SPARK_RPC_CLIENT_CONNECT_TIMEOUT in running Hive On Spark - YARN Cluster mode - apache-spark

I am using HDP2.3 and trying to use Spark(1.3.1) as the execution engine for running hive queries.
spark-assembly jar is also available in the hive/lib folder.
I am able to run the query in spark-master: local but facing the below issue when using spark-master: yarn-cluster.
command run,
hive -e "set hive.execution.engine=spark; set
spark.master=yarn-cluster; select count(*) from db_name.table_name;"
output,
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/hdp/2.3.0.0-2557/hadoop/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.3.0.0-2557/hive/lib/spark-assembly-1.3.1-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/root/downloads/machine/spark/lib/spark-assembly-1.3.1-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
WARNING: Use "yarn jar" to launch YARN applications.
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/hdp/2.3.0.0-2557/hadoop/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.3.0.0-2557/hive/lib/spark-assembly-1.3.1-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/root/downloads/machine/spark/lib/spark-assembly-1.3.1-hadoop2.6.0.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
Logging initialized using configuration in file:/etc/hive/2.3.0.0-2557/0/hive-log4j.properties
Query ID = root_20150909201120_a67d5ca3-36df-43fe-894a-3645585eec7a
Total jobs = 1
Launching Job 1 out of 1
In order to change the average load for a reducer (in bytes):
set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
set mapreduce.job.reduces=<number>
Failed to execute spark task, with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create spark client.)'
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.spark.SparkTask
yarn log of the application,
15/09/09 19:42:27 INFO yarn.ApplicationMaster: Waiting for spark context initialization ...
15/09/09 19:42:27 INFO client.RemoteDriver: Connecting to: sandbox.hortonworks.com:59941
15/09/09 19:42:27 ERROR yarn.ApplicationMaster: User class threw exception: SPARK_RPC_CLIENT_CONNECT_TIMEOUT
java.lang.NoSuchFieldError: SPARK_RPC_CLIENT_CONNECT_TIMEOUT
at org.apache.hive.spark.client.rpc.RpcConfiguration.<clinit>(RpcConfiguration.java:46)
at org.apache.hive.spark.client.RemoteDriver.<init>(RemoteDriver.java:146)
at org.apache.hive.spark.client.RemoteDriver.main(RemoteDriver.java:556)
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.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:480)
15/09/09 19:42:27 INFO yarn.ApplicationMaster: Final app status: FAILED, exitCode: 15, (reason: User class threw exception: SPARK_RPC_CLIENT_CONNECT_TIMEOUT)
15/09/09 19:42:37 ERROR yarn.ApplicationMaster: SparkContext did not initialize after waiting for 100000 ms. Please check earlier log output for errors. Failing the application.
15/09/09 19:42:37 INFO yarn.ApplicationMaster: Unregistering ApplicationMaster with FAILED (diag message: User class threw exception: SPARK_RPC_CLIENT_CONNECT_TIMEOUT)
15/09/09 19:42:37 INFO yarn.ApplicationMaster: Deleting staging directory .sparkStaging/application_1441817597849_0008
Any help on debugging the issue is much appreciated.

I don't think queries can be executed in yarn-cluster mode.
You can run interactive queries in local and yarn-client mode only

