libraryDependencies += "org.apache.spark" % "spark-core_2.10" % "1.6.0" libraryDependencies += "org.apache.spark" % "spark-streaming_2.10" % "1.6.0" libraryDependencies += "org.apache.spark" % "spark-streaming-kafka_2.10" % "1.6.1" Please take a look at the SBT copy.
I would rather think that the problem is related to the Zookeeper/Kafka consumers. [2016-06-07 11:24:52,484] WARN Either no config or no quorum defined in config, running in standalone mode (org.apache.zookeeper.server.quorum.QuorumPeerMain) Any indication onto why the channel connection might be closed? Would it be Kafka or Zookeeper related? > On 07 Jun 2016, at 14:07, Todd Nist <tsind...@gmail.com> wrote: > > What version of Spark are you using? I do not believe that 1.6.x is > compatible with 0.9.0.1 due to changes in the kafka clients between 0.8.2.2 > and 0.9.0.x. See this for more information: > > https://issues.apache.org/jira/browse/SPARK-12177 > <https://issues.apache.org/jira/browse/SPARK-12177> > > -Todd > > On Tue, Jun 7, 2016 at 7:35 AM, Dominik Safaric <dominiksafa...@gmail.com > <mailto:dominiksafa...@gmail.com>> wrote: > Hi, > > Correct, I am using the 0.9.0.1 version. > > As already described, the topic contains messages. Those messages are > produced using the Confluence REST API. > > However, what I’ve observed is that the problem is not in the Spark > configuration, but rather Zookeeper or Kafka related. > > Take a look at the exception’s stack top item: > > org.apache.spark.SparkException: java.nio.channels.ClosedChannelException > org.apache.spark.SparkException: Couldn't find leader offsets for > Set([<topicname>,0]) > at > org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$checkErrors$1.apply(KafkaCluster.scala:366) > at > org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$checkErrors$1.apply(KafkaCluster.scala:366) > at scala.util.Either.fold(Either.scala:97) > at > org.apache.spark.streaming.kafka.KafkaCluster$.checkErrors(KafkaCluster.scala:365) > at > org.apache.spark.streaming.kafka.KafkaUtils$.getFromOffsets(KafkaUtils.scala:222) > at > org.apache.spark.streaming.kafka.KafkaUtils$.createDirectStream(KafkaUtils.scala:484) > at org.mediasoft.spark.Driver$.main(Driver.scala:22) > at .<init>(<console>:11) > at .<clinit>(<console>) > at .<init>(<console>:7) > > By listing all active connections using netstat, I’ve also observed that both > Zookeper and Kafka are running. Zookeeper on port 2181, while Kafka 9092. > > Furthermore, I am also able to retrieve all log messages using the console > consumer. > > Any clue what might be going wrong? > >> On 07 Jun 2016, at 13:13, Jacek Laskowski <ja...@japila.pl >> <mailto:ja...@japila.pl>> wrote: >> >> Hi, >> >> What's the version of Spark? You're using Kafka 0.9.0.1, ain't you? What's >> the topic name? >> >> Jacek >> >> On 7 Jun 2016 11:06 a.m., "Dominik Safaric" <dominiksafa...@gmail.com >> <mailto:dominiksafa...@gmail.com>> wrote: >> As I am trying to integrate Kafka into Spark, the following exception occurs: >> >> org.apache.spark.SparkException: java.nio.channels.ClosedChannelException >> org.apache.spark.SparkException: Couldn't find leader offsets for >> Set([*<topicName>*,0]) >> at >> org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$checkErrors$1.apply(KafkaCluster.scala:366) >> at >> org.apache.spark.streaming.kafka.KafkaCluster$$anonfun$checkErrors$1.apply(KafkaCluster.scala:366) >> at scala.util.Either.fold(Either.scala:97) >> at >> org.apache.spark.streaming.kafka.KafkaCluster$.checkErrors(KafkaCluster.scala:365) >> at >> org.apache.spark.streaming.kafka.KafkaUtils$.getFromOffsets(KafkaUtils.scala:222) >> at >> org.apache.spark.streaming.kafka.KafkaUtils$.createDirectStream(KafkaUtils.scala:484) >> at org.mediasoft.spark.Driver$.main(Driver.scala:42) >> at .<init>(<console>:11) >> at .<clinit>(<console>) >> at .<init>(<console>:7) >> at .<clinit>(<console>) >> at $print(<console>) >> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> at >> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) >> at >> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >> at java.lang.reflect.Method.invoke(Method.java:483) >> at >> scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:734) >> at >> scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:983) >> at scala.tools.nsc.interpreter.IMain.loadAndRunReq$1(IMain.scala:573) >> at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:604) >> at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:568) >> at >> scala.tools.nsc.interpreter.ILoop.reallyInterpret$1(ILoop.scala:760) >> at >> scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:805) >> at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:717) >> at scala.tools.nsc.interpreter.ILoop.processLine$1(ILoop.scala:581) >> at scala.tools.nsc.interpreter.ILoop.innerLoop$1(ILoop.scala:588) >> at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:591) >> at >> scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:882) >> at >> scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:837) >> at >> scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:837) >> at >> scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135) >> at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:837) >> at scala.tools.nsc.interpreter.ILoop.main(ILoop.scala:904) >> at >> org.jetbrains.plugins.scala.compiler.rt.ConsoleRunner.main(ConsoleRunner.java:64) >> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> at >> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) >> at >> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >> at java.lang.reflect.Method.invoke(Method.java:483) >> at >> com.intellij.rt.execution.application.AppMain.main(AppMain.java:144) >> >> As for the Spark configuration: >> >> val conf: SparkConf = new >> SparkConf().setAppName("AppName").setMaster("local[2]") >> >> val confParams: Map[String, String] = Map( >> "metadata.broker.list" -> "<IP_ADDRESS>:9092", >> "auto.offset.reset" -> "largest" >> ) >> >> val topics: Set[String] = Set("<topic_name>") >> >> val context: StreamingContext = new StreamingContext(conf, Seconds(1)) >> val kafkaStream = KafkaUtils.createDirectStream(context,confParams, >> topics) >> >> kafkaStream.foreachRDD(rdd => { >> rdd.collect().foreach(println) >> }) >> >> context.awaitTermination() >> context.start() >> >> The Kafka topic does exist, Kafka server is up and running and I am able to >> produce messages to that particular topic using the Confluent REST API. >> >> What might the problem actually be? >> >> >> >> >> -- >> View this message in context: >> http://apache-spark-user-list.1001560.n3.nabble.com/Apache-Spark-Kafka-Integration-org-apache-spark-SparkException-Couldn-t-find-leader-offsets-for-Set-tp27103.html >> >> <http://apache-spark-user-list.1001560.n3.nabble.com/Apache-Spark-Kafka-Integration-org-apache-spark-SparkException-Couldn-t-find-leader-offsets-for-Set-tp27103.html> >> Sent from the Apache Spark User List mailing list archive at Nabble.com >> <http://nabble.com/>. >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> <mailto:user-unsubscr...@spark.apache.org> >> For additional commands, e-mail: user-h...@spark.apache.org >> <mailto:user-h...@spark.apache.org> >> > >
