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authorKay Ousterhout <kayousterhout@gmail.com>2014-02-06 16:10:48 -0800
committerPatrick Wendell <pwendell@gmail.com>2014-02-06 16:10:48 -0800
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Merge pull request #321 from kayousterhout/ui_kill_fix. Closes #321.
Inform DAG scheduler about all started/finished tasks. Previously, the DAG scheduler was not always informed when tasks started and finished. The simplest example here is for speculated tasks: the DAGScheduler was only told about the first attempt of a task, meaning that SparkListeners were also not told about multiple task attempts, so users can't see what's going on with speculation in the UI. The DAGScheduler also wasn't always told about finished tasks, so in the UI, some tasks will never be shown as finished (this occurs, for example, if a task set gets killed). The other problem is that the fairness accounting was wrong -- the number of running tasks in a pool was decreased when a task set was considered done, even if all of its tasks hadn't yet finished. Author: Kay Ousterhout <kayousterhout@gmail.com> == Merge branch commits == commit c8d547d0f7a17f5a193bef05f5872b9f475675c5 Author: Kay Ousterhout <kayousterhout@gmail.com> Date: Wed Jan 15 16:47:33 2014 -0800 Addressed Reynold's review comments. Always use a TaskEndReason (remove the option), and explicitly signal when we don't know the reason. Also, always tell DAGScheduler (and associated listeners) about started tasks, even when they're speculated. commit 3fee1e2e3c06b975ff7f95d595448f38cce97a04 Author: Kay Ousterhout <kayousterhout@gmail.com> Date: Wed Jan 8 22:58:13 2014 -0800 Fixed broken test and improved logging commit ff12fcaa2567c5d02b75a1d5db35687225bcd46f Author: Kay Ousterhout <kayousterhout@gmail.com> Date: Sun Dec 29 21:08:20 2013 -0800 Inform DAG scheduler about all finished tasks. Previously, the DAG scheduler was not always informed when tasks finished. For example, when a task set was aborted, the DAG scheduler was never told when the tasks in that task set finished. The DAG scheduler was also never told about the completion of speculated tasks. This led to confusion with SparkListeners because information about the completion of those tasks was never passed on to the listeners (so in the UI, for example, some tasks will never be shown as finished). The other problem is that the fairness accounting was wrong -- the number of running tasks in a pool was decreased when a task set was considered done, even if all of its tasks hadn't yet finished.
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