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author | Reynold Xin <rxin@apache.org> | 2013-12-18 22:22:21 -0800 |
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committer | Reynold Xin <rxin@apache.org> | 2013-12-18 22:22:21 -0800 |
commit | bfba5323bedca3aa021e3cd9267d88379e767a92 (patch) | |
tree | 0b196617549ded8c28408b1d3cfba2a126289716 /python/pyspark/files.py | |
parent | c64a53a48b894c3b5f4631eb0549c3292cd3d167 (diff) | |
parent | 293a0af5a1def95e47d9188f42957083f5adf3b8 (diff) | |
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Merge pull request #247 from aarondav/minor
Increase spark.akka.askTimeout default to 30 seconds
In experimental clusters we've observed that a 10 second timeout was insufficient, despite having a low number of nodes and relatively small workload (16 nodes, <1.5 TB data). This would cause an entire job to fail at the beginning of the reduce phase.
There is no particular reason for this value to be small as a timeout should only occur in an exceptional situation.
Also centralized the reading of spark.akka.askTimeout to AkkaUtils (surely this can later be cleaned up to use Typesafe).
Finally, deleted some lurking implicits. If anyone can think of a reason they should still be there, please let me know.
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