Details
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Improvement
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Status: Resolved
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Minor
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Resolution: Invalid
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2.1.0
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None
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None
Description
As part of benchmarking this change: https://github.com/apache/spark/pull/15505 and alternatives, shivaram and I found that moving task serialization from TaskSetManager (which happens as part of the TaskSchedulerImpl's thread) to CoarseGranedSchedulerBackend leads to approximately a 10% reduction in job runtime for a job that counted 10,000 partitions (that each had 1 int) using 20 machines. Similar performance improvements were reported in the pull request linked above. This would appear to be because the TaskSchedulerImpl thread is the bottleneck, so moving serialization to CGSB reduces runtime. This change may not improve runtime (and could potentially worsen runtime) in scenarios where the CGSB thread is the bottleneck (e.g., if tasks are very large, so calling launch to send the tasks to the executor blocks on the network).
One benefit of implementing this change is that it makes it easier to parallelize the serialization of tasks (different tasks could be serialized by different threads). Another benefit is that all of the serialization occurs in the same place (currently, the Task is serialized in TaskSetManager, and the TaskDescription is serialized in CGSB).
I'm not totally convinced we should fix this because it seems like there are better ways of reducing the serialization time (e.g., by re-using a single serialized object with the Task/jars/files and broadcasting it for each stage) but I wanted to open this JIRA to document the discussion.
cc witgo
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