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Posted to dev@aurora.apache.org by "Bill Farner (JIRA)" <ji...@apache.org> on 2014/01/25 19:22:38 UTC
[jira] [Updated] (AURORA-121) Make the preemptor more efficient
[ https://issues.apache.org/jira/browse/AURORA-121?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Bill Farner updated AURORA-121:
-------------------------------
Description:
When {{TaskSchedulerImpl}} fails to find an open slot for a task, it falls back to the preemptor:
{code}
if (!offerQueue.launchFirst(getAssignerFunction(taskId, task))) {
// Task could not be scheduled.
maybePreemptFor(taskId);
return TaskSchedulerResult.TRY_AGAIN;
}
{code}
This can be problematic when the task store is large (O(10k tasks)) and there is a steady supply of PENDING tasks not satisfied by open slots. This will manifest as an overall degraded/slow scheduler, and logs of slow queries used for preemption:
{noformat}
I0125 17:47:36.970 THREAD23 org.apache.aurora.scheduler.storage.mem.MemTaskStore.fetchTasks: Query took 107 ms: TaskQuery(owner:null, environment:null, jobName:null,
taskIds:null, statuses:[KILLING, ASSIGNED, STARTING, RUNNING, RESTARTING], slaveHost:null, instanceIds:null)
{noformat}
Several approaches come to mind to improve this situation (not mutually exclusive):
- (easy) More aggressively back off on tasks that cannot be satisfied
- (easy) Fall back to preemption less frequently
- (easy) Gather the list of slaves from {{AttributeStore}} rather than {{TaskStore}}. This breaks the operation up into many smaller queries and reduces the amount of work in cases where a match is found. However, this would actually create more work when a match is not found, so this approach is probably not helpful by itself.
- (harder) Scan for preemption candidates asynchronously, freeing up the TaskScheduler thread and the storage write lock. Scans could be kicked off by the task scheduler, ideally in a way that doesn't dogpile. This could also be done in a weakly-consistent way to minimally contribute to storage contention.
was:
When {{TaskSchedulerImpl}} fails to find an open slot for a task, it falls back to the preemptor:
{code}
if (!offerQueue.launchFirst(getAssignerFunction(taskId, task))) {
// Task could not be scheduled.
maybePreemptFor(taskId);
return TaskSchedulerResult.TRY_AGAIN;
}
{code}
This can be problematic when the task store is large (O(10k tasks)) and there is a steady supply of PENDING tasks not satisfied by open slots. This will manifest as an overall degraded/slow scheduler, and logs of slow queries used for preemption:
{noformat}
I0125 17:47:36.970 THREAD23 org.apache.aurora.scheduler.storage.mem.MemTaskStore.fetchTasks: Query took 107 ms: TaskQuery(owner:null, environment:null, jobName:null,
taskIds:null, statuses:[KILLING, ASSIGNED, STARTING, RUNNING, RESTARTING], slaveHost:null, instanceIds:null)
{noformat}
Several approaches come to mind to improve this situation:
- (easy) More aggressively back off on tasks that cannot be satisfied
- (easy) Fall back to preemption less frequently
- (harder) Scan for preemption candidates asynchronously, freeing up the TaskScheduler thread and the storage write lock. Scans could be kicked off by the task scheduler, ideally in a way that doesn't dogpile. This could also be done in a weakly-consistent way to minimally contribute to storage contention.
> Make the preemptor more efficient
> ---------------------------------
>
> Key: AURORA-121
> URL: https://issues.apache.org/jira/browse/AURORA-121
> Project: Aurora
> Issue Type: Story
> Components: Scheduler
> Reporter: Bill Farner
>
> When {{TaskSchedulerImpl}} fails to find an open slot for a task, it falls back to the preemptor:
> {code}
> if (!offerQueue.launchFirst(getAssignerFunction(taskId, task))) {
> // Task could not be scheduled.
> maybePreemptFor(taskId);
> return TaskSchedulerResult.TRY_AGAIN;
> }
> {code}
> This can be problematic when the task store is large (O(10k tasks)) and there is a steady supply of PENDING tasks not satisfied by open slots. This will manifest as an overall degraded/slow scheduler, and logs of slow queries used for preemption:
> {noformat}
> I0125 17:47:36.970 THREAD23 org.apache.aurora.scheduler.storage.mem.MemTaskStore.fetchTasks: Query took 107 ms: TaskQuery(owner:null, environment:null, jobName:null,
> taskIds:null, statuses:[KILLING, ASSIGNED, STARTING, RUNNING, RESTARTING], slaveHost:null, instanceIds:null)
> {noformat}
> Several approaches come to mind to improve this situation (not mutually exclusive):
> - (easy) More aggressively back off on tasks that cannot be satisfied
> - (easy) Fall back to preemption less frequently
> - (easy) Gather the list of slaves from {{AttributeStore}} rather than {{TaskStore}}. This breaks the operation up into many smaller queries and reduces the amount of work in cases where a match is found. However, this would actually create more work when a match is not found, so this approach is probably not helpful by itself.
> - (harder) Scan for preemption candidates asynchronously, freeing up the TaskScheduler thread and the storage write lock. Scans could be kicked off by the task scheduler, ideally in a way that doesn't dogpile. This could also be done in a weakly-consistent way to minimally contribute to storage contention.
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