http://apache-carbondata-dev-mailing-list-archive.168.s1.nabble.com/Exception-throws-when-I-load-data-using-carbondata-1-0-0-tp7553p7772.html
Here storeLocation is hdfs://hacluster/tmp/carbondata/carbon.store in your case.
> Hi,
>
> How did you create CarbonContext?
> Can you check whether you have provided same store path in
> carbon.properties and the CarbonContext.
>
> Regards,
> Ravindra.
>
> On 20 February 2017 at 12:26, Xiaoqiao He <
[hidden email]> wrote:
>
>> Hi Ravindra,
>>
>> Thanks for your suggestions. But another problem met when I create table
>> and load data.
>>
>> 1. I follow README to compile and build CarbonData actually, via
>>
https://github.com/apache/incubator-carbondata/blob/master/>> build/README.md :
>>
>> > mvn -DskipTests -Pspark-1.6 -Dspark.version=1.6.2 clean package
>>
>>
>> 2. I think the exceptions mentioned above (ClassNotFoundException/'exists
>> and does not match'), is related to configuration item of
>> 'spark.executor.extraClassPath'. Since when i trace executor logs, i
>> found
>> it tries to load Class from the same path as spark.executor.extraClassPath
>> config and it can not found local (this local path is valid only for
>> driver), and throw exception. When I remove this item in configuration and
>> run the same command with --jar parameter, then not throw this exception
>> again.
>>
>> 3. but when i create table following quick-start as below:
>>
>> > scala> cc.sql("CREATE TABLE IF NOT EXISTS sample (id string, name
>> string,
>> > city string, age Int) STORED BY 'carbondata'")
>>
>>
>> there is some info logs such as:
>>
>> > INFO 20-02 12:00:35,690 - main Query [CREATE TABLE TEST.SAMPLE USING
>> > CARBONDATA OPTIONS (TABLENAME "TEST.SAMPLE", TABLEPATH
>> > "/HOME/PATH/HEXIAOQIAO/CARBON.STORE/TEST/SAMPLE") ]
>>
>> and* TABLEPATH looks not the proper path (I have no idea why this path is
>> not HDFS path)*, and then load data as blow but another exception throws.
>>
>> > scala> cc.sql("LOAD DATA INPATH
>> > 'hdfs://hacluster/user/hadoop-data/sample.csv' INTO TABLE sample")
>>
>>
>> there is some info logs such as:
>>
>> > INFO 20-02 12:01:27,608 - main HDFS lock
>> > path:hdfs://hacluster/home/path/hexiaoqiao/carbon.store/test
>> /sample/meta.lock
>>
>> *this lock path is not the expected hdfs path, it looks [hdfs
>> scheme://authority] + local setup path of carbondata. (is storelocation
>> not
>> active?)*
>> and throw exception:
>>
>> > INFO 20-02 12:01:42,668 - Table MetaData Unlocked Successfully after
>> data
>> > load
>> > java.lang.RuntimeException: Table is locked for updation. Please try
>> after
>> > some time
>> > at scala.sys.package$.error(package.scala:27)
>> > at
>> > org.apache.spark.sql.execution.command.LoadTable.run(
>> carbonTableSchema.scala:360)
>> > at
>> > org.apache.spark.sql.execution.ExecutedCommand.sideEffectRes
>> ult$lzycompute(commands.scala:58)
>> > at
>> > org.apache.spark.sql.execution.ExecutedCommand.sideEffectRes
>> ult(commands.scala:56)
>> > at
>> > org.apache.spark.sql.execution.ExecutedCommand.doExecute(
>> commands.scala:70)
>>
>> ......
>>
>>
>> CarbonData Configuration:
>> carbon.storelocation=hdfs://hacluster/tmp/carbondata/carbon.store
>> carbon.lock.type=HDFSLOCK
>> FYI.
>>
>> Regards,
>> Hexiaoqiao
>>
>>
>> On Sat, Feb 18, 2017 at 3:26 PM, Ravindra Pesala <
[hidden email]>
>> wrote:
>>
>> > Hi Xiaoqiao,
>> >
>> > Is the problem still exists?
