[
https://issues.apache.org/jira/browse/SPARK-30101?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
sam updated SPARK-30101:
------------------------
Description:
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.
.......................
According to below comments, it uses spark.sql.shuffle.partitions, which needs
documenting in configuration.
> Default number of partitions in RDDs returned by transformations like join,
> reduceByKey, and parallelize when not set by user.
in https://spark.apache.org/docs/latest/configuration.html should say
> Default number of partitions in RDDs, but not DS/DF (see
> spark.sql.shuffle.partitions) returned by transformations like join,
> reduceByKey, and parallelize when not set by user.
was:
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.
> spark.sql.shuffle.partitions is not in Configuration docs, but a very
> critical parameter
> ----------------------------------------------------------------------------------------
>
> 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.
> .......................
> According to below comments, it uses spark.sql.shuffle.partitions, which
> needs documenting in configuration.
> > Default number of partitions in RDDs returned by transformations like join,
> > reduceByKey, and parallelize when not set by user.
> in https://spark.apache.org/docs/latest/configuration.html should say
> > Default number of partitions in RDDs, but not DS/DF (see
> > spark.sql.shuffle.partitions) returned by transformations like join,
> > reduceByKey, and parallelize when not set by user.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
