[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17340593#comment-17340593 ] xiaoli commented on YARN-9927: -- mark > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Sub-task > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Assignee: Qi Zhu >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch, YARN-9927.002.patch, YARN-9927.003.patch, > YARN-9927.004.patch, YARN-9927.005.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17339383#comment-17339383 ] Qi Zhu commented on YARN-9927: -- Great review and investigation! Thanks very much [~ebadger] [~ebadger] . I agree with you that we should do some stress test done via SLS or manually. And the more generic way of event handling is a great improvement in YARN. And about the test, i will change it to test both the multi-thread and the single one. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Sub-task > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Assignee: Qi Zhu >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch, YARN-9927.002.patch, YARN-9927.003.patch, > YARN-9927.004.patch, YARN-9927.005.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[
https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17338237#comment-17338237
]
Andras Gyori commented on YARN-9927:
Thank you [~zhuqi] for the patch. I think this approach is well thought,
because it reuses existing logic already established elsewhere (services as
separate threads). On this part I have one addition:
* Please move MultiThreadDispatcher to its own file as ResourceManager already
has quite a good amount of code.
As for RMNode event handling, I have one proposition. Usually keeping code as
simple as possible is a good recommendation, but I do think event handling is a
crucial part of YARN, and it might be worthwhile to provide fine tuning
options. The RMNode event handling is a good way to improve performance, but I
could see a value in providing a more generic way of event handling. A proof of
concept implementation of my proposition is:
# Create a MultiThreadEventHandler wrapper
{code:java}
public static class MultiThreadEventHandler implements EventHandler> {
private final ThreadPoolExecutor multiHandlerThreadPool;
private final EventHandler> handler;
public MultiThreadEventHandler(EventHandler> handler,
int maximumPoolSize) {
this.handler = handler;
ThreadFactory threadFactory = new ThreadFactoryBuilder()
.setNameFormat("multiHandlerThread #%d")
.build();
multiHandlerThreadPool = new ThreadPoolExecutor(
5, maximumPoolSize, 10, TimeUnit.SECONDS,
new LinkedBlockingQueue<>(), threadFactory);
}
@Override
public void handle(Event event) {
multiHandlerThreadPool.submit(() -> handler.handle(event));
}
}
{code}
# Provide configuration values to set MultiThreadEventHandler for a specific
EventType and the MultiThreadDispatcher#register would look like this
{code:java}
@Override
public void register(Class eventType,
EventHandler handler) {
if (eventTypeDispatcherMap.get(eventType) == null) {
AsyncDispatcher asyncDispatcher =
createDispatcher(eventType);
eventTypeDispatcherMap.put(eventType,
asyncDispatcher);
addIfService(asyncDispatcher);
}
EventHandler registeredHandler = handler;
boolean isMultiThreadEventHandler =
getConfig().getBoolean("yarn.scheduler.event." + eventType.getCanonicalName()
+ ".multi-thread-handler.enabled", false);
if (isMultiThreadEventHandler) {
int poolSize = getConfig().getInt("yarn.scheduler.event." +
eventType.getCanonicalName()
+ ".multi-thread-handler.max-pool-size", 5);
registeredHandler = new MultiThreadEventHandler(handler, poolSize);
}
eventTypeDispatcherMap.
get(eventType).register(eventType, registeredHandler);
}
{code}
As it was emphasised before, this is a performance critical section of YARN,
therefore some kind of stress test done via SLS or manually would need to be
done to make sure RM is not crippled by these changes and the performance
increase justifies this complexity and extended hardware resource usage.
