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https://issues.apache.org/jira/browse/SPARK-20611?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15998050#comment-15998050
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Sean Owen commented on SPARK-20611:
-----------------------------------
No, there's not necessarily any problem in Spark. The Logging trait changed
over versions of Spark -- not in CDH -- and if you don't match the versions
correctly, this internal API may not be compatible across releases, because
it's not an external API. For example you generally use Spark 2 in CDH 5.10 but
you are targeting 1.6. CDH doesn't support the Kinesis connector, though it may
happen to work. This is in any event not an issue for Spark.
> Spark kinesis connector doesnt work with cloudera distribution
> ---------------------------------------------------------------
>
> Key: SPARK-20611
> URL: https://issues.apache.org/jira/browse/SPARK-20611
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.0
> Reporter: sumit
> Labels: cloudera
> Attachments: spark-kcl.patch
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> Facing below exception on CDH5.10
> 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)
> below is my POM file
> <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>
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