Related

Start PySpark in Jupyter notebook on EMR 6.5

I am trying to start a pyspark job using Amazon EMR Jupyter hub feature, as follow:
And with following code:
from pyspark import SparkSession
spark = SparkSession \
.builder \
.appName("My App") \
.getOrCreate()
But at the end, I always got:
The code failed because of a fatal error:
Session 0 unexpectedly reached final status 'dead'. See logs:
stdout:
stderr:
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/lib/spark/jars/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/share/aws/emr/emrfs/lib/slf4j-log4j12-1.7.12.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/share/aws/redshift/jdbc/redshift-jdbc42-1.2.37.1061.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.spark.unsafe.Platform (file:/usr/lib/spark/jars/spark-unsafe_2.12-3.1.2-amzn-1.jar) to constructor java.nio.DirectByteBuffer(long,int)
WARNING: Please consider reporting this to the maintainers of org.apache.spark.unsafe.Platform
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
22/05/04 13:21:11 INFO RSCDriver: Connecting to: ip-10-42-255-42.eu-west-1.compute.internal:10000
22/05/04 13:21:11 INFO RSCDriver: Starting RPC server...
22/05/04 13:21:11 INFO RpcServer: Connected to the port 10001
22/05/04 13:21:11 WARN RSCConf: Your hostname, ip-10-42-255-42.eu-west-1.compute.internal, resolves to a loopback address, but we couldn't find any external IP address!
22/05/04 13:21:11 WARN RSCConf: Set livy.rsc.rpc.server.address if you need to bind to another address.
Exception in thread "main" java.lang.IncompatibleClassChangeError: Inconsistent constant pool data in classfile for class org/apache/livy/shaded/json4s/DefaultFormats. Method 'java.text.SimpleDateFormat $anonfun$df$1(org.apache.livy.shaded.json4s.DefaultFormats)' at index 156 is CONSTANT_MethodRef and should be CONSTANT_InterfaceMethodRef
at org.apache.livy.shaded.json4s.DefaultFormats.$init$(Formats.scala:318)
at org.apache.livy.shaded.json4s.DefaultFormats$.<init>(Formats.scala:296)
at org.apache.livy.shaded.json4s.DefaultFormats$.<clinit>(Formats.scala)
at org.apache.livy.repl.Session.<init>(Session.scala:66)
at org.apache.livy.repl.ReplDriver.initializeSparkEntries(ReplDriver.scala:43)
at org.apache.livy.rsc.driver.RSCDriver.run(RSCDriver.java:337)
at org.apache.livy.rsc.driver.RSCDriverBootstrapper.main(RSCDriverBootstrapper.java:93)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:959)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1047)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1056)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
22/05/04 13:21:11 INFO ShutdownHookManager: Shutdown hook called
22/05/04 13:21:11 INFO ShutdownHookManager: Deleting directory /mnt/tmp/spark-2804f6ee-21f1-4773-98dc-8b3e3bd1924a
Seems the livy version is clahing with the livy version embedded with the apache shaded jar, so I tried to override the jar using a fat jar that contains all the spark jar I'm used to use, and use the following config to import it:
%%configure -f
{
"conf": {
"spark.jars": "s3://mybucket/myfatjar.jar"
}
}
But without any effect.

java.lang.ClassCastException: org.apache.hadoop.conf.Configuration cannot be cast to org.apache.hadoop.yarn.conf.YarnConfiguration

I am running a spark application using yarn in cloudera.
Spark version: 2.1
I get the following error:
SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found
binding in
[jar:file:/data/yarn/nm/filecache/13/jars/slf4j-log4j12-1.7.16.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in
[jar:file:/opt/cloudera/parcels/CDH-5.10.2-1.cdh5.10.2.p0.5/jars/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an
explanation. SLF4J: Actual binding is of type
[org.slf4j.impl.Log4jLoggerFactory] 18/04/14 22:20:57 INFO
util.SignalUtils: Registered signal handler for TERM 18/04/14 22:20:57
INFO util.SignalUtils: Registered signal handler for HUP 18/04/14
22:20:57 INFO util.SignalUtils: Registered signal handler for INT
Exception in thread "main" java.lang.ClassCastException:
org.apache.hadoop.conf.Configuration cannot be cast to
org.apache.hadoop.yarn.conf.YarnConfiguration at
org.apache.spark.deploy.yarn.ApplicationMaster.(ApplicationMaster.scala:60)
at
org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$main$1.apply$mcV$sp(ApplicationMaster.scala:764)
at
org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:67)
at
org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:66)
at java.security.AccessController.doPrivileged(Native Method) at
javax.security.auth.Subject.doAs(Subject.java:415) at
org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1656)
at
org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:66)
at
org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:763)
at
org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
I managed to solve it by verifyning that the spark version configured in SPARK_HOME variable matches the hadoop version installed in cloudera.
From the following link https://spark.apache.org/downloads.html you can download the suitable version for your required hadoop.
The haddop version in cloudera can by found by:
$ hadoop version
I encounter the same issue while trying to start a Spark job using Yarn Rest API.
And the reason was that the environment variable SPARK_YARN_MODE was missing. Adding this env var, everything works fine :
export SPARK_YARN_MODE=true

