I have scala code which uses the Htable class of Hbase , I am building that as jar and running using spark-submit like below
spark2-submit --conf spark.driver.extraClassPath=/opt/cloudera/parcels/CDH-5.11.0-1.cdh5.11.0.p0.34/lib/hbase/lib/* --class commontest scala-maven-plugin-0.0.1-SNAPSHOT.jar
I am passing the hbase class path using extraClassPath , but still getting below error, has anyone got this error ?
Exception in thread "main" java.lang.NoSuchMethodError: com.fasterxml.jackson.module.scala.deser.BigDecimalDeserializer$.handledType()Ljava/lang/Class;
at com.fasterxml.jackson.module.scala.deser.NumberDeserializers$.<init>(ScalaNumberDeserializersModule.scala:49)
at com.fasterxml.jackson.module.scala.deser.NumberDeserializers$.<clinit>(ScalaNumberDeserializersModule.scala)
at com.fasterxml.jackson.module.scala.deser.ScalaNumberDeserializersModule$class.$init$(ScalaNumberDeserializersModule.scala:61)
at com.fasterxml.jackson.module.scala.DefaultScalaModule.<init>(DefaultScalaModule.scala:20)
at com.fasterxml.jackson.module.scala.DefaultScalaModule$.<init>(DefaultScalaModule.scala:37)
at com.fasterxml.jackson.module.scala.DefaultScalaModule$.<clinit>(DefaultScalaModule.scala)
at org.apache.spark.util.JsonProtocol$.<init>(JsonProtocol.scala:59)
at org.apache.spark.util.JsonProtocol$.<clinit>(JsonProtocol.scala)
at org.apache.spark.scheduler.EventLoggingListener$.initEventLog(EventLoggingListener.scala:270)
at org.apache.spark.scheduler.EventLoggingListener.start(EventLoggingListener.scala:121)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:531)
at KPICommonDeviceDayUsage$.main(KPICommonDeviceDayUsage.scala:339)
at KPICommonDeviceDayUsage.main(KPICommonDeviceDayUsage.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$$runMain(SparkSubmit.scala:738)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Exception in thread "main" java.lang.NoSuchMethodError:
com.fasterxml.jackson.module.scala.deser.BigDecimalDeserializer$.handledType()Ljava/lang/Class;
This exception indicates that you have multiple versions of the library available at run-time.
Related
I usually work with Pyspark but I had to deal with a spark streaming job written in Scala. I am running the spark-submit on EMR directly it works but running the same through Airflow throws me the following error. I don't even to where to start debugging the issue. Any ideas would be greatly appreciated.
org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:226)
at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:468)
at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:305)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply$mcV$sp(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:779)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1844)
at org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:778)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:244)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:803)
at org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
Caused by: com.typesafe.config.ConfigException$IO: available_application.properties -Dlog4j.configuration=log4j-yarn.properties: java.io.FileNotFoundException: available_application.properties -Dlog4j.configuration=log4j-yarn.properties (No such file or directory)
at com.typesafe.config.impl.Parseable.parseValue(Parseable.java:183)
at com.typesafe.config.impl.Parseable.parseValue(Parseable.java:170)
at com.typesafe.config.impl.Parseable.parse(Parseable.java:227)
at com.typesafe.config.ConfigFactory.parseFile(ConfigFactory.java:595)
at com.typesafe.config.ConfigFactory.loadDefaultConfig(ConfigFactory.java:244)
at com.typesafe.config.ConfigFactory.access$000(ConfigFactory.java:38)
at com.typesafe.config.ConfigFactory$1.call(ConfigFactory.java:378)
at com.typesafe.config.ConfigFactory$1.call(ConfigFactory.java:375)
at com.typesafe.config.impl.ConfigImpl$LoaderCache.getOrElseUpdate(ConfigImpl.java:58)
at com.typesafe.config.impl.ConfigImpl.computeCachedConfig(ConfigImpl.java:86)
at com.typesafe.config.ConfigFactory.load(ConfigFactory.java:375)
at com.typesafe.config.ConfigFactory.load(ConfigFactory.java:299)
at com.typesafe.config.ConfigFactory.load(ConfigFactory.java:288)
at com.nike.tdp.AvailabilityKafkaEvents$.main(AvailabilityKafkaEvents.scala:101)
at com.nike.tdp.AvailabilityKafkaEvents.main(AvailabilityKafkaEvents.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:684)
Caused by: java.io.FileNotFoundException: available_application.properties -Dlog4j.configuration=log4j-yarn.properties (No such file or directory)
at java.io.FileInputStream.open0(Native Method)
at java.io.FileInputStream.open(FileInputStream.java:195)
at java.io.FileInputStream.<init>(FileInputStream.java:138)
at com.typesafe.config.impl.Parseable$ParseableFile.reader(Parseable.java:512)
at com.typesafe.config.impl.Parseable.rawParseValue(Parseable.java:193)
at com.typesafe.config.impl.Parseable.parseValue(Parseable.java:176)
... 19 more
22/10/26 19:14:02 INFO ShutdownHookManager: Shutdown hook called
Caused by: java.io.FileNotFoundException: available_application.properties -Dlog4j.configuration=log4j-yarn.properties
is the main piece of information in the error you've shown.
