Github user markhamstra commented on the pull request:
https://github.com/apache/spark/pull/27#issuecomment-36277558
I see two issues: 1) The deterministic nature of the current scheduler
places tasks on the same small set of machines while leaving others largely
unused; 2) There is no rebalancing of partitions across worker nodes when new
nodes are added to the cluster. Neither LRU nor randomization really addresses
the rebalancing issue, and LRU is only a little better than randomization in
addressing the unused workers issue, so I think the additional complexity of
LRU weighs against it -- at least until such time as we have evidence that
random isn't adequate.
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