[jira] [Commented] (SPARK-44512) dataset.sort.select.write.partitionBy sorts wrong column

["Dongjoon Hyun (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-44512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17781169#comment-17781169 ] 

Dongjoon Hyun commented on SPARK-44512:
---------------------------------------

Hi, All. Is this correctness issue valid in branch-3.4/3.5/master? Let me set the `Target Version` to 3.4.2 not to forget.

> dataset.sort.select.write.partitionBy sorts wrong column
> --------------------------------------------------------
>
>                 Key: SPARK-44512
>                 URL: https://issues.apache.org/jira/browse/SPARK-44512
>             Project: Spark
>          Issue Type: Bug
>          Components: Optimizer, SQL
>    Affects Versions: 3.4.1
>            Reporter: Yiu-Chung Lee
>            Priority: Blocker
>              Labels: correctness
>         Attachments: Test-Details-for-Query-0.png, Test-Details-for-Query-1.png
>
>
> (In this example the dataset is of type Tuple3, and the columns are named _1, _2 and _3)
>  
> I found -then when AQE is enabled,- that the following code does not produce sorted output (.drop() also have the same problem), unless spark.sql.optimizer.plannedWrite.enabled is set to false.
> After further investigation, spark actually sorted wrong column in the following code.
> {{dataset.sort("_1")}}
> {{.select("_2", "_3")}}
> {{.write()}}
> {{.partitionBy("_2")}}
> {{.text("output");}}
>  
> (the following workaround is no longer necessary)
> -However, if I insert an identity mapper between select and write, the output would be sorted as expected.-
> -{{dataset = dataset.sort("_1")}}-
> -{{.select("_2", "_3");}}-
> -{{dataset.map((MapFunction<Row, Row>) row -> row, dataset.encoder())}}-
> -{{.write()}}-
> -{{{}.{}}}{{{}partitionBy("_2"){}}}-
> -{{.text("output")}}-
> Below is the complete code that reproduces the problem.



--
This message was sent by Atlassian Jira
(v8.20.10#820010)

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