>> > Can you try with clean build with "mvn clean -DskipTests -Pspark-1.6
>> > package" command.
>> >
>> > Regards,
>> > Ravindra.
>> >
>> > On 16 February 2017 at 08:36, Xiaoqiao He <
[hidden email]> wrote:
>> >
>> > > hi Liang Chen,
>> > >
>> > > Thank for your help. It is true that i install and configure
>> carbondata
>> > on
>> > > "spark on yarn" cluster following installation guide (
>> > >
https://github.com/apache/incubator-carbondata/blob/>> > > master/docs/installation-guide.md#installing-and-
>> > > configuring-carbondata-on-spark-on-yarn-cluster
>> > > ).
>> > >
>> > > Best Regards,
>> > > Heixaoqiao
>> > >
>> > >
>> > > On Thu, Feb 16, 2017 at 7:47 AM, Liang Chen <
[hidden email]>
>> > > wrote:
>> > >
>> > > > Hi He xiaoqiao
>> > > >
>> > > > Quick start is local model spark.
>> > > > Your case is yarn cluster , please check :
>> > > >
https://github.com/apache/incubator-carbondata/blob/>> > > > master/docs/installation-guide.md
>> > > >
>> > > > Regards
>> > > > Liang
>> > > >
>> > > > 2017-02-15 3:29 GMT-08:00 Xiaoqiao He <
[hidden email]>:
>> > > >
>> > > > > hi Manish Gupta,
>> > > > >
>> > > > > Thanks for you focus, actually i try to load data following
>> > > > >
https://github.com/apache/incubator-carbondata/blob/>> > > > > master/docs/quick-start-guide.md
>> > > > > for deploying carbondata-1.0.0.
>> > > > >
>> > > > > 1.when i execute carbondata by `bin/spark-shell`, it throws as
>> above.
>> > > > > 2.when i execute carbondata by `bin/spark-shell --jars
>> > > > > carbonlib/carbondata_2.10-1.0.0-incubating-shade-hadoop2.7.1
>> .jar`,
>> > it
>> > > > > throws another exception as below:
>> > > > >
>> > > > > org.apache.spark.SparkException: Job aborted due to stage
>> failure:
>> > > Task
>> > > > 0
>> > > > > > in stage 0.0 failed 4 times, most recent failure: Lost task 0.3
>> in
>> > > > stage
>> > > > > > 0.0 (TID 3, [task hostname]): org.apache.spark.SparkException:
>> > File
>> > > > > > ./carbondata_2.10-1.0.0-incubating-shade-hadoop2.7.1.jar exists
>> > and
>> > > > does
>> > > > > > not match contents of
>> > > > > >
http://master:50843/jars/carbondata_2.10-1.0.0->> > > > > incubating-shade-hadoop2.7.1.jar
>> > > > >
>> > > > >
>> > > > > I check the assembly jar and CarbonBlockDistinctValuesCombineRDD
>> is
>> > > > > present
>> > > > > actually.
>> > > > >
>> > > > > anyone who meet the same problem?
>> > > > >
>> > > > > Best Regards,
>> > > > > Hexiaoqiao
>> > > > >
>> > > > >
>> > > > > On Wed, Feb 15, 2017 at 12:56 AM, manish gupta <
>> > > >
[hidden email]>
>> > > > > wrote:
>> > > > >
>> > > > > > Hi,
>> > > > > >
>> > > > > > I think the carbon jar is compiled properly. Can you use any
>> > > decompiler
>> > > > > and
>> > > > > > decompile carbondata-spark-common-1.1.0-incubating-SNAPSHOT.jar
>> > > > present
>> > > > > in
>> > > > > > spark-common module target folder and check whether the required
>> > > class
>> > > > > file
>> > > > > > org.apache.carbondata.spark.rdd.CarbonBlockDistinctValuesCombi
>> > neRDD
>> > > is
>> > > > > > present or not.
>> > > > > >
>> > > > > > If you are using only the assembly jar then decompile and check
>> in
>> > > > > assembly
>> > > > > > jar.
