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From Michael Armbrust <>
Subject Re: How to gracefully handle Kafka OffsetOutOfRangeException
Date Fri, 10 Mar 2017 15:34:00 GMT
One option here would be to try Structured Streaming.  We've added an
option "failOnDataLoss" that will cause Spark to just skip a head when this
exception is encountered (its off by default though so you don't silently
miss data).

On Fri, Mar 18, 2016 at 4:16 AM, Ramkumar Venkataraman <> wrote:

> I am using Spark streaming and reading data from Kafka using
> KafkaUtils.createDirectStream. I have the "auto.offset.reset" set to
> smallest.
> But in some Kafka partitions, I get kafka.common.OffsetOutOfRangeException
> and my spark job crashes.
> I want to understand if there is a graceful way to handle this failure and
> not kill the job. I want to keep ignoring these exceptions, as some other
> partitions are fine and I am okay with data loss.
> Is there any way to handle this and not have my spark job crash? I have no
> option of increasing the kafka retention period.
> I tried to have the DStream returned by createDirectStream() wrapped in a
> Try construct, but since the exception happens in the executor, the Try
> construct didn't take effect. Do you have any ideas of how to handle this?
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