It looks like you've made a typo in the parameters for running the app and available_application.properties -Dlog4j.configuration=log4j-yarn.properties is interpreted as the configuration file name instead of only available_application.properties (I assume).
Check the parameters used to run your app, maybe quotes in wrong place or missing? Maybe extra whitespace? ...
I am currently using John Snow labs SparkNLP library to train a custom NER Model. I am able to successfully complete the training and the model is getting saved to the disk. When I try to load the model for next step to actually tag some sample data I run into the following error. I using the Ubuntu on Windows 10. spark-nlp_2.12:3.1.2 with Spark 3.1.2, scala 2.12.10 OpenJDK 8
I have also tried the same on PySpark I get same the exact error
pyspark error:
java.lang.NoSuchMethodException:
org.apache.spark.ml.PipelineModel.(java.lang.String)
at java.lang.Class.getConstructor0(Class.java:3082)
at java.lang.Class.getConstructor(Class.java:1825)
at org.apache.spark.ml.util.DefaultParamsReader.load(ReadWrite.scala:468)
at com.johnsnowlabs.nlp.FeaturesReader.load(ParamsAndFeaturesReadable.scala:12)
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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Any help is appreciated. Scala version error
java.lang.NoSuchMethodException:
org.apache.spark.ml.PipelineModel.(java.lang.String) at
java.lang.Class.getConstructor0(Class.java:3082) at
java.lang.Class.getConstructor(Class.java:1825) at
org.apache.spark.ml.util.DefaultParamsReader.load(ReadWrite.scala:468)
at
com.johnsnowlabs.nlp.FeaturesReader.load(ParamsAndFeaturesReadable.scala:12)
at
com.johnsnowlabs.nlp.FeaturesReader.load(ParamsAndFeaturesReadable.scala:8)
val loaded_ner_model = NerDLModel.load("./NER_bert_prod_20200221")
.setInputCols("sentence", "token", "bert")
.setOutputCol("ner")
I'm trying to query MongoDB using Spark SQL shell. I have a limitation that I can only use SQL: no Scala, Python, etc. I intend to use Thrift, but for proof of concept, I am using spark-sql. I'm using EMR with Spark version 2.4.4. More info:
Using Scala version 2.11.12, OpenJDK 64-Bit Server VM, 1.8.0_242
Branch HEAD
Compiled by user ec2-user on 2019-12-14T00:54:30Z
Revision 5f788d5e8f90539ee331702c753fa250727128f4
Url git#aws157git.com:/pkg/Aws157BigTop
Type --help for more information.
