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From "Guozhang Wang (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (KAFKA-5158) Options for handling exceptions during processing
Date Tue, 12 Dec 2017 20:00:01 GMT

     [ https://issues.apache.org/jira/browse/KAFKA-5158?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Guozhang Wang updated KAFKA-5158:
---------------------------------
    Issue Type: Task  (was: Sub-task)
        Parent:     (was: KAFKA-5156)

> Options for handling exceptions during processing
> -------------------------------------------------
>
>                 Key: KAFKA-5158
>                 URL: https://issues.apache.org/jira/browse/KAFKA-5158
>             Project: Kafka
>          Issue Type: Task
>          Components: streams
>            Reporter: Eno Thereska
>
> Imagine the app-level processing of a (non-corrupted) record fails (e.g. the user attempted
to do a RPC to an external system, and this call failed). How can you process such failed
records in a scalable way? For example, imagine you need to implement a retry policy such
as "retry with exponential backoff". Here, you have the problem that 1. you can't really pause
processing a single record because this will pause the processing of the full stream (bottleneck!)
and 2. there is no straight-forward way to "sort" failed records based on their "next retry
time".



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