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https://issues.apache.org/jira/browse/FLINK-5048?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15670803#comment-15670803
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ASF GitHub Bot commented on FLINK-5048:
---------------------------------------

Github user StephanEwen commented on a diff in the pull request:

    https://github.com/apache/flink/pull/2789#discussion_r88264932
  
    --- Diff: 
flink-streaming-connectors/flink-connector-kafka-0.9/src/main/java/org/apache/flink/streaming/connectors/kafka/internal/Kafka09Fetcher.java
 ---
    @@ -143,133 +123,26 @@ public Kafka09Fetcher(
     
        @Override
        public void runFetchLoop() throws Exception {
    --- End diff --
    
    To be safe, I think the `CloseExceptions` should be re-thrown, as should 
all others.
    Just for the case when we overlook something and the consumer thread could 
close the handover by itself or so. Any abnormal termination of the fetch loop 
should result in an exception - that is the safest we can do.


> Kafka Consumer (0.9/0.10) threading model leads problematic cancellation 
> behavior
> ---------------------------------------------------------------------------------
>
>                 Key: FLINK-5048
>                 URL: https://issues.apache.org/jira/browse/FLINK-5048
>             Project: Flink
>          Issue Type: Bug
>          Components: Kafka Connector
>    Affects Versions: 1.1.3
>            Reporter: Stephan Ewen
>            Assignee: Stephan Ewen
>             Fix For: 1.2.0
>
>
> The {{FLinkKafkaConsumer}} (0.9 / 0.10) spawns a separate thread that 
> operates the KafkaConsumer. That thread is shielded from interrupts, because 
> the Kafka Consumer has not been handling thread interrupts well.
> Since that thread is also the thread that emits records, it may block in the 
> network stack (backpressure) or in chained operators. The later case leads to 
> situations where cancellations get very slow unless that thread would be 
> interrupted (which it cannot be).
> I propose to change the thread model as follows:
>   - A spawned consumer thread pull from the KafkaConsumer and pushes its 
> pulled batch of records into a blocking queue (size one)
>   - The main thread of the task will pull the record batches from the 
> blocking queue and emit the records.
> This allows actually for some additional I/O overlay while limiting the 
> additional memory consumption - only two batches are ever held, one being 
> fetched and one being emitted.



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