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https://issues.apache.org/jira/browse/FLINK-3679?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15902546#comment-15902546
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ASF GitHub Bot commented on FLINK-3679:
---------------------------------------

Github user asfgit closed the pull request at:

    https://github.com/apache/flink/pull/3314


> Allow Kafka consumer to skip corrupted messages
> -----------------------------------------------
>
>                 Key: FLINK-3679
>                 URL: https://issues.apache.org/jira/browse/FLINK-3679
>             Project: Flink
>          Issue Type: Bug
>          Components: DataStream API, Kafka Connector
>            Reporter: Jamie Grier
>            Assignee: Haohui Mai
>
> There are a couple of issues with the DeserializationSchema API that I think 
> should be improved.  This request has come to me via an existing Flink user.
> The main issue is simply that the API assumes that there is a one-to-one 
> mapping between input and outputs.  In reality there are scenarios where one 
> input message (say from Kafka) might actually map to zero or more logical 
> elements in the pipeline.
> Particularly important here is the case where you receive a message from a 
> source (such as Kafka) and say the raw bytes don't deserialize properly.  
> Right now the only recourse is to throw IOException and therefore fail the 
> job.  
> This is definitely not good since bad data is a reality and failing the job 
> is not the right option.  If the job fails we'll just end up replaying the 
> bad data and the whole thing will start again.
> Instead in this case it would be best if the user could just return the empty 
> set.
> The other case is where one input message should logically be multiple output 
> messages.  This case is probably less important since there are other ways to 
> do this but in general it might be good to make the 
> DeserializationSchema.deserialize() method return a collection rather than a 
> single element.
> Maybe we need to support a DeserializationSchema variant that has semantics 
> more like that of FlatMap.



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