Danny Ruchman commented on SPARK-18838:


We also have an issue where we query huge amount of parquet file with spark sql 
and experiencing dramatic slowdown after the process reach around 100K tasks. 
Until this point it works in very impressive speed. The query creates over 2MM 
tasks so this practically prevents us from being able to query this amount of 
data using spark 2.0 and above. 
It works with spark 1.6 though but the execution time per task is slower than 
the execution per task in spark 2.0 (until the process starts to slow down)
It seems very much related to the issue described in this ticket.

Is anyone working on a solution for this?

> 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
> 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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