> RM multi-thread event processing mechanism
> --
>
> Key: YARN-9927
> URL: https://issues.apache.org/jira/browse/YARN-9927
> Project: Hadoop YARN
> Issue Type: Sub-task
> Components: yarn
>Affects Versions: 3.0.0, 2.9.2
>Reporter: hcarrot
>Assignee: Qi Zhu
>Priority: Major
> Attachments: RM multi-thread event processing mechanism.pdf,
> YARN-9927.001.patch, YARN-9927.002.patch, YARN-9927.003.patch,
> YARN-9927.004.patch, YARN-9927.005.patch
>
>
> Recently, we have observed serious event blocking in RM event dispatcher
> queue. After analysis of RM event monitoring data and RM event processing
> logic, we found that
> 1) environment: a cluster with thousands of nodes
> 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler
> 3) Meanwhile, RM event processing is in a single-thread mode, and It results
> in the low headroom of RM event scheduler, thus performance of RM.
> So we proposed a RM multi-thread event processing mechanism to improve RM
> performance.
--
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[
https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17335804#comment-17335804
]
Eric Badger commented on YARN-9927:
---
{noformat}
+// Test multi thread dispatcher
+conf.setBoolean(YarnConfiguration.
+MULTI_THREAD_DISPATCHER_ENABLED, true);
{noformat}
If this is a feature that is disabled by default, I don't think we should have
it enabled by default in all of the RM tests. I would be happier running it as
a parameterized test with both multi and single thread dispatchers.
In general I think the patch looks reasonable, but I would like to see testing
done to see if this makes the problem better or worse. I would think it would
make things better, but until we run some real tests on it, we won't really
know. So getting something similar to what [~hcarrot] provided originally would
be good. That way we can merge this with confidence.
> RM multi-thread event processing mechanism
> --
>
> Key: YARN-9927
> URL: https://issues.apache.org/jira/browse/YARN-9927
> Project: Hadoop YARN
> Issue Type: Sub-task
> Components: yarn
>Affects Versions: 3.0.0, 2.9.2
>Reporter: hcarrot
>Assignee: Qi Zhu
>Priority: Major
> Attachments: RM multi-thread event processing mechanism.pdf,
> YARN-9927.001.patch, YARN-9927.002.patch, YARN-9927.003.patch,
> YARN-9927.004.patch, YARN-9927.005.patch
>
>
> Recently, we have observed serious event blocking in RM event dispatcher
> queue. After analysis of RM event monitoring data and RM event processing
> logic, we found that
> 1) environment: a cluster with thousands of nodes
> 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler
> 3) Meanwhile, RM event processing is in a single-thread mode, and It results
> in the low headroom of RM event scheduler, thus performance of RM.
> So we proposed a RM multi-thread event processing mechanism to improve RM
> performance.
--
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
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https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17334689#comment-17334689
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Hadoop QA commented on YARN-9927:
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17334565#comment-17334565 ] Qi Zhu commented on YARN-9927: -- [~ebadger] [~gandras] [~epayne] Updated a patch to improve: 1. The event produce to event queue : Each eventType will have single async dispatcher thread, the thread number is small which i have counted. And each dispatcher has single event queue, events will not affect each other anymore. 2. The event consume from event queue and process: I add an example to multi thread processing in handler just for RMNodeEvent. Different RMNodeImpl object has different write lock, i think it can be faster to make multi thread handle with different RMNode object. What's your opinions about this? Thanks. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Sub-task > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Assignee: Qi Zhu >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch, YARN-9927.002.patch, YARN-9927.003.patch, > YARN-9927.004.patch, YARN-9927.005.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
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Hadoop QA commented on YARN-9927:
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17319898#comment-17319898 ] Qi Zhu commented on YARN-9927: -- Fixed the checkstyle in latest patch. cc [~gandras] [~pbacsko] > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Sub-task > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Assignee: Qi Zhu >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch, YARN-9927.002.patch, YARN-9927.003.patch, > YARN-9927.004.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
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https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17314467#comment-17314467
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Hadoop QA commented on YARN-9927:
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[
https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17314344#comment-17314344
]
Hadoop QA commented on YARN-9927:
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17314294#comment-17314294 ] Qi Zhu commented on YARN-9927: -- [~gandras] [~pbacsko] Updated a patch, each eventType will have single async dispatcher thread. I will add unit test later. I think we first realize the multi thread dispatcher for each eventType, so that the event queue will not be a problem. And about the thread number, i counted the eventType number, it is in reasonable range. Then we can move to that, how can we consume the event queue faster. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Sub-task > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Assignee: Qi Zhu >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch, YARN-9927.002.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17305941#comment-17305941 ] Andras Gyori commented on YARN-9927: Thanks [~zhuqi] for the answer, I agree with your concerns. Ideally, we could predefine a small threadpool on creation, and decide on EventType registration whether we want that kind of event to be handled separately in a thread. I think a separate thread for NodeEvents and AppAttempts make sense, but we will not need a new thread for every event type. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Sub-task > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Assignee: Qi Zhu >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17305895#comment-17305895 ] Qi Zhu commented on YARN-9927: -- Thanks [~gandras] for investigation and reply. I agree with you that which you suggested is a better mode, the only concern to me is that if the thread number will be too many, and if it will cause some side effect compare with the original mode. We also should make stress test to the new mode. Thanks. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Sub-task > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Assignee: Qi Zhu >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[
https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17304992#comment-17304992
]
Andras Gyori commented on YARN-9927:
Thank you [~hcarrot] for raising this issue and [~zhuqi] for stepping up to
continue this undertaking.