>> > > > > >
>> > > > > > Regards
>> > > > > > Manish Gupta
>> > > > > >
>> > > > > > On Tue, Feb 14, 2017 at 11:19 AM, Xiaoqiao He <
>>
[hidden email]
>> > >
>> > > > > wrote:
>> > > > > >
>> > > > > > > hi, dev,
>> > > > > > >
>> > > > > > > The latest release version apache-carbondata-1.0.0-
>> > incubating-rc2
>> > > > > which
>> > > > > > > takes Spark-1.6.2 to build throws exception `
>> > > > > > > java.lang.ClassNotFoundException:
>> > > > > > > org.apache.carbondata.spark.rdd.CarbonBlockDistinctValuesCom
>> bi
>> > > neRDD`
>> > > > > > when
>> > > > > > > i
>> > > > > > > load data following Quick Start Guide.
>> > > > > > >
>> > > > > > > Env:
>> > > > > > > a. CarbonData-1.0.0-incubating-rc2
>> > > > > > > b. Spark-1.6.2
>> > > > > > > c. Hadoop-2.7.1
>> > > > > > > d. CarbonData on "Spark on YARN" Cluster and run yarn-client
>> > mode.
>> > > > > > >
>> > > > > > > any suggestions? Thank you.
>> > > > > > >
>> > > > > > > The exception stack trace as below:
>> > > > > > >
>> > > > > > > --------
>> > > > > > > ERROR 14-02 12:21:02,005 - main generate global dictionary
>> failed
>> > > > > > > org.apache.spark.SparkException: Job aborted due to stage
>> > failure:
>> > > > > Task
>> > > > > > 0
>> > > > > > > in stage 0.0 failed 4 times, most recent failure: Lost task
>> 0.3
>> > in
>> > > > > stage
>> > > > > > > 0.0 (TID 3, nodemanger): java.lang.ClassNotFoundException:
>> > > > > > > org.apache.carbondata.spark.rdd.CarbonBlockDistinctValuesCom
>> bi
>> > > neRDD
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.ExecutorClassLoader.findClass(
>> > > > > > > ExecutorClassLoader.scala:84)
>> > > > > > >
>> > > > > > > at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
>> > > > > > > at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
>> > > > > > > at java.lang.Class.forName0(Native Method)
>> > > > > > > at java.lang.Class.forName(Class.java:274)
>> > > > > > > at
>> > > > > > > org.apache.spark.serializer.JavaDeserializationStream$$
>> > > > > > > anon$1.resolveClass(JavaSerializer.scala:68)
>> > > > > > >
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readNonProxyDesc(
>> > > > > ObjectInputStream.java:1612)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readClassDesc(
>> > > ObjectInputStream.java:1517)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readOrdinaryObject(
>> > > > > > ObjectInputStream.java:1771)
>> > > > > > > at java.io.ObjectInputStream.read
>> Object0(ObjectInputStream.
>> > > > > > java:1350)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.defaultReadFields(
>> > > > > ObjectInputStream.java:1990)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readSerialData(
>> > > > ObjectInputStream.java:1915)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readOrdinaryObject(
>> > > > > > ObjectInputStream.java:1798)
>> > > > > > > at java.io.ObjectInputStream.read
>> Object0(ObjectInputStream.
>> > > > > > java:1350)
>> > > > > > > at java.io.ObjectInputStream.read
>> Object(ObjectInputStream.
>> > > > > java:370)
>> > > > > > > at
>> > > > > > > org.apache.spark.serializer.JavaDeserializationStream.
>> > > > > > > readObject(JavaSerializer.scala:76)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.serializer.JavaSerializerInstance.
