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https://issues.apache.org/jira/browse/SPARK-18838?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16017120#comment-16017120
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Antoine PRANG commented on SPARK-18838:
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[~joshrosen] I uploaded the timings I get. I put some counters in the code. You 
can take a look at the metrics branch of my forks.
I do not have exact profile of the methods.
First the StorageListener "really" execute a lot of message. It has not a no-op 
received method for the most frequent messages (SparkListenerBlockUpdated) if i 
understand well.
they are not logged in the EventLoggingListener for example.
But the StorageStatusListener listens to this kind of events too, and its 
execution time is not comparable.
But it seems to do much more work (with the parent classes).
there is a lot of synchronization which may be avoided in my mind.


> High latency of event processing for large jobs
> -----------------------------------------------
>
>                 Key: SPARK-18838
>                 URL: https://issues.apache.org/jira/browse/SPARK-18838
>             Project: Spark
>          Issue Type: Improvement
>    Affects Versions: 2.0.0
>            Reporter: Sital Kedia
>         Attachments: SparkListernerComputeTime.xlsx
>
>
> Currently we are observing the issue of very high event processing delay in 
> driver's `ListenerBus` for large jobs with many tasks. Many critical 
> component of the scheduler like `ExecutorAllocationManager`, 
> `HeartbeatReceiver` depend on the `ListenerBus` events and this delay might 
> hurt the job performance significantly or even fail the job.  For example, a 
> significant delay in receiving the `SparkListenerTaskStart` might cause 
> `ExecutorAllocationManager` manager to mistakenly remove an executor which is 
> not idle.  
> The problem is that the event processor in `ListenerBus` is a single thread 
> which loops through all the Listeners for each event and processes each event 
> synchronously 
> https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/LiveListenerBus.scala#L94.
>  This single threaded processor often becomes the bottleneck for large jobs.  
> Also, if one of the Listener is very slow, all the listeners will pay the 
> price of delay incurred by the slow listener. In addition to that a slow 
> listener can cause events to be dropped from the event queue which might be 
> fatal to the job.
> To solve the above problems, we propose to get rid of the event queue and the 
> single threaded event processor. Instead each listener will have its own 
> dedicate single threaded executor service . When ever an event is posted, it 
> will be submitted to executor service of all the listeners. The Single 
> threaded executor service will guarantee in order processing of the events 
> per listener.  The queue used for the executor service will be bounded to 
> guarantee we do not grow the memory indefinitely. The downside of this 
> approach is separate event queue per listener will increase the driver memory 
> footprint. 



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