Local Kafka Application failing with: NoSuchMethodError: createEphemeral - apache-spark

Question

I am trying to run my spark application in local mode. To set it up all, I followed this tutorial: http://blog.d2-si.fr/2015/11/05/apache-kafka-3/, (in
French) showing each step to build up the local kafka/zookeeper environment.
Moreover, I use IntelliJ with the following configuration:
val sparkConf = new SparkConf().setAppName("zumbaApp").setMaster("local[2]")
And my run config, for the consumer:
"127.0.0.1:2181" "zumbaApp-gpId" "D2SI" "1"
And for the producer:
"127.0.0.1:9092" "D2SI" "my\Input\File.csv" 300
Beforehand, I checked if the consumer received the inputs from the producer with the default console-producer and console-consumer of kafka_2.10-0.9.0.1 ; it does.
But, I am facing the following error:
java.lang.NoSuchMethodError: org.I0Itec.zkclient.ZkClient.createEphemeral(Ljava/lang/String;Ljava/lang/Object;Ljava/util/List;)V
at kafka.utils.ZkPath$.createEphemeral(ZkUtils.scala:921)
at kafka.utils.ZkUtils.createEphemeralPath(ZkUtils.scala:348)
at kafka.utils.ZkUtils.createEphemeralPathExpectConflict(ZkUtils.scala:363)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener$$anonfun$18.apply(ZookeeperConsumerConnector.scala:839)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener$$anonfun$18.apply(ZookeeperConsumerConnector.scala:833)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:98)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:98)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:226)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:39)
at scala.collection.mutable.HashMap.foreach(HashMap.scala:98)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.AbstractTraversable.map(Traversable.scala:105)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener.reflectPartitionOwnershipDecision(ZookeeperConsumerConnector.scala:833)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener.kafka$consumer$ZookeeperConsumerConnector$ZKRebalancerListener$$rebalance(ZookeeperConsumerConnector.scala:721)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener$$anonfun$syncedRebalance$1$$anonfun$apply$mcV$sp$1.apply$mcVI$sp(ZookeeperConsumerConnector.scala:636)
at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:141)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener$$anonfun$syncedRebalance$1.apply$mcV$sp(ZookeeperConsumerConnector.scala:627)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener$$anonfun$syncedRebalance$1.apply(ZookeeperConsumerConnector.scala:627)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener$$anonfun$syncedRebalance$1.apply(ZookeeperConsumerConnector.scala:627)
at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
at kafka.consumer.ZookeeperConsumerConnector$ZKRebalancerListener.syncedRebalance(ZookeeperConsumerConnector.scala:626)
at kafka.consumer.ZookeeperConsumerConnector.kafka$consumer$ZookeeperConsumerConnector$$reinitializeConsumer(ZookeeperConsumerConnector.scala:967)
at kafka.consumer.ZookeeperConsumerConnector.consume(ZookeeperConsumerConnector.scala:254)
at kafka.consumer.ZookeeperConsumerConnector.createMessageStreams(ZookeeperConsumerConnector.scala:156)
at org.apache.spark.streaming.kafka.KafkaReceiver.onStart(KafkaInputDStream.scala:111)
at org.apache.spark.streaming.receiver.ReceiverSupervisor.startReceiver(ReceiverSupervisor.scala:148)
at org.apache.spark.streaming.receiver.ReceiverSupervisor.start(ReceiverSupervisor.scala:130)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:575)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:565)
at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1992)
at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1992)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
I did not succeed in solving this. I thought it was a zookeeper-config error but after comparing with a working version of the application on another machine with the same configuration files, It does not seem it is anymore.

Answer 1

Looks like you have a dependency issue here.
Check the version of the library com.101tec.zkclient in our classpath. Kafka needs the version 0.7
In addition, since kafka_2.10-0.9.0.1 the APIs for both producer and consumer don't use zookeeper anymore. It seems that Spark-streaming uses a 0.8 version of Kafka in your case.