>> > > > > > > deserialize(JavaSerializer.scala:115)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.ShuffleMapTask.runTask(
>> > > > > > ShuffleMapTask.scala:64)
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.ShuffleMapTask.runTask(
>> > > > > > ShuffleMapTask.scala:41)
>> > > > > > > at org.apache.spark.scheduler.Task.run(Task.scala:89)
>> > > > > > > at
>> > > > > > > org.apache.spark.executor.Executor$TaskRunner.run(
>> > > > Executor.scala:227)
>> > > > > > > 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:745)
>> > > > > > >
>> > > > > > > Driver stacktrace:
>> > > > > > > at org.apache.spark.scheduler.DAGScheduler.org
>> > $apache$spark$
>> > > > > > > scheduler$DAGScheduler$$failJobAndIndependentStages(
>> > > > > > > DAGScheduler.scala:1431)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGScheduler$$anonfun$
>> > > abortStage$1.apply(
>> > > > > > > DAGScheduler.scala:1419)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGScheduler$$anonfun$
>> > > abortStage$1.apply(
>> > > > > > > DAGScheduler.scala:1418)
>> > > > > > >
>> > > > > > > at
>> > > > > > > scala.collection.mutable.ResizableArray$class.foreach(
>> > > > > > > ResizableArray.scala:59)
>> > > > > > >
>> > > > > > > at scala.collection.mutable.ArrayBuffer.foreach(
>> > > > > > ArrayBuffer.scala:47)
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGScheduler.abortStage(
>> > > > > > > DAGScheduler.scala:1418)
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGScheduler$$anonfun$
>> > > > > > > handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGScheduler$$anonfun$
>> > > > > > > handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
>> > > > > > >
>> > > > > > > at scala.Option.foreach(Option.scala:236)
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(
>> > > > > > > DAGScheduler.scala:799)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
>> > > > > > > doOnReceive(DAGScheduler.scala:1640)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
>> > > > > > > onReceive(DAGScheduler.scala:1599)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.
>> > > > > > > onReceive(DAGScheduler.scala:1588)
>> > > > > > >
>> > > > > > > at org.apache.spark.util.EventLoop$$anon$1.run(
>> > > > > EventLoop.scala:48)
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.DAGScheduler.runJob(
>> > > > DAGScheduler.scala:620)
>> > > > > > > at org.apache.spark.SparkContext.
>> runJob(SparkContext.scala:
>> > > > 1832)
>> > > > > > > at org.apache.spark.SparkContext.
>> runJob(SparkContext.scala:
>> > > > 1845)
>> > > > > > > at org.apache.spark.SparkContext.
>> runJob(SparkContext.scala:
>> > > > 1858)
>> > > > > > > at org.apache.spark.SparkContext.
>> runJob(SparkContext.scala:
>> > > > 1929)
>> > > > > > > at org.apache.spark.rdd.RDD$$anon
>> fun$collect$1.apply(RDD.
>> > > > > scala:927)
>> > > > > > > at
>> > > > > > > org.apache.spark.rdd.RDDOperationScope$.withScope(
>> > > > > > > RDDOperationScope.scala:150)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.rdd.RDDOperationScope$.withScope(
>> > > > > > > RDDOperationScope.scala:111)
>> > > > > > >
>> > > > > > > at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
>> > > > > > > at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
>> > > > > > > at
>> > > > > > > org.apache.carbondata.spark.util.GlobalDictionaryUtil$.
>> > > > > > > generateGlobalDictionary(GlobalDictionaryUtil.scala:742)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.command.LoadTable.
>> > > > > > > run(carbonTableSchema.scala:577)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.ExecutedCommand.
>> > > > > > > sideEffectResult$lzycompute(commands.scala:58)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.ExecutedCommand.
>> > > > > > sideEffectResult(commands.
>> > > > > > > scala:56)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.ExecutedCommand.
>> > > > > > > doExecute(commands.scala:70)
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.SparkPlan$$anonfun$
>> > > > > > > execute$5.apply(SparkPlan.scala:132)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.SparkPlan$$anonfun$
>> > > > > > > execute$5.apply(SparkPlan.scala:130)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.rdd.RDDOperationScope$.withScope(
>> > > > > > > RDDOperationScope.scala:150)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.SparkPlan.execute(
>> > > > SparkPlan.scala:130)
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.QueryExecution.toRdd$
>> lzycompute(
>> > > > > > > QueryExecution.scala:55)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.sql.execution.QueryExecution.
