GitHub user andrewor14 reopened a pull request:
https://github.com/apache/spark/pull/3353
[SPARK-4480] Avoid many small spills in external data structures
**Summary.** Currently, we may spill many small files in
`ExternalAppendOnlyMap` and `ExternalSorter`. The underlying root cause of this
is summarized in
[SPARK-4452](https://issues.apache.org/jira/browse/SPARK-4452). This PR does
not address this root cause, but simply provides the guarantee that we never
spill the in-memory data structure if its size is less than a hard-coded
threshold of 5MB.
**Symptom.** Each spill is orders of magnitude smaller than 1MB, and there
are many spills. In environments where the ulimit is set, this frequently
causes "too many open file" exceptions observed in
[SPARK-3633](https://issues.apache.org/jira/browse/SPARK-3633).
```
14/11/13 19:20:43 INFO collection.ExternalSorter: Thread 60 spilling
in-memory batch of 4792 B to disk (292769 spills so far)
14/11/13 19:20:43 INFO collection.ExternalSorter: Thread 60 spilling
in-memory batch of 4760 B to disk (292770 spills so far)
14/11/13 19:20:43 INFO collection.ExternalSorter: Thread 60 spilling
in-memory batch of 4520 B to disk (292771 spills so far)
14/11/13 19:20:43 INFO collection.ExternalSorter: Thread 60 spilling
in-memory batch of 4560 B to disk (292772 spills so far)
14/11/13 19:20:43 INFO collection.ExternalSorter: Thread 60 spilling
in-memory batch of 4792 B to disk (292773 spills so far)
14/11/13 19:20:43 INFO collection.ExternalSorter: Thread 60 spilling
in-memory batch of 4784 B to disk (292774 spills so far)
```
**Reproduction.** I ran the following on a small 4-node cluster with 512MB
executors. Note that the back-to-back shuffle here is necessary for reasons
described in [SPARK-4522](https://issues.apache.org/jira/browse/SPARK-4452).
The second shuffle is a `reduceByKey` because it performs a map-side combine.
```
sc.parallelize(1 to 100000000, 100)
.map { i => (i, i) }
.groupByKey()
.reduceByKey(_ ++ _)
.count()
```
Before the change, I notice that each thread may spill up to 1000 times,
and the size of each spill is on the order of 10KB. After the change, each
thread spills only up to 20 times in the worst case, and the size of each spill
is on the order of 1MB.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/andrewor14/spark avoid-small-spills
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/3353.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 #3353
----
commit a9197768432ef8446d4c1072e247c313356ae229
Author: Andrew Or <[email protected]>
Date: 2014-11-19T01:46:09Z
Avoid many small spills
commit f4736e3d4a7bc3825e6c13a14f4c0b9ef04a8b86
Author: Andrew Or <[email protected]>
Date: 2014-11-19T04:10:23Z
Fix tests
Unfortunately we have to expose the config here to keep the
test duration reasonably low.
commit 27d6966f4bcfd3bc0a5ae5c061b5d1935045883e
Author: Andrew Or <[email protected]>
Date: 2014-11-19T18:24:38Z
Merge branch 'master' of github.com:apache/spark into avoid-small-spills
Conflicts:
core/src/main/scala/org/apache/spark/util/collection/Spillable.scala
----
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
