:     (was: 3.0.0)
                       3.1.0

> Writing data to parquet with dynamic partitionOverwriteMode should not do the folder rename in commitjob stage
> --------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-30474
>                 URL: https://issues.apache.org/jira/browse/SPARK-30474
>             Project: Spark
>          Issue Type: Improvement
>          Components: Input/Output
>    Affects Versions: 3.1.0
>            Reporter: Zaisheng Dai
>            Priority: Minor
>
> In the current spark implementation if you set,
> {code:java}
> spark.sql.sources.partitionOverwriteMode=dynamic
> {code}
> even with 
> {code:java}
> mapreduce.fileoutputcommitter.algorithm.version=2
> {code}
> it would still rename the partition folder *sequentially* in commitJob stage as shown here: 
> [https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/internal/io/HadoopMapReduceCommitProtocol.scala#L188]
> [https://github.com/apache/spark/blob/branch-2.4/core/src/main/scala/org/apache/spark/internal/io/HadoopMapReduceCommitProtocol.scala#L184]
>  
> This is very slow in cloud storage. We should commit the data similar to FileOutputCommitter v2?
>  



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org