Yes, I tried ssc.checkpoint("checkpoint"), it works for me as long as i
don't use reduceByKeyAndWindow.
When i start using "reduceByKeyAndWindow" it complains me with the error
"Exception in thread "main" org.apache.spark.SparkException: Invalid
checkpoint directory: file:/home/ubuntu/checkpoint/342e3171-01f3-48$
2-97be-e3862eb5c944/rdd-8"
The stack trace is as below:
Exception in thread "main" org.apache.spark.SparkException: Invalid
checkpoint directory: file:/home/ubuntu/checkpoint/342e3171[22/9706$
2-97be-e3862eb5c944/rdd-8
at
org.apache.spark.rdd.CheckpointRDD.getPartitions(CheckpointRDD.scala:54)
at
org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
at
org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
at
org.apache.spark.rdd.RDDCheckpointData.doCheckpoint(RDDCheckpointData.scala:97)
at org.apache.spark.rdd.RDD.doCheckpoint(RDD.scala:1415)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.rdd.RDD.doCheckpoint(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.rdd.RDD.doCheckpoint(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at
scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.rdd.RDD.doCheckpoint(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at
scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.rdd.RDD.doCheckpoint(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at
scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.rdd.RDD.doCheckpoint(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
org.apache.spark.rdd.RDD$$anonfun$doCheckpoint$1.apply(RDD.scala:1417)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at
scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.rdd.RDD.doCheckpoint(RDD.scala:1417)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1468)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1483)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1504)
at
com.datastax.spark.connector.streaming.DStreamFunctions$$anonfun$saveToCassandra$1.apply(DStreamFunctions.scala:33)
at
com.datastax.spark.connector.streaming.DStreamFunctions$$anonfun$saveToCassandra$1.apply(DStreamFunctions.scala:33)
at
org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1.apply(DStream.scala:534)
at
org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1.apply(DStream.scala:534)
at
org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:42)
at
org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40)
at
org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40)
at scala.util.Try$.apply(Try.scala:161)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32)
at
org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:176)
at
org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:176)
at
org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:176)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
at
org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:175)
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)
On Tue, Sep 22, 2015 at 6:49 PM, Adrian Tanase <atan...@adobe.com> wrote:
> Have you tried simply ssc.checkpoint("checkpoint”)? This should create it
> in the local folder, has always worked for me when in development on local
> mode.
>
> For the others (/tmp/..) make sure you have rights to write there.
>
> -adrian
>
> From: srungarapu vamsi
> Date: Tuesday, September 22, 2015 at 7:59 AM
> To: user
> Subject: Invalid checkpoint url
>
> I am using reduceByKeyAndWindow (with inverse reduce function) in my code.
> In order to use this, it seems the checkpointDirectory which i have to use
> should be hadoop compatible file system.
> Does that mean that, i should setup hadoop on my system.
> I googled about this and i found in a S.O answer that i need not setup
> hdfs but the checkpoint directory should be HDFS copatible.
>
> I am a beginner in this area. I am running my spark streaming application
> on ubuntu 14.04, spark -1.3.1
> If at all i need not setup hdfs and ext4 is hdfs compatible, then how does
> my checkpoint directory look like?
>
> i tried all these:
> ssc.checkpoint("/tmp/checkpoint")
> ssc.checkpoint("hdfs:///tmp/checkpoint")
> ssc.checkpoint("file:///tmp/checkpoint")
>
> But none of them worked for me.
>
> --
> /Vamsi
>
--
/Vamsi
