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https://issues.apache.org/jira/browse/SPARK-26391?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-26391.
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Resolution: Invalid
Questions should go to mailing list. You could have a better answer from
developers and users.
> Spark Streaming Kafka with Offset Gaps
> --------------------------------------
>
> Key: SPARK-26391
> URL: https://issues.apache.org/jira/browse/SPARK-26391
> Project: Spark
> Issue Type: Question
> Components: Spark Core, Structured Streaming
> Affects Versions: 2.4.0
> Reporter: Rishabh
> Priority: Major
>
> I have an app that uses Kafka Streaming to pull data from `input` topic and
> push to `output` topic with `processing.guarantee=exactly_once`. Due to
> `exactly_once` gaps (transaction markers) are created in Kafka. Let's call
> this app `kafka-streamer`.
> Now I've another app that listens to this output topic (actually they are
> multiple topics with a Pattern/Regex) and processes the data using
> [https://spark.apache.org/docs/latest/streaming-kafka-0-10-integration.html].
> Let's call this app `spark-streamer`.
> Due to the gaps, the first thing that happens is spark streaming fails. To
> fix this I enabled `spark.streaming.kafka.allowNonConsecutiveOffsets=true` in
> the spark config before creating the StreamingContext. Now let's look at the
> issues that were faced when I start `spark-streamer`:
> # Even though there are new offsets to be polled/consumed, it requires
> another message push to the topic partition to be able to start processing.
> If I start the app (and there are messages in queue to be polled) and don't
> push any topic, the code will timeout after default 120ms and throw an
> exception.
> # It doesn't fetch the last record. It fetches the record till second-last.
> This means to poll/process the last record, another message has to be pushed.
> This is a problem for us since `spark-streamer` is listening to multiple
> topics (based on a pattern) and there might be a topic where throughput is
> low but the data should still make it to Spark for processing.
> # In general if no data/message is pushed then it'll die after 120ms default
> timeout for polling.
> Now in the limited amount of time I had, I tried going through the
> spark-streaming-kafka code and was only able to find an answer to the third
> problem which is this -
> [https://github.com/apache/spark/blob/master/external/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumer.scala#L178]
> My questions are:
> # Why do we throw an exception in `compactedNext()` if no data is polled ?
> # I wasn't able to figure out why the first and second issue happened, would
> be great if somebody can point out a solution or reason behind the behaviour ?
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