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From andrewor14 <>
Subject [GitHub] spark pull request: [WIP][SPARK-3795] Heuristics for dynamically s...
Date Mon, 20 Oct 2014 23:40:42 GMT
Github user andrewor14 commented on the pull request:
    @kayousterhout @sryza Correct me if I'm wrong, but I believe grabbing as many executors
as needed in MR/Tez comes for free in these two frameworks because a container is supposed
to be short-lived (unless you explicitly specify to reuse containers). Thus, it is much easier
to understand this policy in these contexts because the same policy is used for normal scheduling
of tasks. In Spark, however, executors are mostly coarse-grained, so we have to use the ratio
of pending tasks per executor to achieve something similar. However, this is more complicated
for Spark because the correlation between number of executors added and the number of pending
tasks these executors will be scheduled is less clear.

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