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| author | Sital Kedia <skedia@fb.com> | 2017-03-17 09:33:45 -0500 |
|---|---|---|
| committer | Imran Rashid <irashid@cloudera.com> | 2017-03-17 09:33:58 -0500 |
| commit | 7b5d873aef672aa0aee41e338bab7428101e1ad3 (patch) | |
| tree | cf93435eaa5644ddf0c431065f340d9e5fab7414 /python/setup.py | |
| parent | 13538cf3dd089222c7e12a3cd6e72ac836fa51ac (diff) | |
| download | spark-7b5d873aef672aa0aee41e338bab7428101e1ad3.tar.gz spark-7b5d873aef672aa0aee41e338bab7428101e1ad3.tar.bz2 spark-7b5d873aef672aa0aee41e338bab7428101e1ad3.zip | |
[SPARK-13369] Add config for number of consecutive fetch failures
The previously hardcoded max 4 retries per stage is not suitable for all cluster configurations. Since spark retries a stage at the sign of the first fetch failure, you can easily end up with many stage retries to discover all the failures. In particular, two scenarios this value should change are (1) if there are more than 4 executors per node; in that case, it may take 4 retries to discover the problem with each executor on the node and (2) during cluster maintenance on large clusters, where multiple machines are serviced at once, but you also cannot afford total cluster downtime. By making this value configurable, cluster managers can tune this value to something more appropriate to their cluster configuration.
Unit tests
Author: Sital Kedia <skedia@fb.com>
Closes #17307 from sitalkedia/SPARK-13369.
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