These are my feedback and suggestions, which might not mirror the actual
situation, therefore feel free to discuss the false information. I think the
current patch is not the best approach of this problem. It does include the
concerns already raised in this jira, and my insights as well.
The single entry point for an event is AsyncDispatcher#handle, which puts the
event in the eventQueue, and is processed asynchronously in a single thread.
There is no way this could be circumvented, because it is used as
rmContext.getDispatcher() all over the place. We must retain this entry point.
However I have a strong sense that the performance bottleneck is actually the
AsyncDispatcher#eventQueue (a BlockingQueue). In my opinion, the solution is
exactly the suggestion that is already described in the documentation of
AsyncDispatcher:
{code:java}
/**
Dispatches {@link Event}s in a separate thread. Currently only single thread
does that. Potentially there could be multiple channels for each event type
class and a thread pool can be used to dispatch the events.
*/
{code}
My suggestion would be:
# Store a new BlockingQueue for each event type in a HashMap
# Create a new thread for each of the registered event type / eventQueue
# Every thread is responsible for one eventQueue processing
# The Dispatcher would map to an N:N:N (EventQueue:Thread:EventHandler) system
(or a N:M:N where M is smaller than N in order to reduce the amount of
threads), where N is the number of EventTypes registered
A more fine-grained solution is possible by making an M*N:M*N:N
(EventQueue:Thread:EventHandler) system, where M is a number given on
registration (how many thread should be processing this kind of event) and N is
the number of EventTypes registered (as far as I am concerned the EventHandlers
do not use locks internally, and they are thread safe). I am not sure if this
is feasible, because of the external locks used in EventHandlers (eg.
NodeEventHandler uses getRMNodes(), which is locked behind a ConcurrentMap -> I
think this is the feedback which was given by [~adam.antal] and [~epayne]).
A dummy implementation of the aforementioned system would be:
{code:java}
public class ThreadedDispatcher {
private final ConcurrentMap> events;
private final ConcurrentMap> eventHandlers;
public void register(Class eventType,
EventHandler handler) {
new Thread(() -> {
EventHandler handler = eventHandlers.get(eventType);
BlockingQueue eventQueue = events.get(eventType);
while (!stopped && !Thread.currentThread().isInterrupted()) {
Event event = eventQueue.take();
handler.handle(event);
}
}).run();
class GenericEventHandler implements EventHandler {
public void handle(Event event) {
events.get(event.getType()).put(event);
}
}
}
{code}
cc: [~pbacsko]
> RM multi-thread event processing mechanism
> --
>
> Key: YARN-9927
> URL: https://issues.apache.org/jira/browse/YARN-9927
> Project: Hadoop YARN
> Issue Type: Sub-task
> Components: yarn
>Affects Versions: 3.0.0, 2.9.2
>Reporter: hcarrot
>Assignee: Qi Zhu
>Priority: Major
> Attachments: RM multi-thread event processing mechanism.pdf,
> YARN-9927.001.patch
>
>
> Recently, we have observed serious event blocking in RM event dispatcher
> queue. After analysis of RM event monitoring data and RM event processing
> logic, we found that
> 1) environment: a cluster with thousands of nodes
> 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler
> 3) Meanwhile, RM event processing is in a single-thread mode, and It results
> in the low headroom of RM event scheduler, thus performance of RM.
