yes you're right jeff. i'm sorry that's my mistake.
i've checked the application log but there is no helpful information
from that. only classpath and something like this:
"Stage Infos":[{"Stage ID":0,"Stage Attempt ID":0,"Stage Name":"groupBy
at pack.java:186","Number of Tasks":2,"RDD Info":[{"RDD
ID":2,"Name":"2","Storage Level
":{"Use Disk":false,"Use Memory":false,"Use
Tachyon":false,"Deserialized":false,"Replication":1},"Number of
Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Tachyon
Size":0,"Disk Size":0},{"RDD ID":1,"Name":"1","Storage Leve
l":{"Use Disk":false,"Use Memory":true,"Use
Tachyon":false,"Deserialized":true,"Replication":1},"Number of
Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Tachyon
Size":0,"Disk Size":0},{"RDD ID":0,"Name":"/user/apps/sample
1.txt","Storage Level":{"Use Disk":false,"Use Memory":false,"Use
Tachyon":false,"Deserialized":false,"Replication":1},"Number of
Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Tachyon
Size":0,"Disk Size":0}],"Details":"org
.apache.spark.api.java.AbstractJavaRDDLike.groupBy(JavaRDDLike.scala:46)\ncobaSpark.pack.execute(pack.java:186)\ncobaSpark.pack.main(pack.java:115)\nsun.reflect.NativeMethodAccessorImpl.invoke0(Native
Method)\nsun.reflect.Nati
veMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)\nsun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\njava.lang.reflect.Method.invoke(Method.java:606)\norg.apache.spark.deploy.yarn.Applicati
onMaster$$anon$2.run(ApplicationMaster.scala:480)","Accumulables":[]},{"Stage
ID":1,"Stage Attempt ID":0,"Stage Name":"sortByKey at
pack.java:190","Number of Tasks":2,"RDD Info":[{"RDD
ID":6,"Name":"6","Storage Level":{"Use Disk":false
,"Use Memory":false,"Use
Tachyon":false,"Deserialized":false,"Replication":1},"Number of
Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Tachyon
Size":0,"Disk Size":0},{"RDD ID":4,"Name":"4","Storage Level":{"Use
Disk":fals
e,"Use Memory":false,"Use
Tachyon":false,"Deserialized":false,"Replication":1},"Number of
Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Tachyon
Size":0,"Disk Size":0},{"RDD ID":5,"Name":"5","Storage Level":{"Use
Disk":fal
se,"Use Memory":false,"Use
Tachyon":false,"Deserialized":false,"Replication":1},"Number of
Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Tachyon
Size":0,"Disk Size":0},{"RDD ID":3,"Name":"3","Storage Level":{"Use Disk":fa
lse,"Use Memory":false,"Use
Tachyon":false,"Deserialized":false,"Replication":1},"Number of
Partitions":2,"Number of Cached Partitions":0,"Memory Size":0,"Tachyon
Size":0,"Disk Size":0}],"Details":"org.apache.spark.api.java.JavaPairRDD.so
rtByKey(JavaPairRDD.scala:873)\ncobaSpark.pack.execute(pack.java:190)\ncobaSpark.pack.main(pack.java:115)\nsun.reflect.NativeMethodAccessorImpl.invoke0(Native
Method)\nsun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAc
cessorImpl.java:57)\nsun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\njava.lang.reflect.Method.invoke(Method.java:606)\norg.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.sca
la:480)","Accumulables":[]}],"Stage IDs":[0,1],"Properties":{}}
On 15/02/16 16:32, Jeff Zhang wrote:
there is no application logs of spark job. i think it's because the job
still on running state.
Even the application is in running state, the log should exist too unless
the application is in accepted state. Could you check the RM UI ?
On Mon, Feb 15, 2016 at 5:18 PM, tkg_cangkul <[email protected]> wrote:
there is no application logs of spark job. i think it's because the job
still on running state.
i've tune it like your earlier mail for tuning too. hadoop job was success
using your tuning suggestion config. but still not worked on spark.
is there any other configuration that i must set?? especially in spark
configuration
On 15/02/16 15:53, Jaydeep Vishwakarma wrote:
By the log snap I can see that Launcher is able to launch spark job.
Please share the application logs of spark job.
I am also suspecting 2 cores and lack memory might creating problem.
You may wish to tune your cluster. Please refer my earlier mail for
tuning.
On Mon, Feb 15, 2016 at 2:04 PM, tkg_cangkul <[email protected]
<mailto:[email protected]>> wrote:
hi jaydeep,
thx for your reply.
it has been succeed to submit job. but the proccess stuck at
running state.
the RM memory that i've set is 5GB. and i has been separate the
queue mapred job & oozie launcher job.
RM
i've succees to submit hadoop job with this config and it's
succeed. but when i try submit spark job it was stuck on that
state. is there any missed configuration? pls help. FYI. this is
just a single node machine.
On 15/02/16 14:05, Jaydeep Vishwakarma wrote:
Can you check error you have in app master?
On Mon, Feb 15, 2016 at 12:19 PM, tkg_cangkul<[email protected]>
<mailto:[email protected]> wrote:
i try to subbmit spark job with oozie but it was failed with this
message.
Main class [org.apache.oozie.action.hadoop.SparkMain], exit code [1]
is it any wrong configuration from me?
this is my xml conf.
<workflow-app xmlns='uri:oozie:workflow:0.5' name='tkg-cangkul'>
<start to='spark-node' />
<action name='spark-node'>
<spark xmlns="uri:oozie:spark-action:0.1">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<configuration>
<property>
<name>mapred.job.queue.name <http://mapred.job.queue.name></name>
<value>default</value>
</property>
<property>
<name>oozie.launcher.mapred.job.queue.name <
http://oozie.launcher.mapred.job.queue.name></name>
<value>user1</value>
</property>
</configuration>
<master>yarn-cluster</master>
<name>Spark</name>
<class>cobaSpark.pack</class>
<jar>hdfs://localhost:8020/user/apps/cobaSpark.jar</jar>
<arg>/user/apps/sample1.txt</arg>
<arg>/user/apps/oozie-spark/out</arg>
</spark>
<ok to="end" />
<error to="fail" />
</action>
<kill name="fail">
<message>Workflow failed, error
message[${wf:errorMessage(wf:lastErrorNode())}]
</message>
</kill>
<end name='end' />
</workflow-app>
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