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Date: Thu, 7 Sep 2017 08:23:00 +0000 (UTC)
From: "Nazar Vishka (JIRA)" <jira@apache.org>
To: issues@camel.apache.org
Message-ID: <JIRA.13100094.1504692898000.47682.1504772580463@Atlassian.JIRA>
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Subject: [jira] [Commented] (CAMEL-11750) Camel route with multicast
 (parallel) generate huge CPU load
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archived-at: Thu, 07 Sep 2017 08:23:06 -0000


    [ https://issues.apache.org/jira/browse/CAMEL-11750?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16156670#comment-16156670 ] 

Nazar Vishka commented on CAMEL-11750:
--------------------------------------

I propose minor fix:
{code}public long getDelay(TimeUnit unit) {
          return unit.convert(id - index.get(), TimeUnit.SECONDS);
}{code}
It does not broke other logic but adds 1 second delat for a task that is 2nd in the queue, 2 sec for 3rd task, 3sec for 4th task, etc. On my test project it helps to decrease CPU load:
!https://www.screencast.com/t/wz6BFkI37!

> Camel route with multicast (parallel) generate huge CPU load
> ------------------------------------------------------------
>
>                 Key: CAMEL-11750
>                 URL: https://issues.apache.org/jira/browse/CAMEL-11750
>             Project: Camel
>          Issue Type: Bug
>          Components: camel-core
>            Reporter: Nazar Vishka
>            Priority: Critical
>
> I've created simple [Spring Camel Route application|https://github.com/leofromgroza/camel-long-term-route] that can be used for issue reproducing. Here we have very simple route:
> {code}
>     public void configure() throws Exception {
>         from("direct:start").routeId("start")
>                 .multicast().parallelProcessing()
>                 .to("direct:very-long-task", "direct:long-task")
>                 .end();
>         from("direct:long-task").routeId("long-task")
>                 .log("Started long-task")
>                 .process(exchange -> Thread.sleep(5000))
>                 .log("Finished long-task")
>                 .end();
>         from("direct:very-long-task").routeId("very-long-task")
>                 .log("Started very-long-task")
>                 .process(exchange -> Thread.sleep(35000))
>                 .log("Finished very-long-task")
>                 .end();
>     }{code}
> From our main route 'start' we are starting in parallel two sub-routes: 'long-task' and 'very-long-task'. They are just doing something for some period of time and do not generate any load to the system.
> But I found that when one task finished earlier than other one, route start to make a huge CPU load. Here you can see a CPU usage during executiong of Camel route that was mentioned earlier (after finishing of 'long-task' usage of CPU uncreased from 0 to 12.5%):
> !https://content.screencast.com/users/NazarV/folders/Jing/media/830268f0-d184-4c57-adb1-b782ea63fa6d/2017-09-06_1241.png!
> Screenshot was made when I was running route on my Windows PC with 4 physical CPU cores + 4 HT. On Unix systems we found that after end of 'long-task' it used 100% of one core till the end of work.
> One more interesting thing that i've found is that the main load on the system was generated by the thread MulticastProcessor-AggregateTask that was spending a lot of time in the method java.util.concurrent.locks.AbstractQueuedSynchronizer.ConditionObject#awaitNanos that was called from java.util.concurrent.DelayQueue#poll(long, java.util.concurrent.TimeUnit):
> {code}"Camel (camel-1) thread #2 - MulticastProcessor-AggregateTask" #29 daemon prio=5 os_prio=0 tid=0x00000000215e3000 nid=0x7a0 runnable [0x0000000022eaf000]
>    java.lang.Thread.State: RUNNABLE
> 	at java.lang.Thread.isInterrupted(Native Method)
> 	at java.lang.Thread.interrupted(Thread.java:944)
> 	at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.checkInterruptWhileWaiting(AbstractQueuedSynchronizer.java:2002)
> 	at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2079)
> 	at java.util.concurrent.DelayQueue.poll(DelayQueue.java:273)
> 	at org.apache.camel.util.concurrent.SubmitOrderedCompletionService.poll(SubmitOrderedCompletionService.java:127)
> 	at org.apache.camel.processor.MulticastProcessor$AggregateOnTheFlyTask.aggregateOnTheFly(MulticastProcessor.java:463)
> 	at org.apache.camel.processor.MulticastProcessor$AggregateOnTheFlyTask.run(MulticastProcessor.java:418)
> 	at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> 	at java.util.concurrent.FutureTask.run(FutureTask.java:266)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> 	at java.lang.Thread.run(Thread.java:745){code}
> In DelayQueue#poll(long, java.util.concurrent.TimeUnit) we have a piece of code:
> {code}E first = q.peek();
> if (first == null) {
>  ...
> } else {
>   long delay = first.getDelay(NANOSECONDS);
>     ...
>   long timeLeft =  available.awaitNanos(delay) {code}
> During debugging I found that E first is object of class [org.apache.camel.util.concurrent.SubmitOrderedCompletionService.SubmitOrderFutureTask|https://github.com/apache/camel/blob/camel-2.19.2/camel-core/src/main/java/org/apache/camel/util/concurrent/SubmitOrderedCompletionService.java] and it's very interesting [getDelay(TimeUnit) method|https://github.com/apache/camel/blob/camel-2.19.2/camel-core/src/main/java/org/apache/camel/util/concurrent/SubmitOrderedCompletionService.java#L64] always return 1. I thing that is a source of current issue:
> {code} public long getDelay(TimeUnit unit) {
>             // if the answer is 0 then this task is ready to be taken
>             return id - index.get();
>         }{code}
> So when delay is 1, AggregateTask thread is not sleeping at all and generates a huge CPU load all the time when it is waiting for the end of the last task.
> I think that [getDelay(TimeUnit) method|https://github.com/apache/camel/blob/camel-2.19.2/camel-core/src/main/java/org/apache/camel/util/concurrent/SubmitOrderedCompletionService.java#L64] should be somehow re-implemented.


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