> So we proposed a RM multi-thread event processing mechanism to improve RM
> performance.
--
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17281120#comment-17281120 ] hcarrot commented on YARN-9927: --- [~zhuqi] I will be appreciated if you can help to rebase and improve it. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[
https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17281119#comment-17281119
]
Hadoop QA commented on YARN-9927:
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| {color:orange} hadoop-yarn-project/hadoop-yarn: The patch generated 61 new +
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17280942#comment-17280942 ] Qi Zhu commented on YARN-9927: -- [~hcarrot] [~leftnoteasy] [~adam.antal] [~epayne] Is it going on? I think it will be helpful in large cluster, i can help to rebase it. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[
https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16971506#comment-16971506
]
Hadoop QA commented on YARN-9927:
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0s{color} | {color:green} The patch does not contain any @author tags. {color} |
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|| || || || {color:brown} trunk Compile Tests {color} ||
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At ResourceManager.java:1202 of value previously dereferenced in
org.apache
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16971421#comment-16971421 ] hcarrot commented on YARN-9927: --- sorry for the first time, our YARN version is not compatible with the origin version. The patch has been uploaded again. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927.001.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[
https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16967336#comment-16967336
]
Hadoop QA commented on YARN-9927:
-
| (x) *{color:red}-1 overall{color}* |
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0s{color} | {color:blue} Docker mode activated. {color} |
| {color:red}-1{color} | {color:red} patch {color} | {color:red} 0m 7s{color}
| {color:red} YARN-9927 does not apply to trunk. Rebase required? Wrong Branch?
See https://wiki.apache.org/hadoop/HowToContribute for help. {color} |
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|| Subsystem || Report/Notes ||
| JIRA Issue | YARN-9927 |
| JIRA Patch URL |
https://issues.apache.org/jira/secure/attachment/12984902/YARN-9927.001.patch |
| Console output |
https://builds.apache.org/job/PreCommit-YARN-Build/25101/console |
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This message was automatically generated.
> RM multi-thread event processing mechanism
> --
>
> Key: YARN-9927
> URL: https://issues.apache.org/jira/browse/YARN-9927
> Project: Hadoop YARN
> Issue Type: Improvement
> Components: yarn
>Affects Versions: 3.0.0, 2.9.2
>Reporter: hcarrot
>Priority: Major
> Attachments: RM multi-thread event processing mechanism.pdf,
> YARN-9927.001.patch
>
>
> Recently, we have observed serious event blocking in RM event dispatcher
> queue. After analysis of RM event monitoring data and RM event processing
> logic, we found that
> 1) environment: a cluster with thousands of nodes
> 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler
> 3) Meanwhile, RM event processing is in a single-thread mode, and It results
> in the low headroom of RM event scheduler, thus performance of RM.
> So we proposed a RM multi-thread event processing mechanism to improve RM
> performance.
--
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16966849#comment-16966849 ] Adam Antal commented on YARN-9927: -- Thanks for the patch [~hcarrot]. Could you please name your patch aligned with the convention (something like YARN-9927.001.patch would be fine), and also set the status of this issue to Patch available so that jenkins can pick this up? I'm ready to review it after the tests pass. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927-addMultiEventDispatcher.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16962987#comment-16962987 ] hcarrot commented on YARN-9927: --- The code has been finished. I think this mechanism can handler RMNodeStatusEvent from different nodes concurrently. Because the lock object of different RMNode state machine is different. [~adam.antal] [~epayne] > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf, > YARN-9927-addMultiEventDispatcher.patch > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[
https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16962135#comment-16962135
]
Eric Payne commented on YARN-9927:
--
Thank you [~hcarrot] for bringing this up and for your work in making the RM
better, and thank you for providing the architecture document.
