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 < clifford.mil...@phoenix-opsgroup.com> 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 <suyash.khar...@gmail.com> > 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 < >> clifford.mil...@phoenix-opsgroup.com> 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 >> > > > > >