spark kinesis failing on cloudera with java.lang.AbstractMethodError - apache-spark

Question

below is my POM file. I am writing a spark streaming with aws kinesis
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.10</artifactId>
<version>1.6.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.6.0</version>
</dependency>
<dependency>
<groupId>com.amazonaws</groupId>
<artifactId>amazon-kinesis-client</artifactId>
<version>1.6.1</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming-kinesis-asl_2.10</artifactId>
<version>1.6.0</version>
</dependency>
I am facing below exception during run of spark of spark program on Cloudera 5.10
17/04/27 05:34:04 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 58.0 (TID 179, hadoop1.local, executor 5): java.lang.AbstractMethodError
at org.apache.spark.Logging$class.log(Logging.scala:50)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.log(KinesisCheckpointer.scala:39)
at org.apache.spark.Logging$class.logDebug(Logging.scala:62)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.logDebug(KinesisCheckpointer.scala:39)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.startCheckpointerThread(KinesisCheckpointer.scala:119)
at org.apache.spark.streaming.kinesis.KinesisCheckpointer.<init>(KinesisCheckpointer.scala:50)
at org.apache.spark.streaming.kinesis.KinesisReceiver.onStart(KinesisReceiver.scala:149)
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$$anonfun$38.apply(SparkContext.scala:2000)
at org.apache.spark.SparkContext$$anonfun$38.apply(SparkContext.scala:2000)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:242)
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)
This runs perfectly fine on EMR4.4 However CDH fails. Any suggestion

Answer 1

The underlying problem seems to be the use of org.apache.spark.Logging:
NOTE: DO NOT USE this class outside of Spark.
It is intended as an internal utility.
This will likely be changed or removed in future releases.
http://spark.apache.org/docs/1.6.2/api/java/org/apache/spark/Logging.html
This is fixed in 2.0.0 as mentioned in https://issues.apache.org/jira/browse/SPARK-9307.