Stop and Restart SparkContext executing in deploy mode "cluster" - apache-spark

In order to fit the efficiency requirements, I am forced to stop SparkContext and restart it with a new configuration more optimal in terms of number of executors, memory per executor, executor memory overhead...
I can achieve this launching my spark-submit in client mode :
spark-submit --num-executors 5 \
--deploy-mode client \
--class className spark.jar
And then within my code executing:
spark.stop()
val spark2 : SparkSession = SparkSession.builder
.config("spark.submit.deployMode", "client")
.config("spark.executor.instances", "8")
.getOrCreate()
And everything works OK.
However, when launching in client mode, stopping the SparkContext and restarting sparkContext in cluster mode, I get the following error:
20/05/28 18:05:24 ERROR spark.SparkContext: Error initializing SparkContext.
org.apache.spark.SparkException: Detected yarn cluster mode, but isn't running on a cluster. Deployment to YARN is not supported directly by SparkContext. Please use spark-submit.
at org.apache.spark.SparkContext.<init>(SparkContext.scala:379)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2520)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:935)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:926)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:926)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:849)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:167)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:195)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
20/05/28 18:05:24 ERROR util.Utils: Uncaught exception in thread main
java.lang.NullPointerException
at org.apache.spark.SparkContext.org$apache$spark$SparkContext$$postApplicationEnd(SparkContext.scala:2416)
at org.apache.spark.SparkContext$$anonfun$stop$1.apply$mcV$sp(SparkContext.scala:1931)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1385)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1930)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:585)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2520)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:935)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:926)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:926)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:849)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:167)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:195)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
I have also tried launching spark-submit in cluster mode, stopping SparkCOntext and restarting it again in cluster mode. In this case I get the error:
Exception in thread "main" org.apache.spark.SparkException: Application application_1583287354042_80626 finished with failed status
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1171)
at org.apache.spark.deploy.yarn.YarnClusterApplication.start(Client.scala:1608)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:849)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:167)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:195)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
I am not sure if it might be related to the fact that the driver is running on the cluster...
I'd be very grateful if someone could provide a solution to achieve these requirements.

Related

Unable to read Hbase data with spark in yarn cluster mode

Cluster configuration:
Hadoop: CDH-6.2.1
Spark: 2.4.0
Hbase: 2.0
What I do: Read HBase data through Spark
When I use IntelliJ and local mode everything works fine, but when I change mode to
spark-submit --master yarn, the following stacktrace happens:
20/05/20 11:00:46 ERROR mapreduce.TableInputFormat: java.io.IOException: java.lang.reflect.InvocationTargetException
at org.apache.hadoop.hbase.client.ConnectionFactory.createConnection(ConnectionFactory.java:221)
at org.apache.hadoop.hbase.client.ConnectionFactory.createConnection(ConnectionFactory.java:114)
at org.apache.hadoop.hbase.mapreduce.TableInputFormat.initialize(TableInputFormat.java:200)
at org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:243)
at org.apache.hadoop.hbase.mapreduce.TableInputFormat.getSplits(TableInputFormat.java:254)
at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:131)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2146)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
at com.song.HbaseOnSpark1$.main(HbaseOnSpark1.scala:32)
at com.song.HbaseOnSpark1.main(HbaseOnSpark1.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:673)
Caused by: java.lang.reflect.InvocationTargetException
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.hbase.client.ConnectionFactory.createConnection(ConnectionFactory.java:219)
... 27 more
Caused by: java.lang.NullPointerException
at org.apache.hadoop.hbase.client.ConnectionImplementation.close(ConnectionImplementation.java:1938)
at org.apache.hadoop.hbase.client.ConnectionImplementation.<init>(ConnectionImplementation.java:310)
... 32 more
20/05/20 11:00:46 ERROR yarn.ApplicationMaster: User class threw exception: java.io.IOException: Cannot create a record reader because of a previous error. Please look at the previous logs lines from the task's full log for more details.
java.io.IOException: Cannot create a record reader because of a previous error. Please look at the previous logs lines from the task's full log for more details.
at org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:254)
at org.apache.hadoop.hbase.mapreduce.TableInputFormat.getSplits(TableInputFormat.java:254)
at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:131)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2146)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
at com.song.HbaseOnSpark1$.main(HbaseOnSpark1.scala:32)
at com.song.HbaseOnSpark1.main(HbaseOnSpark1.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:673)
Caused by: java.lang.IllegalStateException: The input format instance has not been properly initialized. Ensure you call initializeTable either in your constructor or initialize method
at org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getTable(TableInputFormatBase.java:558)
at org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:249)
... 24 more
This is my code:
val conf: SparkConf = new SparkConf().setAppName("spark1")
val spark = new SparkContext(conf)
val hbaseConf: Configuration = HBaseConfiguration.create()
hbaseConf.set("hbase.zookeeper.quorum","hadoop01,hadoop02,hadoop03")
hbaseConf.set(TableInputFormat.INPUT_TABLE,"idx_name")
hbaseConf.set("hbase.defaults.for.version.skip", "true")
val rdd: RDD[(ImmutableBytesWritable, Result)] = spark.newAPIHadoopRDD(
hbaseConf,
classOf[TableInputFormat],
classOf[ImmutableBytesWritable],
classOf[Result]
)
its hbase classpatth issue in your cluster but you need to add hbase jars to your classpath like this
export SPARK_CLASSPATH=$SPARK_CLASSPATH:`hbase classpath`
hbase classpath will give all the jars for hbase connections and etc....
Why its working in local mode ?
Since all the jars required are there in ide lib
If you are using maven do a mvn depdency:tree to understand what jars are needed in the cluster. based on that you can adjust your spark-submit script.
if you are using --jars option see that all jars passed correctly or uber jar has correct dependencies when packing jar..
There might be jar conflict also check that carefully with local mode environment since thats working fine.
Further reading Spark spark-submit --jars arguments wants comma list, how to declare a directory of jars?