>> > > > > > > toRdd(QueryExecution.scala:55)
>> > > > > > >
>> > > > > > > at org.apache.spark.sql.DataFrame.<init>(DataFrame.
>> > scala:145)
>> > > > > > > at org.apache.spark.sql.DataFrame.<init>(DataFrame.
>> > scala:130)
>> > > > > > > at org.apache.spark.sql.CarbonContext.sql(
>> > > > > CarbonContext.scala:139)
>> > > > > > > at
>> > > > > > > $line22.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<
>> > > > > > > init>(<console>:33)
>> > > > > > >
>> > > > > > > at
>> > > > > > > $line22.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>
>> > > > > > (<console>:38)
>> > > > > > > at
>> > > > > > > $line22.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<
>> > > > console>:40)
>> > > > > > > at $line22.$read$$iwC$$iwC$$iwC$$
>> > > iwC$$iwC$$iwC.<init>(<console>
>> > > > > :42)
>> > > > > > > at $line22.$read$$iwC$$iwC$$iwC$$
>> > > iwC$$iwC.<init>(<console>:44)
>> > > > > > > at $line22.$read$$iwC$$iwC$$iwC$$
>> iwC.<init>(<console>:46)
>> > > > > > > at $line22.$read$$iwC$$iwC$$iwC.<init>(<console>:48)
>> > > > > > > at $line22.$read$$iwC$$iwC.<init>(<console>:50)
>> > > > > > > at $line22.$read$$iwC.<init>(<console>:52)
>> > > > > > > at $line22.$read.<init>(<console>:54)
>> > > > > > > at $line22.$read$.<init>(<console>:58)
>> > > > > > > at $line22.$read$.<clinit>(<console>)
>> > > > > > > at $line22.$eval$.<init>(<console>:7)
>> > > > > > > at $line22.$eval$.<clinit>(<console>)
>> > > > > > > at $line22.$eval.$print(<console>)
>> > > > > > > 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.repl.SparkIMain$ReadEvalPrint.call(
>> > > > > > SparkIMain.scala:1065)
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.SparkIMain$Request.loadAndRun(
>> > > > > > SparkIMain.scala:1346)
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.SparkIMain.loadAndRunReq$1(
>> > > > SparkIMain.scala:840)
>> > > > > > > at org.apache.spark.repl.SparkIMain.interpret(
>> > > > > SparkIMain.scala:871)
>> > > > > > > at org.apache.spark.repl.SparkIMain.interpret(
>> > > > > SparkIMain.scala:819)
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.SparkILoop.reallyInterpret$1(
>> > > > > SparkILoop.scala:857)
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.SparkILoop.interpretStartingWith(
>> > > > > > > SparkILoop.scala:902)
>> > > > > > >
>> > > > > > > at org.apache.spark.repl.SparkILoop.command(SparkILoop.
>> > > > scala:814)
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.SparkILoop.processLine$1(
>> > > SparkILoop.scala:657)
>> > > > > > > at org.apache.spark.repl.SparkILoop.innerLoop$1(
>> > > > > > SparkILoop.scala:665)
>> > > > > > > at org.apache.spark.repl.SparkILoop.org$apache$spark$
>> > > > > > > repl$SparkILoop$$loop(SparkILoop.scala:670)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.SparkILoop$$anonfun$org$
>> > > > > > > apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(
>> > > > > > SparkILoop.scala:997)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.SparkILoop$$anonfun$org$
>> > > > > > > apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.
>> > > scala:945)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.SparkILoop$$anonfun$org$
>> > > > > > > apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.
>> > > scala:945)
>> > > > > > >
>> > > > > > > at
>> > > > > > > scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(
>> > > > > > > ScalaClassLoader.scala:135)
>> > > > > > >
>> > > > > > > at org.apache.spark.repl.SparkILoop.org$apache$spark$
>> > > > > > > repl$SparkILoop$$process(SparkILoop.scala:945)
>> > > > > > >
>> > > > > > > at org.apache.spark.repl.SparkILoop.process(SparkILoop.