{quote}
bq. we just replace the time in the dispatcher queue with lock-holding time for
each event.
RM can process different events concurrently
{quote}
I share the same concern as [~adam.antal]. Since the code path through
RMNodeStatusEvent is protected by locks, I think that even if multiple
RMNodeStatusEvent events are being processed by multiple dispatcher threads at
the same time, only one will actually be running. Unless the design is to
dedicate one thread to handling only RMNodeStatusEvent events and the other
threads to handling non-RMNodeStatusEvent events.
I look forward to seeing your POC.
> RM multi-thread event processing mechanism
> --
>
> Key: YARN-9927
> URL: https://issues.apache.org/jira/browse/YARN-9927
> Project: Hadoop YARN
> Issue Type: Improvement
> Components: yarn
>Affects Versions: 3.0.0, 2.9.2
>Reporter: hcarrot
>Priority: Major
> Attachments: RM multi-thread event processing mechanism.pdf
>
>
> Recently, we have observed serious event blocking in RM event dispatcher
> queue. After analysis of RM event monitoring data and RM event processing
> logic, we found that
> 1) environment: a cluster with thousands of nodes
> 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler
> 3) Meanwhile, RM event processing is in a single-thread mode, and It results
> in the low headroom of RM event scheduler, thus performance of RM.
> So we proposed a RM multi-thread event processing mechanism to improve RM
> performance.
--
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[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16957378#comment-16957378 ] Wangda Tan commented on YARN-9927: -- Thanks [~hcarrot] for working on this. Tagging: [~prabhujoseph] , [~jhung] ,[~sunil.gov...@gmail.com] , [~epayne] for review. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16957037#comment-16957037 ] zhoukang commented on YARN-9927: nice idea, we also want to do similar job. looking forward for the poc [~hcarrot] > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16956949#comment-16956949 ] hcarrot commented on YARN-9927: --- The performance bottleneck is the single-thread RMEventDispatcher mode. Events are processed one by one. If we change single-thread to multi-thread, RM can process different events concurrently. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Major > Attachments: RM multi-thread event processing mechanism.pdf > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that > 1) environment: a cluster with thousands of nodes > 2) RMNodeStatusEvent dominates 90% time consumption of RM event scheduler > 3) Meanwhile, RM event processing is in a single-thread mode, and It results > in the low headroom of RM event scheduler, thus performance of RM. > So we proposed a RM multi-thread event processing mechanism to improve RM > performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Commented] (YARN-9927) RM multi-thread event processing mechanism
[ https://issues.apache.org/jira/browse/YARN-9927?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16956764#comment-16956764 ] Adam Antal commented on YARN-9927: -- Thanks for filing this [~hcarrot], interesting approach. One question that came to my mind is that: are you certain the the dispatcher is the real bottleneck here? I mean if an event processing requires holding the lock the whole time, then we just replace the time in the dispatcher queue with lock-holding time for each event. We should dig down that for a certain event type how long the lock should be hold. > RM multi-thread event processing mechanism > -- > > Key: YARN-9927 > URL: https://issues.apache.org/jira/browse/YARN-9927 > Project: Hadoop YARN > Issue Type: Improvement > Components: yarn >Affects Versions: 3.0.0, 2.9.2 >Reporter: hcarrot >Priority: Minor > Attachments: RM multi-thread event processing mechanism.pdf > > > Recently, we have observed serious event blocking in RM event dispatcher > queue. After analysis of RM event monitoring data and RM event processing > logic, we found that the proportion of RMNodeStatusEvent is less than other > events, but the overall processing time of it is more than other events. > Meanwhile, RM event processing is in a single-thread mode, and It results in > the decrease of RM's performance. So we proposed a RM multi-thread event > processing mechanism to improve RM performance. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