SAP HANA VORA - Spark Controller issue

I am trying to install start the SAP HANA Spark Controller on VORA 1.2 using Ambari.
However, when I am starting my Spark controller, I am getting the below exception.
Kindly help here...
[hanaes#ip-172-30-2-218 bin]$ ./hanaes start
Starting HANA Spark Controller ...
Class path is /usr/sap/spark/controller/bin/../conf:/usr/hdp/2.3.4.7-4/hadoop/conf:/etc/hive/conf:../*:../lib/*:../lib/external/*:/usr/hdp/2.3.4.7-4/hadoop/*:/usr/hdp/2.3.4.7-4/hadoop/lib/*:/usr/hdp/2.3.4.7-4/hadoop-hdfs/*:/usr/hdp/2.3.4.7-4/hadoop-hdfs/lib/*
STARTED
[hanaes#ip-172-30-2-218 bin]$ clear
[hanaes#ip-172-30-2-218 bin]$ tail -1000f /var/log/hanaes/hana_controller.log
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/sap/spark/controller/lib/external/spark-assembly-1.5.2.2.3.4.7-4-hadoop2.7.1.2.3.4.7-4.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.3.4.7-4/hadoop/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
16/05/09 12:04:43 INFO HanaESConfig: Loaded HANA Extended Store Configuration Found Spark Libraries. Proceeding with Current Class Path
16/05/09 12:04:44 INFO Server: Starting Spark Controller
16/05/09 12:04:52 ERROR SparkContext: Error initializing SparkContext. org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:125)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:65)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:144)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:523)
at com.sap.hana.spark.network.CommandRouter.initializeHanaContext(CommandRouter.scala:125)
at com.sap.hana.spark.network.CommandRouter.<init>(CommandRouter.scala:38)
at com.sap.hana.spark.network.Server$$anonfun$1.apply(Server.scala:96)
at com.sap.hana.spark.network.Server$$anonfun$1.apply(Server.scala:96)
at akka.actor.TypedCreatorFunctionConsumer.produce(Props.scala:343)
at akka.actor.Props.newActor(Props.scala:252)
at akka.actor.ActorCell.newActor(ActorCell.scala:552)
at akka.actor.ActorCell.create(ActorCell.scala:578)
at akka.actor.ActorCell.invokeAll$1(ActorCell.scala:456)
at akka.actor.ActorCell.systemInvoke(ActorCell.scala:478)
at akka.dispatch.Mailbox.processAllSystemMessages(Mailbox.scala:263)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) 16/05/09 12:04:52 ERROR Utils: Uncaught exception in thread SAPHanaSpark-akka.actor.default-dispatcher-2 java.lang.NullPointerException
at org.apache.spark.network.netty.NettyBlockTransferService.close(NettyBlockTransferService.scala:152)
at org.apache.spark.storage.BlockManager.stop(BlockManager.scala:1228)
at org.apache.spark.SparkEnv.stop(SparkEnv.scala:100)
at org.apache.spark.SparkContext$$anonfun$stop$12.apply$mcV$sp(SparkContext.scala:1749)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1185)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1748)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:593)
at com.sap.hana.spark.network.CommandRouter.initializeHanaContext(CommandRouter.scala:125)
at com.sap.hana.spark.network.CommandRouter.<init>(CommandRouter.scala:38)
at com.sap.hana.spark.network.Server$$anonfun$1.apply(Server.scala:96)
at com.sap.hana.spark.network.Server$$anonfun$1.apply(Server.scala:96)
at akka.actor.TypedCreatorFunctionConsumer.produce(Props.scala:343)
at akka.actor.Props.newActor(Props.scala:252)
at akka.actor.ActorCell.newActor(ActorCell.scala:552)
at akka.actor.ActorCell.create(ActorCell.scala:578)
at akka.actor.ActorCell.invokeAll$1(ActorCell.scala:456)
at akka.actor.ActorCell.systemInvoke(ActorCell.scala:478)
at akka.dispatch.Mailbox.processAllSystemMessages(Mailbox.scala:263)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
The spark controller log indicates issue with Yarn, you need to check Yarn log that is responsible for the failed spark controller job:
Ambari -> Yarn -> Quick Links -> Resource Manager UI -> find the failed Spark Controller job -> click on application ID on left -> click on ‘logs'

Logging in pyspark

I am trying to create a log file while using pyspark, but I am getting the following error message:
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
I have added the jar files in my class-path, but I still get this error. Anyway I can sort this out. I even tried to pass the jar file as arguments in driver-class-path, but still I get the same error.

