[jira] [Created] (SPARK-24067) Spark 2.3 Streaming Kafka 0.10 Consumer Can't Handle Non-consecutive Offsets (i.e. Log Compaction)

["Joachim Hereth (JIRA)" <ji...@apache.org>]

Joachim Hereth created SPARK-24067:
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             Summary: Spark 2.3 Streaming Kafka 0.10 Consumer Can't Handle Non-consecutive Offsets (i.e. Log Compaction)
                 Key: SPARK-24067
                 URL: https://issues.apache.org/jira/browse/SPARK-24067
             Project: Spark
          Issue Type: Bug
          Components: DStreams
    Affects Versions: 2.0.0
            Reporter: Joachim Hereth
            Assignee: Cody Koeninger
             Fix For: 2.4.0


When Kafka does log compaction offsets often end up with gaps, meaning the next requested offset will be frequently not be offset+1. The logic in KafkaRDD & CachedKafkaConsumer has a baked in assumption that the next offset will always be just an increment of 1 above the previous offset. 

I have worked around this problem by changing CachedKafkaConsumer to use the returned record's offset, from:
{{nextOffset = offset + 1}}
to:
{{nextOffset = record.offset + 1}}

and changed KafkaRDD from:
{{requestOffset += 1}}
to:
{{requestOffset = r.offset() + 1}}

(I also had to change some assert logic in CachedKafkaConsumer).

There's a strong possibility that I have misconstrued how to use the streaming kafka consumer, and I'm happy to close this out if that's the case. If, however, it is supposed to support non-consecutive offsets (e.g. due to log compaction) I am also happy to contribute a PR.



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