I use 'pio train -- --master yarn' It works for me to train universal recommender
On Tue, May 29, 2018 at 8:31 PM, Miller, Clifford < [email protected]> wrote: > To add more details to this. When I attempt to execute my training job > using the command 'pio train -- --master yarn' I get the exception that > I've included below. Can anyone tell me how to correctly submit the > training job or what setting I need to change to make this work. I've made > not custom code changes and am simply using PIO 0.12.1 with the > SimilarProduct Recommender. > > > > [ERROR] [SparkContext] Error initializing SparkContext. > [INFO] [ServerConnector] Stopped Spark@1f992a3a{HTTP/1.1}{0.0.0.0:4040} > [WARN] [YarnSchedulerBackend$YarnSchedulerEndpoint] Attempted to request > executors before the AM has registered! > [WARN] [MetricsSystem] Stopping a MetricsSystem that is not running > Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException: 1 > at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$$anonfun$ > setEnvFromInputString$1.apply(YarnSparkHadoopUtil.scala:154) > at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$$anonfun$ > setEnvFromInputString$1.apply(YarnSparkHadoopUtil.scala:152) > at scala.collection.IndexedSeqOptimized$class. > foreach(IndexedSeqOptimized.scala:33) > at scala.collection.mutable.ArrayOps$ofRef.foreach( > ArrayOps.scala:186) > at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$. > setEnvFromInputString(YarnSparkHadoopUtil.scala:152) > at org.apache.spark.deploy.yarn.Client$$anonfun$ > setupLaunchEnv$6.apply(Client.scala:819) > at org.apache.spark.deploy.yarn.Client$$anonfun$ > setupLaunchEnv$6.apply(Client.scala:817) > at scala.Option.foreach(Option.scala:257) > at org.apache.spark.deploy.yarn.Client.setupLaunchEnv(Client. > scala:817) > at org.apache.spark.deploy.yarn.Client. > createContainerLaunchContext(Client.scala:911) > at org.apache.spark.deploy.yarn.Client.submitApplication( > Client.scala:172) > at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend. > start(YarnClientSchedulerBackend.scala:56) > at org.apache.spark.scheduler.TaskSchedulerImpl.start( > TaskSchedulerImpl.scala:156) > at org.apache.spark.SparkContext.<init>(SparkContext.scala:509) > at org.apache.predictionio.workflow.WorkflowContext$. > apply(WorkflowContext.scala:45) > at org.apache.predictionio.workflow.CoreWorkflow$. > runTrain(CoreWorkflow.scala:59) > at org.apache.predictionio.workflow.CreateWorkflow$.main( > CreateWorkflow.scala:251) > at org.apache.predictionio.workflow.CreateWorkflow.main( > CreateWorkflow.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.SparkSubmit$.org$apache$spark$ > deploy$SparkSubmit$$runMain(SparkSubmit.scala:751) > at org.apache.spark.deploy.SparkSubmit$.doRunMain$1( > SparkSubmit.scala:187) > at org.apache.spark.deploy.SparkSubmit$.submit( > SparkSubmit.scala:212) > at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit. > scala:126) > at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) > > > > > On Tue, May 29, 2018 at 12:01 AM, Miller, Clifford < > [email protected]> wrote: > >> So updating the version in the RELEASE file to 2.1.1 fixed the version >> detection problem but I'm still not able to submit Spark jobs unless they >> are strictly local. How are you submitting to the HDP Spark? >> >> Thanks, >> >> --Cliff. >> >> >> >> On Mon, May 28, 2018 at 1:12 AM, suyash kharade <[email protected] >> > wrote: >> >>> Hi Miller, >>> I faced same issue. >>> It is giving error as release file has '-' in version >>> Insert simple version in release file something like 2.6. >>> >>> On Mon, May 28, 2018 at 4:32 AM, Miller, Clifford < >>> [email protected]> wrote: >>> >>>> *I've installed an HDP cluster with Hbase and Spark with YARN. As part >>>> of that installation I created some HDP (Ambari) managed clients. I >>>> installed PIO on one of these clients and configured PIO to use the HDP >>>> installed Hadoop, HBase, and Spark. When I run the command 'pio >>>> eventserver &', I get the following error.