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https://issues.apache.org/jira/browse/SPARK-11193?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14966030#comment-14966030
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Phil Kallos commented on SPARK-11193:
-------------------------------------
regarding the SynchronizedMap warning, you can find it on the scala doc page
here:
http://www.scala-lang.org/api/2.11.4/index.html#scala.collection.mutable.SynchronizedMap
{quote}(Since version 2.11.0) Synchronization via traits is deprecated as it is
inherently unreliable. Consider java.util.concurrent.ConcurrentHashMap as an
alternative.{quote}
Not sure what the implications are for scala 2.10 and the KinesisReceiver are,
however?
I will try replacing with SynchronizedMap with ConcurrentHashMap and see if I
can find out.
> Spark 1.5+ Kinesis Streaming - ClassCastException when starting
> KinesisReceiver
> -------------------------------------------------------------------------------
>
> Key: SPARK-11193
> URL: https://issues.apache.org/jira/browse/SPARK-11193
> Project: Spark
> Issue Type: Bug
> Components: Streaming
> Affects Versions: 1.5.0, 1.5.1
> Reporter: Phil Kallos
> Attachments: screen.png
>
>
> After upgrading from Spark 1.4.x -> 1.5.x, I am now unable to start a Kinesis
> Spark Streaming application, and am being consistently greeted with this
> exception:
> java.lang.ClassCastException: scala.collection.mutable.HashMap cannot be cast
> to scala.collection.mutable.SynchronizedMap
> at
> org.apache.spark.streaming.kinesis.KinesisReceiver.onStart(KinesisReceiver.scala:175)
> 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$$anonfun$9.apply(ReceiverTracker.scala:542)
> at
> org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:532)
> at
> org.apache.spark.SparkContext$$anonfun$38.apply(SparkContext.scala:1982)
> at
> org.apache.spark.SparkContext$$anonfun$38.apply(SparkContext.scala:1982)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> Worth noting that I am able to reproduce this issue locally, and also on
> Amazon EMR (using the latest emr-release 4.1.0 which packages Spark 1.5.0).
> Also, I am not able to run the included kinesis-asl example.
> Built locally using:
> git checkout v1.5.1
> mvn -Pyarn -Pkinesis-asl -Phadoop-2.6 -DskipTests clean package
> Example run command:
> bin/run-example streaming.KinesisWordCountASL phibit-test kinesis-connector
> https://kinesis.us-east-1.amazonaws.com
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