I start my shell with a pointer to MongoDB Spark maven coordinates:
spark-sql --packages org.mongodb.spark:mongo-spark-connector_2.12:2.4.1 --conf spark.mongodb.input.uri=mongodb://something.real/development?readPreference=secondary
Spark SQL seems to recognise the jar, via the logs:
org.mongodb.spark#mongo-spark-connector_2.12 added as a dependency
Then I run
CREATE TEMPORARY VIEW mongo
USING com.mongodb.spark.sql.DefaultSource
OPTIONS (
collection 'accounts'
);
And I get the following error:
java.lang.NoSuchMethodError: scala.Product.$init$(Lscala/Product;)V
at com.mongodb.spark.rdd.partitioner.DefaultMongoPartitioner$.<init>(DefaultMongoPartitioner.scala:64)
at com.mongodb.spark.rdd.partitioner.DefaultMongoPartitioner$.<clinit>(DefaultMongoPartitioner.scala)
at com.mongodb.spark.config.ReadConfig$.<init>(ReadConfig.scala:48)
at com.mongodb.spark.config.ReadConfig$.<clinit>(ReadConfig.scala)
at com.mongodb.spark.sql.DefaultSource.constructRelation(DefaultSource.scala:91)
at com.mongodb.spark.sql.DefaultSource.createRelation(DefaultSource.scala:50)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:318)
at org.apache.spark.sql.execution.datasources.CreateTempViewUsing.run(ddl.scala:93)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:79)
at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:194)
at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:194)
at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:84)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:165)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:74)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3369)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:194)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:79)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:643)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:694)
at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:62)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:371)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:376)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:274)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:853)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:161)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:184)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:928)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:937)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
java.lang.NoSuchMethodError: scala.Product.$init$(Lscala/Product;)V
at com.mongodb.spark.rdd.partitioner.DefaultMongoPartitioner$.<init>(DefaultMongoPartitioner.scala:64)
at com.mongodb.spark.rdd.partitioner.DefaultMongoPartitioner$.<clinit>(DefaultMongoPartitioner.scala)
at com.mongodb.spark.config.ReadConfig$.<init>(ReadConfig.scala:48)
at com.mongodb.spark.config.ReadConfig$.<clinit>(ReadConfig.scala)
at com.mongodb.spark.sql.DefaultSource.constructRelation(DefaultSource.scala:91)
at com.mongodb.spark.sql.DefaultSource.createRelation(DefaultSource.scala:50)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:318)
at org.apache.spark.sql.execution.datasources.CreateTempViewUsing.run(ddl.scala:93)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:79)
at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:194)
at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:194)
at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:84)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:165)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:74)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3369)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:194)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:79)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:643)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:694)
at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:62)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:371)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:376)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:274)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:853)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:161)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:184)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:928)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:937)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Any idea how to set up this view using SQL only, ideally without any startup command line options except the Maven coordinates would also be ace.
Looks like a mismatch between Scala versions.
Starting spark-sql with spark-sql --packages org.mongodb.spark:mongo-spark-connector_2.11:2.4.1 worked alright.
To create the Mongo view using SQL only:
CREATE TEMPORARY VIEW source
USING mongo
OPTIONS (
uri 'mongodb://…',
collection 'my_collection'
);
I am using the package IBMSparkGPU/GPUenabler package. I use sbt assembly to package all the dependency into one single jar file and submit it to the spark standalone cluster manager. However, the following error message appear:
org.apache.spark.SparkException: Error sending message [message = CacheGPUDS(a99176e95cf37ba4e5e46b9b172369ac_-1728716590,false)]
at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:119)
at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:78)
at com.ibm.gpuenabler.GPUMemoryManagerMasterEndPoint.com$ibm$gpuenabler$GPUMemoryManagerMasterEndPoint$$tell(GPUMemoryManager.scala:172)
at com.ibm.gpuenabler.GPUMemoryManagerMasterEndPoint$$anonfun$registerGPUMemoryManager$2.apply(GPUMemoryManager.scala:64)
at com.ibm.gpuenabler.GPUMemoryManagerMasterEndPoint$$anonfun$registerGPUMemoryManager$2.apply(GPUMemoryManager.scala:64)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
