GitHub user szhem opened a pull request:
https://github.com/apache/spark/pull/23083
[SPARK-26114][CORE] ExternalSorter Leak
## What changes were proposed in this pull request?
This pull request fixes
[SPARK-26114](https://issues.apache.org/jira/browse/SPARK-26114) issue that
occurs when trying to reduce the number of partitions by means of coalesce
without shuffling after shuffle-based transformations.
For the following data
```scala
import org.apache.hadoop.io._
import org.apache.hadoop.io.compress._
import org.apache.commons.lang._
import org.apache.spark._
// generate 100M records of sample data
sc.makeRDD(1 to 1000, 1000)
.flatMap(item => (1 to 100000)
.map(i => new Text(RandomStringUtils.randomAlphanumeric(3).toLowerCase)
-> new Text(RandomStringUtils.randomAlphanumeric(1024))))
.saveAsSequenceFile("/tmp/random-strings", Some(classOf[GzipCodec]))
```
and the following job
```scala
import org.apache.hadoop.io._
import org.apache.spark._
import org.apache.spark.storage._
val rdd = sc.sequenceFile("/tmp/random-strings", classOf[Text],
classOf[Text])
rdd
.map(item => item._1.toString -> item._2.toString)
.repartitionAndSortWithinPartitions(new HashPartitioner(1000))
.coalesce(10,false)
.count
```
... executed like the following
```bash
spark-shell \
--num-executors=5 \
--executor-cores=2 \
--master=yarn \
--deploy-mode=client \
--conf spark.executor.memory=1g \
--conf spark.dynamicAllocation.enabled=false \
--conf spark.executor.extraJavaOptions='-XX:+HeapDumpOnOutOfMemoryError
-XX:HeapDumpPath=/tmp -Dio.netty.noUnsafe=true'
```
... executors are always failing with OutOfMemoryErrors.
The main issue is multiple leaks of ExternalSorter references.
For example, in case of 2 tasks per executor it is expected to be 2
simultaneous instances of ExternalSorter per executor but heap dump generated
on OutOfMemoryError shows that there are more ones.
P.S. This PR does not cover cases with CoGroupedRDDs which use
ExternalAppendOnlyMap internally, which itself can lead to OutOfMemoryErrors in
many places.
## How was this patch tested?
- Existing unit tests
- New unit tests
- Job executions on the live environment
Here is the screenshot before applying this patch
Here is the screenshot after applying this patch
And in case of reducing the number of executors even more the job is still
stable
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/szhem/spark SPARK-26114-externalsorter-leak
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/23083.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #23083
----
commit 9ca5ddbeb2022259ec79e60b3e81332466947d90
Author: Sergey Zhemzhitsky <szhemzhitski@...>
Date: 2018-11-05T22:31:59Z
Allow memory consumers and spillables to be optionally unregistered and not
trackable on freeing up the memory
commit bf57de2c9d23c3cbac23817a3d0b6158739ae8aa
Author: Sergey Zhemzhitsky <szhemzhitski@...>
Date: 2018-11-05T22:34:15Z
allow to remove already registered task completion listeners if they dont
need to be fired at task completion
commit e3531acf2751d4ba63e7fa353b66c70d534271df
Author: Sergey Zhemzhitsky <szhemzhitski@...>
Date: 2018-11-05T22:35:31Z
clean up readingIterator on stop
commit baa9656e9d9fa2d006ed6fb98257a213bcace588
Author: Sergey Zhemzhitsky <szhemzhitski@...>
Date: 2018-11-05T22:37:07Z
prevent capturing and holding sub-iterators after completion
commit 3cc54522545f43e0ee9ff9443ba3ea67e5fb9d5b
Author: Sergey Zhemzhitsky <szhemzhitski@...>
Date: 2018-11-05T22:40:13Z
cleaning up resourses as soon as they no longer needed, dont waiting till
the end of the task
commit d36323e7db3d8dc5ec01a2ae46752342ff01fac5
Author: Sergey Zhemzhitsky <szhemzhitski@...>
Date: 2018-11-18T01:01:15Z
adding some unit tests
commit 12075ec265f0d09cd52865bb91155898b9ede523
Author: Sergey Zhemzhitsky <szhemzhitski@...>
Date: 2018-11-18T07:07:27Z
improved docs
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