Failed to submit the Spark Application to Spark REST URL

When submitting the Spark Application to Spark REST URL, always got the exception like the following:
18/04/13 11:54:29 ERROR TransportResponseHandler: Still have 1 requests outstanding when connection from /10.11.9.2:6066 is closed
18/04/13 11:54:29 WARN StandaloneAppClient$ClientEndpoint: Failed to connect to master 10.11.9.2:6066
org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:100)
at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:108)
at org.apache.spark.deploy.client.StandaloneAppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1$$anon$1.run(StandaloneAppClient.scala:106)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
18/04/13 11:55:09 ERROR SparkContext: Error initializing SparkContext.
java.lang.IllegalArgumentException: requirement failed: Can only call getServletHandlers on a running MetricsSystem
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.metrics.MetricsSystem.getServletHandlers(MetricsSystem.scala:91)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:524)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2516)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:918)
at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:910)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:910)
at io.kf.etl.context.Context$$anonfun$getSparkSession$2.apply(Context.scala:76)
at io.kf.etl.context.Context$$anonfun$getSparkSession$2.apply(Context.scala:59)
at scala.Option.map(Option.scala:146)
at io.kf.etl.context.Context$.getSparkSession(Context.scala:59)
at io.kf.etl.context.Context$.sparkSession$lzycompute(Context.scala:20)
at io.kf.etl.context.Context$.sparkSession(Context.scala:20)
at io.kf.etl.processors.common.inject.ProcessorInjectModule.sparkSession$lzycompute(ProcessorInjectModule.scala:8)
at io.kf.etl.processors.common.inject.ProcessorInjectModule.sparkSession(ProcessorInjectModule.scala:8)
at io.kf.etl.processors.download.inject.DownloadInjectModule.getContext(DownloadInjectModule.scala:40)
at io.kf.etl.processors.download.inject.DownloadInjectModule.getProcessor(DownloadInjectModule.scala:54)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at com.google.inject.internal.ProviderMethod.get(ProviderMethod.java:104)
at com.google.inject.internal.InternalFactoryToProviderAdapter.get(InternalFactoryToProviderAdapter.java:40)
at com.google.inject.internal.InjectorImpl$4$1.call(InjectorImpl.java:978)
at com.google.inject.internal.InjectorImpl.callInContext(InjectorImpl.java:1024)
at com.google.inject.internal.InjectorImpl$4.get(InjectorImpl.java:974)
at com.google.inject.internal.InjectorImpl.getInstance(InjectorImpl.java:1013)
at io.kf.etl.ETLMain$.delayedEndpoint$io$kf$etl$ETLMain$1(ETLMain.scala:42)
at io.kf.etl.ETLMain$delayedInit$body.apply(ETLMain.scala:17)
at scala.Function0$class.apply$mcV$sp(Function0.scala:34)
at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
at scala.App$$anonfun$main$1.apply(App.scala:76)
at scala.App$$anonfun$main$1.apply(App.scala:76)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
at scala.App$class.main(App.scala:76)
at io.kf.etl.ETLMain$.main(ETLMain.scala:17)
at io.kf.etl.ETLMain.main(ETLMain.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.worker.DriverWrapper$.main(DriverWrapper.scala:58)
at org.apache.spark.deploy.worker.DriverWrapper.main(DriverWrapper.scala)
18/04/13 11:55:09 INFO SparkContext: SparkContext already stopped.
18/04/13 11:55:09 INFO SparkContext: Successfully stopped SparkContext
I am running Spark 2.2.1 on MacOS
The configurations look like this:
SPARK_LOCAL_IP=10.11.9.2
SPARK_MASTER_HOST=10.11.9.2
The submission command line is
${SPARK_HOME}/bin/spark-submit --master spark://10.11.9.2:6066 --deploy-mode cluster --class ....
If I submitted the application to port 7077, everything is fine.
Hidden REST API is not suppose to be used with spark-submit. Instead all arguments and job definition should be submitted as a http request to http://rest-ip:6066/v1/submissions/create.
Apache spark rest API
Triggering spark jobs with REST
I figured it out by myself.
The submission command line is fine, but when I initialized SparkSession, I also passed in spark://10.11.9.2:6066 as the master string.
if passing in spark://10.11.9.2:7077, everything just works well.