Step by step running apache Nutch 2.2.1

I have config plugin.folders in nutch-default.xml but when I run Nutch via Eclipse & Netbeans,
Main class: org.apache.nutch.crawl.InjectorJob
Arguments: /MY_DATA_SOURCE/HR_PROJECTS/JSearch/Apache_Nutch/RELEASE/release-2.2.1/urls
VM Options: -Dhadoop.log.dir=logs -Dhadoop.log.file=hadoop.log
THe errors like below:
cd /MY_DATA_SOURCE/HR_PROJECTS/JSearch/Apache_Nutch/RELEASE/release-2.2.1; JAVA_HOME=/Library/Java/JavaVirtualMachines/jdk1.7.0_25.jdk/Contents/Home "/Applications/NetBeans/NetBeans 7.3.app/Contents/Resources/NetBeans/java/maven/bin/mvn" "-Dexec.args=-Dhadoop.log.dir=logs -Dhadoop.log.file=hadoop.log -classpath %classpath org.apache.nutch.crawl.InjectorJob /MY_DATA_SOURCE/HR_PROJECTS/JSearch/Apache_Nutch/RELEASE/release-2.2.1/urls" -Dexec.executable=/Library/Java/JavaVirtualMachines/jdk1.7.0_25.jdk/Contents/Home/bin/java process-classes org.codehaus.mojo:exec-maven-plugin:1.2.1:exec
Scanning for projects...
------------------------------------------------------------------------
Building Apache Nutch 2.2.1
------------------------------------------------------------------------
[resources:resources]
[debug] execute contextualize
Using platform encoding (US-ASCII actually) to copy filtered resources, i.e. build is platform dependent!
skip non existing resourceDirectory /MY_DATA_SOURCE/HR_PROJECTS/JSearch/Apache_Nutch/RELEASE/release-2.2.1/src/main/resources
[compiler:compile]
Nothing to compile - all classes are up to date
[exec:exec]
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/Users/hung/.m2/repository/org/slf4j/slf4j-log4j12/1.6.1/slf4j-log4j12-1.6.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Users/hung/.m2/repository/org/slf4j/slf4j-jdk14/1.6.1/slf4j-jdk14-1.6.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Users/hung/.m2/repository/org/slf4j/slf4j-simple/1.6.1/slf4j-simple-1.6.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
13/07/06 08:55:18 INFO crawl.InjectorJob: InjectorJob: starting at 2013-07-06 08:55:18
13/07/06 08:55:18 INFO crawl.InjectorJob: InjectorJob: Injecting urlDir: /MY_DATA_SOURCE/HR_PROJECTS/JSearch/Apache_Nutch/RELEASE/release-2.2.1/urls
2013-07-06 08:55:18.420 java[1206:1c03] Unable to load realm info from SCDynamicStore
13/07/06 08:55:18 WARN store.DataStoreFactory: gora.properties not found, properties will be empty.
13/07/06 08:55:18 WARN store.DataStoreFactory: gora.properties not found, properties will be empty.
13/07/06 08:55:19 INFO crawl.InjectorJob: InjectorJob: Using class org.apache.gora.sql.store.SqlStore as the Gora storage class.
13/07/06 08:55:19 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
13/07/06 08:55:19 WARN mapred.JobClient: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
13/07/06 08:55:19 INFO input.FileInputFormat: Total input paths to process : 1
13/07/06 08:55:19 WARN snappy.LoadSnappy: Snappy native library not loaded
13/07/06 08:55:19 INFO mapred.JobClient: Running job: job_local226390157_0001
13/07/06 08:55:19 INFO mapred.LocalJobRunner: Waiting for map tasks
13/07/06 08:55:19 INFO mapred.LocalJobRunner: Starting task: attempt_local226390157_0001_m_000000_0
13/07/06 08:55:19 INFO mapred.Task: Using ResourceCalculatorPlugin : null
13/07/06 08:55:19 INFO mapred.MapTask: Processing split: file:/MY_DATA_SOURCE/HR_PROJECTS/JSearch/Apache_Nutch/RELEASE/release-2.2.1/urls/seed.txt:0+20
13/07/06 08:55:19 WARN store.DataStoreFactory: gora.properties not found, properties will be empty.
