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Posted to issues@spark.apache.org by "François Garillot (JIRA)" <ji...@apache.org> on 2015/06/18 17:47:00 UTC

[jira] [Commented] (SPARK-7398) Add back-pressure to Spark Streaming

    [ https://issues.apache.org/jira/browse/SPARK-7398?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14592001#comment-14592001 ] 

François Garillot commented on SPARK-7398:
------------------------------------------

Note this subsumes [SPARK-6691|https://issues.apache.org/jira/browse/SPARK-6691], since dynamic throttling is only one of the options we implement (besides dropping, sampling, interfacing with a _Reactive Streams_-compliant source, and plug-your-own congestion strategy).

> Add back-pressure to Spark Streaming
> ------------------------------------
>
>                 Key: SPARK-7398
>                 URL: https://issues.apache.org/jira/browse/SPARK-7398
>             Project: Spark
>          Issue Type: Improvement
>          Components: Streaming
>    Affects Versions: 1.3.1
>            Reporter: François Garillot
>              Labels: streams
>
> Spark Streaming has trouble dealing with situations where 
>  batch processing time > batch interval
> Meaning a high throughput of input data w.r.t. Spark's ability to remove data from the queue.
> If this throughput is sustained for long enough, it leads to an unstable situation where the memory of the Receiver's Executor is overflowed.
> This aims at transmitting a back-pressure signal back to data ingestion to help with dealing with that high throughput, in a backwards-compatible way.
> The design doc can be found here:
> https://docs.google.com/document/d/1ZhiP_yBHcbjifz8nJEyPJpHqxB1FT6s8-Zk7sAfayQw/edit?usp=sharing



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