* >>>> >>>> #### >>>> /home/centos/PredictionIO-0.12.1/bin/semver.sh: line 89: [: >>>> 2.2.6.2.14-5: integer expression expected >>>> /home/centos/PredictionIO-0.12.1/bin/semver.sh: line 93: [[: >>>> 2.2.6.2.14-5: syntax error: invalid arithmetic operator (error token is >>>> ".2.6.2.14-5") >>>> /home/centos/PredictionIO-0.12.1/bin/semver.sh: line 97: [[: >>>> 2.2.6.2.14-5: syntax error: invalid arithmetic operator (error token is >>>> ".2.6.2.14-5") >>>> You have Apache Spark 2.1.1.2.6.2.14-5 at /usr/hdp/2.6.2.14-5/spark2/ >>>> which does not meet the minimum version requirement of 1.3.0. >>>> Aborting. >>>> >>>> #### >>>> >>>> *If I then go to /usr/hdp/2.6.2.14-5/spark2/ and replace the RELEASE >>>> with an empty file, I can then start the Eventserver, which gives me the >>>> following message:* >>>> >>>> ### >>>> /usr/hdp/2.6.2.14-5/spark2/ contains an empty RELEASE file. This is a >>>> known problem with certain vendors (e.g. Cloudera). Please make sure you >>>> are using at least 1.3.0. >>>> [INFO] [Management$] Creating Event Server at 0.0.0.0:7070 >>>> [WARN] [DomainSocketFactory] The short-circuit local reads feature >>>> cannot be used because libhadoop cannot be loaded. >>>> [INFO] [HttpListener] Bound to /0.0.0.0:7070 >>>> [INFO] [EventServerActor] Bound received. EventServer is ready. >>>> #### >>>> >>>> *I can then send events to the Eventserver. After sending the events >>>> listed in the SimilarProduct Recommender example I am unable to train. >>>> Using the cluster. If I use 'pio train' then it successfully trains >>>> locally. If I atttempt to use the command "pio train -- --master yarn" >>>> then I get the following:* >>>> >>>> ####### >>>> Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException: 1 >>>> at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$$anonfun$se >>>> tEnvFromInputString$1.apply(YarnSparkHadoopUtil.scala:154) >>>> at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$$anonfun$se >>>> tEnvFromInputString$1.apply(YarnSparkHadoopUtil.scala:152) >>>> at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSe >>>> qOptimized.scala:33) >>>> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.sca >>>> la:186) >>>> at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$.setEnvFrom >>>> InputString(YarnSparkHadoopUtil.scala:152) >>>> at org.apache.spark.deploy.yarn.Client$$anonfun$setupLaunchEnv$ >>>> 6.apply(Client.scala:819) >>>> at org.apache.spark.deploy.yarn.Client$$anonfun$setupLaunchEnv$ >>>> 6.apply(Client.scala:817) >>>> at scala.Option.foreach(Option.scala:257) >>>> at org.apache.spark.deploy.yarn.Client.setupLaunchEnv(Client.sc >>>> ala:817) >>>> at org.apache.spark.deploy.yarn.Client.createContainerLaunchCon >>>> text(Client.scala:911) >>>> at org.apache.spark.deploy.yarn.Client.submitApplication(Client >>>> .scala:172) >>>> at org.apache.spark.scheduler.cluster.YarnClientSchedulerBacken >>>> d.start(YarnClientSchedulerBackend.scala:56) >>>> at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSched >>>> ulerImpl.scala:156) >>>> at org.apache.spark.SparkContext.<init>(SparkContext.scala:509) >>>> at org.apache.predictionio.workflow.WorkflowContext$.apply(Work >>>> flowContext.scala:45) >>>> at org.apache.predictionio.workflow.CoreWorkflow$.runTrain(Core >>>> Workflow.scala:59) >>>> at org.apache.predictionio.workflow.CreateWorkflow$.main(Create >>>> Workflow.scala:251) >>>> at org.apache.predictionio.workflow.CreateWorkflow.main(CreateW >>>> orkflow.scala) >>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >>>> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAcce >>>> ssorImpl.java:62) >>>> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMe >>>> thodAccessorImpl.java:43) >>>> at java.lang.reflect.Method.invoke(Method.java:498) >>>> at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy >>>> $SparkSubmit$$runMain(SparkSubmit.scala:751) >>>> at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit >>>> .scala:187) >>>> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scal >>>> a:212) >>>> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala: >>>> 126) >>>> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) >>>> >>>> ######## >>>> >>>> *What is the correct way to get PIO to use the YARN based Spark for >>>> training?* >>>> >>>> *Thanks,* >>>> >>>> *--Cliff.* >>>> >>>> >>>> >>>> >>> >>> >>> -- >>> Regards, >>> Suyash K >>> >> >> >> >> >> -- Regards, Suyash K