Unable to run Spark in yarn-cluster mode

I'm trying to run spark job with YARN in cluster deploy mode.
I tried to run the simpliest spark-submit command only with jar path, class parameter and master yarn-cluster. However I still have the same error, which actually tells me nothing.
Exception in thread "main" org.apache.spark.SparkException: Application application_1506196351647_0032 finished with failed status
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1078)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1125)
at org.apache.spark.deploy.yarn.Client.main(Client.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
If anyone had the similar problem please let me know, I'm using spark 1.6, hadoop 2.6.

PhoenixOutputFormat not found when running a Spark Job on CDH 5.4 with Phoenix 4.5

I managed to configure Phoenix 4.5 on Cloudera CDH 5.4 by recompiling the source code. sqlline.py works well, but there are problems with spark.
spark-submit --class my.JobRunner \
--master yarn --deploy-mode client \
--jars `ls -dm /myapp/lib/* | tr -d ' \r\n'` \
/myapp/mainjar.jar
The /myapp/lib folders contains the phoenix core lib, which contains class org.apache.phoenix.mapreduce.PhoenixOutputFormat. But it seems that the driver/executor cannot see it.
Exception in thread "main" java.lang.RuntimeException: java.lang.ClassNotFoundException: Class org.apache.phoenix.mapreduce.PhoenixOutputFormat not found
at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2112)
at org.apache.hadoop.mapreduce.task.JobContextImpl.getOutputFormatClass(JobContextImpl.java:232)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:971)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopFile(PairRDDFunctions.scala:903)
at org.apache.phoenix.spark.ProductRDDFunctions.saveToPhoenix(ProductRDDFunctions.scala:51)
at com.mypackage.save(DAOImpl.scala:41)
at com.mypackage.ProtoStreamingJob.execute(ProtoStreamingJob.scala:58)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at com.mypackage.SparkApplication.sparkRun(SparkApplication.scala:95)
at com.mypackage.SparkApplication$delayedInit$body.apply(SparkApplication.scala:112)
at scala.Function0$class.apply$mcV$sp(Function0.scala:40)
at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
at scala.App$$anonfun$main$1.apply(App.scala:71)
at scala.App$$anonfun$main$1.apply(App.scala:71)
at scala.collection.immutable.List.foreach(List.scala:318)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:32)
at scala.App$class.main(App.scala:71)
at com.mypackage.SparkApplication.main(SparkApplication.scala:15)
at com.mypackage.ProtoStreamingJobRunner.main(ProtoStreamingJob.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.ClassNotFoundException: Class org.apache.phoenix.mapreduce.PhoenixOutputFormat not found
at org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:2018)
at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2110)
... 30 more
What can I do to overcome this exception?
Adding phoenix-core to classpath.txt solves the problem. This file is usually located under /etc/spark/conf folder.