>> > > > > scala:1059)
>> > > > > > > at org.apache.spark.repl.Main$.main(Main.scala:31)
>> > > > > > > at org.apache.spark.repl.Main.main(Main.scala)
>> > > > > > > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native
>> > > Method)
>> > > > > > > at
>> > > > > > > sun.reflect.NativeMethodAccessorImpl.invoke(
>> > > > > > NativeMethodAccessorImpl.java:
>> > > > > > > 57)
>> > > > > > >
>> > > > > > > at
>> > > > > > > sun.reflect.DelegatingMethodAccessorImpl.invoke(
>> > > > > > > DelegatingMethodAccessorImpl.java:43)
>> > > > > > >
>> > > > > > > at java.lang.reflect.Method.invoke(Method.java:606)
>> > > > > > > at
>> > > > > > > org.apache.spark.deploy.SparkSubmit$.org$apache$spark$
>> > > > > > > deploy$SparkSubmit$$runMain(SparkSubmit.scala:735)
>> > > > > > >
>> > > > > > > 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.SparkS
>> ubmit$.main(SparkSubmit.
>> > > > > scala:121)
>> > > > > > > at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.
>> > > scala)
>> > > > > > > Caused by: java.lang.ClassNotFoundException:
>> > > > > > > org.apache.carbondata.spark.rdd.CarbonBlockDistinctValuesCom
>> bi
>> > > neRDD
>> > > > > > > at
>> > > > > > > org.apache.spark.repl.ExecutorClassLoader.findClass(
>> > > > > > > ExecutorClassLoader.scala:84)
>> > > > > > >
>> > > > > > > at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
>> > > > > > > at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
>> > > > > > > at java.lang.Class.forName0(Native Method)
>> > > > > > > at java.lang.Class.forName(Class.java:274)
>> > > > > > > at
>> > > > > > > org.apache.spark.serializer.JavaDeserializationStream$$
>> > > > > > > anon$1.resolveClass(JavaSerializer.scala:68)
>> > > > > > >
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readNonProxyDesc(
>> > > > > ObjectInputStream.java:1612)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readClassDesc(
>> > > ObjectInputStream.java:1517)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readOrdinaryObject(
>> > > > > > ObjectInputStream.java:1771)
>> > > > > > > at java.io.ObjectInputStream.read
>> Object0(ObjectInputStream.
>> > > > > > java:1350)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.defaultReadFields(
>> > > > > ObjectInputStream.java:1990)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readSerialData(
>> > > > ObjectInputStream.java:1915)
>> > > > > > > at
>> > > > > > > java.io.ObjectInputStream.readOrdinaryObject(
>> > > > > > ObjectInputStream.java:1798)
>> > > > > > > at java.io.ObjectInputStream.read
>> Object0(ObjectInputStream.
>> > > > > > java:1350)
>> > > > > > > at java.io.ObjectInputStream.read
>> Object(ObjectInputStream.
>> > > > > java:370)
>> > > > > > > at
>> > > > > > > org.apache.spark.serializer.JavaDeserializationStream.
>> > > > > > > readObject(JavaSerializer.scala:76)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.serializer.JavaSerializerInstance.
>> > > > > > > deserialize(JavaSerializer.scala:115)
>> > > > > > >
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.ShuffleMapTask.runTask(
>> > > > > > ShuffleMapTask.scala:64)
>> > > > > > > at
>> > > > > > > org.apache.spark.scheduler.ShuffleMapTask.runTask(
>> > > > > > ShuffleMapTask.scala:41)
>> > > > > > > at org.apache.spark.scheduler.Task.run(Task.scala:89)
>> > > > > > > at
>> > > > > > > org.apache.spark.executor.Executor$TaskRunner.run(
>> > > > Executor.scala:227)
>> > > > > > > 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:745)
>> > > > > > >
>> > > > > >
>> > > > >
>> > > >
>> > > >
>> > > >
>> > > > --
>> > > > Regards
>> > > > Liang
>> > > >
>> > >
>> >
>> >
>> >
>> > --
>> > Thanks & Regards,
>> > Ravi
>> >
>>
>
>
>
> --
> Thanks & Regards,
> Ravi
>