Hi All, We are using the Apache Spark 1.5.1 and kafka_2.10-0.8.2.1 and Kafka DirectStream API to fetch data from Kafka using Spark.
Kafka topic properties: Replication Factor :1 and Partitions : 1 Kafka cluster size: 3 Nodes When all Kafka nodes are up & running, I could successfully get the data for all the topics. But when one of the Kafka node is down , we are getting below exceptions and though the Node is up after some time, still we are not succeeded, and the spark job is terminated. and unable fetch the data from remaining topics in Kafka. ERROR DirectKafkaInputDStream:125 - ArrayBuffer(org.apache.spark.SparkException: Couldn't find leaders for Set([normalized-tenant4,0])) ERROR JobScheduler:96 - Error generating jobs for time 1447929990000 ms org.apache.spark.SparkException: ArrayBuffer(org.apache.spark.SparkException: Couldn't find leaders for Set([normalized-tenant4,0])) at org.apache.spark.streaming.kafka.DirectKafkaInputDStream.latestLeaderOffsets(DirectKafkaInputDStream.scala:123) at org.apache.spark.streaming.kafka.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:145) at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399) at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344) at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342) at scala.Option.orElse(Option.scala:257) at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339) at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:38) at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120) at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120) at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251) at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251) at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105) at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:120) at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:247) at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:245) at scala.util.Try$.apply(Try.scala:161) at org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:245) at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:181) at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:87) at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:86) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) Thanks in advance please help how to resolve the issue. Thanks & Regards, Ganga Phani Charan Adabala | Software Engineer o: +91-40-23116680 | c: +91-9491418099 EiQ Networks, Inc.<http://www.eiqnetworks.com/> [cid:image001.png@01D11C9D.AF5CC1F0]<http://www.eiqnetworks.com/> "This email is intended only for the use of the individual or entity named above and may contain information that is confidential and privileged. If you are not the intended recipient, you are hereby notified that any dissemination, distribution or copying of the email is strictly prohibited. If you have received this email in error, please destroy the original message."