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Interesting point.
As I understand, the key point is the ShuffleManager ensures that only one
map output file is processed by the reduce task, even when multiple
attempts succeed. So it is not a random selection process. At the reduce
stage, only one copy of the map output needs to be read by the
Hi Spark devs,
I have a question around ShuffleManager: With speculative execution, one
map output file is being created multiple times (by multiple task
attempts). If both attempts succeed, which is to be read by the reduce
task in the next stage? Is any map output as good as any other?