13/07/06 08:55:19 INFO mapreduce.GoraRecordWriter: gora.buffer.write.limit = 10000
13/07/06 08:55:19 INFO mapred.LocalJobRunner: Map task executor complete.
13/07/06 08:55:19 WARN mapred.FileOutputCommitter: Output path is null in cleanup
13/07/06 08:55:19 WARN mapred.LocalJobRunner: job_local226390157_0001
java.lang.Exception: java.lang.IllegalArgumentException: plugin.folders is not defined
at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:354)
Caused by: java.lang.IllegalArgumentException: plugin.folders is not defined
at org.apache.nutch.plugin.PluginManifestParser.parsePluginFolder(PluginManifestParser.java:78)
at org.apache.nutch.plugin.PluginRepository.<init>(PluginRepository.java:69)
at org.apache.nutch.plugin.PluginRepository.get(PluginRepository.java:97)
at org.apache.nutch.net.URLNormalizers.<init>(URLNormalizers.java:117)
at org.apache.nutch.crawl.InjectorJob$UrlMapper.setup(InjectorJob.java:99)
at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:142)
at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:764)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:364)
at org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:223)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:334)
at java.util.concurrent.FutureTask.run(FutureTask.java:166)
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:724)
13/07/06 08:55:20 INFO mapred.JobClient: map 0% reduce 0%
13/07/06 08:55:20 INFO mapred.JobClient: Job complete: job_local226390157_0001
13/07/06 08:55:20 INFO mapred.JobClient: Counters: 0
13/07/06 08:55:20 ERROR crawl.InjectorJob: InjectorJob: java.lang.RuntimeException: job failed: name=inject /MY_DATA_SOURCE/HR_PROJECTS/JSearch/Apache_Nutch/RELEASE/release-2.2.1/urls, jobid=job_local226390157_0001
at org.apache.nutch.util.NutchJob.waitForCompletion(NutchJob.java:54)
at org.apache.nutch.crawl.InjectorJob.run(InjectorJob.java:233)
at org.apache.nutch.crawl.InjectorJob.inject(InjectorJob.java:251)
at org.apache.nutch.crawl.InjectorJob.run(InjectorJob.java:273)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
at org.apache.nutch.crawl.InjectorJob.main(InjectorJob.java:282)
------------------------------------------------------------------------
BUILD FAILURE
------------------------------------------------------------------------
Total time: 6.572s
Finished at: Sat Jul 06 08:55:20 ICT 2013
Final Memory: 11M/236M
------------------------------------------------------------------------
Failed to execute goal org.codehaus.mojo:exec-maven-plugin:1.2.1:exec (default-cli) on project nutch: Command execution failed. Process exited with an error: 255 (Exit value: 255) -> [Help 1]
To see the full stack trace of the errors, re-run Maven with the -e switch.
Re-run Maven using the -X switch to enable full debug logging.
For more information about the errors and possible solutions, please read the following articles:
[Help 1] http://cwiki.apache.org/confluence/display/MAVEN/MojoExecutionException
The error message clearly indicates the problem (and where to look for a solution):
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/Users/hung/.m2/repository/org/slf4j/slf4j-log4j12/1.6.1/slf4j-log4j12-1.6.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Users/hung/.m2/repository/org/slf4j/slf4j-jdk14/1.6.1/slf4j-jdk14-1.6.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Users/hung/.m2/repository/org/slf4j/slf4j-simple/1.6.1/slf4j-simple-1.6.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.

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