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https://issues.apache.org/jira/browse/SPARK-21561?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16107324#comment-16107324
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Vlad Badelita commented on SPARK-21561:
---
Sorry, didn't know where to ask about this issues. I have since found out it
was an actual bug, that someone else experienced:
https://issues.apache.org/jira/browse/SPARK-18779
However, it was a kafka bug, not a spark-streaming one and was solved here:
https://issues.apache.org/jira/browse/KAFKA-4547
And it changing the kafka-clients version to 0.10.2.1 fixed it for me.
> spark-streaming-kafka-010 DSteam is not pulling anything from Kafka
> ---
>
> Key: SPARK-21561
> URL: https://issues.apache.org/jira/browse/SPARK-21561
> Project: Spark
> Issue Type: Bug
> Components: DStreams
>Affects Versions: 2.1.1
>Reporter: Vlad Badelita
> Labels: kafka-0.10, spark-streaming
>
> I am trying to use spark-streaming-kafka-0.10 to pull messages from a kafka
> topic(broker version 0.10). I have checked that messages are being produced
> and used a KafkaConsumer to pull them successfully. Now, when I try to use
> the spark streaming api, I am not getting anything. If I just use
> KafkaUtils.createRDD and specify some offset ranges manually it works. But
> when, I try to use createDirectStream, all the rdds are empty and when I
> check the partition offsets it simply reports that all partitions are 0. Here
> is what I tried:
> {code:scala}
> val sparkConf = new SparkConf().setAppName("kafkastream")
> val ssc = new StreamingContext(sparkConf, Seconds(3))
> val topics = Array("my_topic")
> val kafkaParams = Map[String, Object](
>"bootstrap.servers" -> "hostname:6667"
>"key.deserializer" -> classOf[StringDeserializer],
>"value.deserializer" -> classOf[StringDeserializer],
>"group.id" -> "my_group",
>"auto.offset.reset" -> "earliest",
>"enable.auto.commit" -> (true: java.lang.Boolean)
> )
> val stream = KafkaUtils.createDirectStream[String, String](
>ssc,
>PreferConsistent,
>Subscribe[String, String](topics, kafkaParams)
> )
> stream.foreachRDD { rdd =>
>val offsetRanges = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
>rdd.foreachPartition { iter =>
> val o: OffsetRange = offsetRanges(TaskContext.get.partitionId)
> println(s"${o.topic} ${o.partition} ${o.fromOffset} ${o.untilOffset}")
>}
>val rddCount = rdd.count()
>println("rdd count: ", rddCount)
>// stream.asInstanceOf[CanCommitOffsets].commitAsync(offsetRanges)
> }
> ssc.start()
> ssc.awaitTermination()
> {code}
> All partitions show offset ranges from 0 to 0 and all rdds are empty. I would
> like it to start from the beginning of a partition but also pick up
> everything that is being produced to it.
> I have also tried using spark-streaming-kafka-0.8 and it does work. I think
> it is a 0.10 issue because everything else works fine. Thank you!
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