Spark 1.1.0 on cdh5.1.3 does not work in yarn-cluster mode

I am having CDH 5.1 (Hadoop 2.3.0-cdh5.1.3) installed on my cluster, version:
I have installed and configured a prebuilt version of Spark 1.1.0 (Apache Version), built for hadoop 2.3 on my cluster.
when I run the Pi example in the ‘client mode’, it runs successfully, but it fails in the ‘yarn-cluster’ mode. The spark job is successfully submitted, but fails after polling the application master for sometime:
More Logs:
Application application_1415193640322_0016 failed 2 times due to Error launching appattempt_1415193640322_0016_000002. Got exception: org.apache.hadoop.yarn.exceptions.YarnException: java.io.EOFException
at org.apache.hadoop.yarn.ipc.RPCUtil.getRemoteException(RPCUtil.java:38)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:710)
at org.apache.hadoop.yarn.api.impl.pb.service.ContainerManagementProtocolPBServiceImpl.startContainers(ContainerManagementProtocolPBServiceImpl.java:60)
at org.apache.hadoop.yarn.proto.ContainerManagementProtocol$ContainerManagementProtocolService$2.callBlockingMethod(ContainerManagementProtocol.java:95)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:587)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1026)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2013)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2009)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2007)
Caused by: java.io.EOFException
at java.io.DataInputStream.readFully(DataInputStream.java:197)
at java.io.DataInputStream.readUTF(DataInputStream.java:609)
at java.io.DataInputStream.readUTF(DataInputStream.java:564)
at org.apache.hadoop.yarn.security.ContainerTokenIdentifier.readFields(ContainerTokenIdentifier.java:151)
at org.apache.hadoop.security.token.Token.decodeIdentifier(Token.java:142)
at org.apache.hadoop.yarn.server.utils.BuilderUtils.newContainerTokenIdentifier(BuilderUtils.java:262)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:696)
... 10 more
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at org.apache.hadoop.yarn.ipc.RPCUtil.instantiateException(RPCUtil.java:53)
at org.apache.hadoop.yarn.ipc.RPCUtil.unwrapAndThrowException(RPCUtil.java:101)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:99)
at org.apache.hadoop.yarn.server.resourcemanager.amlauncher.AMLauncher.launch(AMLauncher.java:118)
at org.apache.hadoop.yarn.server.resourcemanager.amlauncher.AMLauncher.run(AMLauncher.java:249)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.yarn.exceptions.YarnException): java.io.EOFException
at org.apache.hadoop.yarn.ipc.RPCUtil.getRemoteException(RPCUtil.java:38)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:710)
at org.apache.hadoop.yarn.api.impl.pb.service.ContainerManagementProtocolPBServiceImpl.startContainers(ContainerManagementProtocolPBServiceImpl.java:60)
at org.apache.hadoop.yarn.proto.ContainerManagementProtocol$ContainerManagementProtocolService$2.callBlockingMethod(ContainerManagementProtocol.java:95)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:587)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1026)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2013)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2009)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2007)
Caused by: java.io.EOFException
at java.io.DataInputStream.readFully(DataInputStream.java:197)
at java.io.DataInputStream.readUTF(DataInputStream.java:609)
at java.io.DataInputStream.readUTF(DataInputStream.java:564)
at org.apache.hadoop.yarn.security.ContainerTokenIdentifier.readFields(ContainerTokenIdentifier.java:151)
at org.apache.hadoop.security.token.Token.decodeIdentifier(Token.java:142)
at org.apache.hadoop.yarn.server.utils.BuilderUtils.newContainerTokenIdentifier(BuilderUtils.java:262)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl.startContainers(ContainerManagerImpl.java:696)
... 10 more
at org.apache.hadoop.ipc.Client.call(Client.java:1409)
at org.apache.hadoop.ipc.Client.call(Client.java:1362)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:206)
at com.sun.proxy.$Proxy69.startContainers(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:96)
... 5 more
. Failing the application.
When I go to node Manager logs:
Log Type: stderr
Log Length: 87
Error: Could not find or load main class org.apache.spark.deploy.yarn.ExecutorLauncher
Can you please suggest any solution.Do you think I should compile the spark code on my cluster. Or should I use Spark provided with CDH5.1.
Any help will be appreciated!
spark-shell does not work with spark yarn-cluster mode. You should add --master yarn-client
Example:
path/to/pyspark --master yarn-client

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