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From "Aman Omer (Jira)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-30101) Dataset distinct does not respect spark.default.parallelism
Date Tue, 03 Dec 2019 04:17:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-30101?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16986594#comment-16986594
] 

Aman Omer commented on SPARK-30101:
-----------------------------------

I am checking this.

> Dataset distinct does not respect spark.default.parallelism
> -----------------------------------------------------------
>
>                 Key: SPARK-30101
>                 URL: https://issues.apache.org/jira/browse/SPARK-30101
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.4.0, 2.4.4
>            Reporter: sam
>            Priority: Major
>
> I'm creating a `SparkSession` like this:
> ```
> SparkSession
>       .builder().appName("foo").master("local")
>       .config("spark.default.parallelism", 2).getOrCreate()
> ```
> when I run
> ```
> ((1 to 10) ++ (1 to 10)).toDS().distinct().count()
> ```
> I get 200 partitions
> ```
> 19/12/02 10:29:34 INFO TaskSchedulerImpl: Adding task set 1.0 with 200 tasks
> ...
> 19/12/02 10:29:34 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 2) in 46 ms
on localhost (executor driver) (1/200)
> ```
> It is the `distinct` that is broken since `ds.rdd.getNumPartitions` gives `2`, while
`ds.distinct().rdd.getNumPartitions` gives `200`.  `ds.rdd.groupBy(identity).map(_._2.head)`
and `ds.rdd.distinct()` work correctly.
> Finally I notice that the good old `RDD` interface has a `distinct` that accepts `numPartitions`
partitions, while `Dataset` does not.



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