Closes #16. Use a single shared queue between all threads in each workload mapper. #19
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…ared queue between all threads in a single workload mapper.
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One question, why is this IP based partitioning? To me, it looks like every command gets put into the same queue, and the threads pick up the commands regardless of IP. Am I missing something? |
xkrogen
changed the title
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Sorry, the commit message was a bit incorrect. I have updated the title & the description to more fully explain the issue we are solving here. |
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LGTM, +1 |
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On a single mapper in the workload replay, currently tasks are distributed to threads in a path-partitioned manner. This results in bad skew issues, where one thread can fall very far behind because it is overloaded. Thus, although all of the issues on a specific path get executed in order (though late), the ordering with other paths is very far out of sync. It is better to let some operations on the same path occur out of order so that (a) overall everything stays more in sync and (b) no thread falls far behind (which can delay the entire mapper from completing).