at scala.collection.mutable.ListBuffer.foreach(ListBuffer.scala:45)
at com.ibm.gpuenabler.GPUMemoryManagerMasterEndPoint.registerGPUMemoryManager(GPUMemoryManager.scala:64)
at com.ibm.gpuenabler.GPUMemoryManagerMasterEndPoint$$anonfun$receiveAndReply$1.applyOrElse(GPUMemoryManager.scala:143)
at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:105)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:205)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:101)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:213)
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)
Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult
at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:77)
at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:75)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
at scala.PartialFunction$OrElse.apply(PartialFunction.scala:167)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:83)
at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:102)
... 16 more
Caused by: java.lang.RuntimeException: java.lang.ClassNotFoundException: com.ibm.gpuenabler.CacheGPUDS
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67)
at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1866)
at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1749)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2040)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1571)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2285)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2209)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2067)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1571)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:431)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:108)
at org.apache.spark.rpc.netty.NettyRpcEnv$$anonfun$deserialize$1$$anonfun$apply$1.apply(NettyRpcEnv.scala:259)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.rpc.netty.NettyRpcEnv.deserialize(NettyRpcEnv.scala:308)
at org.apache.spark.rpc.netty.NettyRpcEnv$$anonfun$deserialize$1.apply(NettyRpcEnv.scala:258)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.rpc.netty.NettyRpcEnv.deserialize(NettyRpcEnv.scala:257)
at org.apache.spark.rpc.netty.NettyRpcHandler.internalReceive(NettyRpcEnv.scala:577)
at org.apache.spark.rpc.netty.NettyRpcHandler.receive(NettyRpcEnv.scala:562)
at org.apache.spark.network.server.TransportRequestHandler.processRpcRequest(TransportRequestHandler.java:159)
at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:107)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:119)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
... more
There won't be this error message and the program can run if I submit to local[*] as master. I can also eliminate the error when disable the spark.gpuenabler.autocache. However, is there other way to properly fix the issue?
I am using Ubuntu 17.04, JRE 1.8.0, Scala 2.11 and Spark 2.1.0.
It turned out that adding the option
--conf "spark.executor.extraClassPath=file://path/to/jar" will solve the problem. Another thing is that I need to paste the jar file to all the machine with same path. Other wise the worker will not be able to get the jar file.
I am facing an error when I try to query a table in hive when hive uses spark. For example, when I do:
select count(*) from ma_table;
I get this:
Exception in thread "main" java.lang.NoClassDefFoundError: scala/collection/Iterable
at org.apache.hadoop.hive.ql.parse.spark.GenSparkProcContext.<init>(GenSparkProcContext.java:163)
at org.apache.hadoop.hive.ql.parse.spark.SparkCompiler.generateTaskTree(SparkCompiler.java:195)
at org.apache.hadoop.hive.ql.parse.TaskCompiler.compile(TaskCompiler.java:267)
at org.apache.hadoop.hive.ql.parse.SemanticAnalyzer.analyzeInternal(SemanticAnalyzer.java:10947)
at org.apache.hadoop.hive.ql.parse.CalcitePlanner.analyzeInternal(CalcitePlanner.java:246)
at org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer.analyze(BaseSemanticAnalyzer.java:250)
at org.apache.hadoop.hive.ql.Driver.compile(Driver.java:477)
at org.apache.hadoop.hive.ql.Driver.compileInternal(Driver.java:1242)
at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1384)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1171)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1161)
at org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:232)
at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:183)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:399)
at org.apache.hadoop.hive.cli.CliDriver.executeDriver(CliDriver.java:776)
at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:714)
at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:641)
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.hadoop.util.RunJar.run(RunJar.java:234)
at org.apache.hadoop.util.RunJar.main(RunJar.java:148)
Caused by: java.lang.ClassNotFoundException: scala.collection.Iterable
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:335)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
... 23 more
After some research, I tried to had this to my bashrc (and sourced it ;) ) :
for f in ${HIVE_LIB}/*.jar; do
CLASSPATH=${CLASSPATH}:$f;
done
for f in ${SPARK_HOME}/jars/*.jar; do
CLASSPATH=${CLASSPATH}:$f;
done
for f in ${SCALA_HOME}/lib/*.jar; do
CLASSPATH=${CLASSPATH}:$f;
done
I checked and I have all these jars in the CLASSPATH and still get the error.
I am using Hive 2.1, Hadoop 2.8 and Spark 2.1.
Any ideas? Thanks a lot by advance!
After coming back to it, I found that scala jars files weren't in the lib of Hive.
If you are facing something similar, have a look there:
https://www.linkedin.com/pulse/hive-spark-configuration-common-issues-mohamed-k