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https://issues.apache.org/jira/browse/BEAM-6612?focusedWorklogId=207936&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-207936
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ASF GitHub Bot logged work on BEAM-6612:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 05/Mar/19 18:13
            Start Date: 05/Mar/19 18:13
    Worklog Time Spent: 10m 
      Work Description: kennknowles commented on pull request #7895: 
[BEAM-6612] Improve java SDK performance by using a LinkedBlockingQueue in 
QueueingBeamFnDataClient
URL: https://github.com/apache/beam/pull/7895#discussion_r262619128
 
 

 ##########
 File path: 
sdks/java/fn-execution/src/main/java/org/apache/beam/sdk/fn/data/CompletableFutureInboundDataClient.java
 ##########
 @@ -65,6 +65,8 @@ public void complete() {
 
   @Override
   public void fail(Throwable t) {
-    future.completeExceptionally(t);
+    // Use obtrudeException instead of CompleteExceptionally, forcing any 
future calls to .get()
 
 Review comment:
   Good catch. I did not realize that standard future behavior required this 
other function :-/
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 207936)
    Time Spent: 1.5h  (was: 1h 20m)

> PerformanceRegression in QueueingBeamFnDataClient
> -------------------------------------------------
>
>                 Key: BEAM-6612
>                 URL: https://issues.apache.org/jira/browse/BEAM-6612
>             Project: Beam
>          Issue Type: New Feature
>          Components: java-fn-execution
>            Reporter: Alex Amato
>            Assignee: Alex Amato
>            Priority: Major
>              Labels: triaged
>          Time Spent: 1.5h
>  Remaining Estimate: 0h
>
> Remove QueueingBeamFnDataClient, which made process() calls all run on the 
> same thread.
> [~lcwik] and I came up with this design thinking that it was required to 
> process the bundle in parallel anyways, and we would have good performance. 
> However after speaking to Ken, there is no requirement for a bundle or key to 
> be processed in parallel. Elements are either iterables or single elements 
> which defines the needs for processing a group of elements on the same thread.
> Simply performing this change will lead to the following issues:
> (1) MetricsContainerImpl and MetricsContainer are not thread safe, so when 
> the process() functions enter the metric container context, they will be 
> accessing an thread-unsafe collection in parallel
> (2) An ExecutionStateTracker will be needed in every thread, So we will need 
> to
> create an instance and activate it in every GrpC thread which receives a new 
> element.
> (Will this get sampled properly, since the trackers will be short lived).
> (3) The SimpleExecutionStates being used will need to be thread safe as well? 
> I don't think so, because I don't think that the ExecutionStateSampler 
> invokes them in parallel.
>  



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