[jira] [Comment Edited] (SPARK-7193) Spark on Mesos may need more tests for spark 1.3.1 release

2015-04-28 Thread Littlestar (JIRA) 

[ 
https://issues.apache.org/jira/browse/SPARK-7193?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14516801#comment-14516801
 ] 

Littlestar edited comment on SPARK-7193 at 4/28/15 10:51 AM:
-

1 master + 7 nodes (spark 1.3.1 + mesos 0.22.0/0.22.1)

{noformat}
15/04/28 18:45:53 INFO spark.SparkContext: Running Spark version 1.3.1

Spark context available as sc.
15/04/28 18:45:57 INFO repl.SparkILoop: Created sql context (with Hive 
support)..
SQL context available as sqlContext.

scala val data = Array(1, 2, 3, 4, 5) 
data: Array[Int] = Array(1, 2, 3, 4, 5)

scala val distData = sc.parallelize(data)
distData: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[0] at 
parallelize at console:23

scala distData.reduce(_+_) 
---
org.apache.spark.SparkException: Job aborted due to stage failure: Task 7 in 
stage 0.0 failed 4 times, most recent failure: Lost task 7.3 in stage 0.0 (TID 
17, hpblade06): ExecutorLostFailure (executor 
20150427-165835-1214949568-5050-6-S0 lost)
Driver stacktrace:
at 
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at 
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at 
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at 
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at 
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at 
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)


{noformat}


was (Author: cnstar9988):
{noformat}
15/04/28 18:45:53 INFO spark.SparkContext: Running Spark version 1.3.1

Spark context available as sc.
15/04/28 18:45:57 INFO repl.SparkILoop: Created sql context (with Hive 
support)..
SQL context available as sqlContext.

scala val data = Array(1, 2, 3, 4, 5) 
data: Array[Int] = Array(1, 2, 3, 4, 5)

scala val distData = sc.parallelize(data)
distData: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[0] at 
parallelize at console:23

scala distData.reduce(_+_) 
---
org.apache.spark.SparkException: Job aborted due to stage failure: Task 7 in 
stage 0.0 failed 4 times, most recent failure: Lost task 7.3 in stage 0.0 (TID 
17, hpblade06): ExecutorLostFailure (executor 
20150427-165835-1214949568-5050-6-S0 lost)
Driver stacktrace:
at 
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at 
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at 
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at 
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at 
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at 
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)


{noformat}

 Spark on Mesos may need more tests for spark 1.3.1 release
 

 Key: SPARK-7193
 URL: https://issues.apache.org/jira/browse/SPARK-7193
 Project: Spark
  Issue Type: Bug
  Components: Mesos
Affects Versions: 1.3.1
Reporter: Littlestar

 Spark on Mesos may need more tests for spark 1.3.1 release
 http://spark.apache.org/docs/latest/running-on-mesos.html
 I tested mesos

[jira] [Comment Edited] (SPARK-7193) Spark on Mesos may need more tests for spark 1.3.1 release

2015-04-28 Thread Littlestar (JIRA) 

[ 
https://issues.apache.org/jira/browse/SPARK-7193?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14516801#comment-14516801
 ] 

Littlestar edited comment on SPARK-7193 at 4/28/15 10:53 AM:
-

1 master + 7 nodes (spark 1.3.1 + mesos 0.22.0/0.22.1)

{noformat}
./spark-shell --master mesos://hpblade02:5050

15/04/28 18:45:53 INFO spark.SparkContext: Running Spark version 1.3.1

Spark context available as sc.
15/04/28 18:45:57 INFO repl.SparkILoop: Created sql context (with Hive 
support)..
SQL context available as sqlContext.

scala val data = Array(1, 2, 3, 4, 5) 
data: Array[Int] = Array(1, 2, 3, 4, 5)

scala val distData = sc.parallelize(data)
distData: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[0] at 
parallelize at console:23

scala distData.reduce(_+_) 
---
org.apache.spark.SparkException: Job aborted due to stage failure: Task 7 in 
stage 0.0 failed 4 times, most recent failure: Lost task 7.3 in stage 0.0 (TID 
17, hpblade06): ExecutorLostFailure (executor 
20150427-165835-1214949568-5050-6-S0 lost)
Driver stacktrace:
at 
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at 
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at 
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at 
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at 
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at 
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)


{noformat}


was (Author: cnstar9988):
1 master + 7 nodes (spark 1.3.1 + mesos 0.22.0/0.22.1)

{noformat}
15/04/28 18:45:53 INFO spark.SparkContext: Running Spark version 1.3.1

Spark context available as sc.
15/04/28 18:45:57 INFO repl.SparkILoop: Created sql context (with Hive 
support)..
SQL context available as sqlContext.

scala val data = Array(1, 2, 3, 4, 5) 
data: Array[Int] = Array(1, 2, 3, 4, 5)

scala val distData = sc.parallelize(data)
distData: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[0] at 
parallelize at console:23

scala distData.reduce(_+_) 
---
org.apache.spark.SparkException: Job aborted due to stage failure: Task 7 in 
stage 0.0 failed 4 times, most recent failure: Lost task 7.3 in stage 0.0 (TID 
17, hpblade06): ExecutorLostFailure (executor 
20150427-165835-1214949568-5050-6-S0 lost)
Driver stacktrace:
at 
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at 
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at 
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at 
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at 
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at 
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at 
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)


{noformat}

 Spark on Mesos may need more tests for spark 1.3.1 release
 

 Key: SPARK-7193
 URL: https://issues.apache.org/jira/browse/SPARK-7193
 Project: Spark
  Issue Type: Bug
  Components: Mesos
Affects Versions: 1.3.1
Reporter: Littlestar

 Spark on Mesos may need more tests for spark 1.3.1

[jira] [Comment Edited] (SPARK-7193) Spark on Mesos may need more tests for spark 1.3.1 release

2015-04-28 Thread Littlestar (JIRA) 

[ 
https://issues.apache.org/jira/browse/SPARK-7193?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14518610#comment-14518610
 ] 

Littlestar edited comment on SPARK-7193 at 4/29/15 2:40 AM:


I think official document missing some notes about Spark on Mesos

I worked well with following:

extract spark-1.3.1-bin-hadoop2.4.tgz, and modify conf\spark-env.sh and repack 
with new spark-1.3.1-bin-hadoop2.4.tgz, and then put to hdfs

spark-env.sh set JAVA_HOME, HADOOP_CONF_DIR, HADOOP_HOME







was (Author: cnstar9988):
I think official document missing some notes about Spark on Mesos

I worked well with following:

extract spark-1.3.1-bin-hadoop2.4.tgz, and modify conf\spark-env.sh and repack 
with new spark-1.3.1-bin-hadoop2.4.tgz, and then put to hdfs

spark-env.sh set JAVA_HOME, HADOO_CONF_DIR, HADOO_HOME






 Spark on Mesos may need more tests for spark 1.3.1 release
 

 Key: SPARK-7193
 URL: https://issues.apache.org/jira/browse/SPARK-7193
 Project: Spark
  Issue Type: Bug
  Components: Mesos
Affects Versions: 1.3.1
Reporter: Littlestar

 Spark on Mesos may need more tests for spark 1.3.1 release
 http://spark.apache.org/docs/latest/running-on-mesos.html
 I tested mesos 0.21.1/0.22.0/0.22.1 RC4.
 It just work well with ./bin/spark-shell --master mesos://host:5050.
 Any task need more than one nodes, it will throws the following exceptions.
 {noformat}
 Exception in thread main org.apache.spark.SparkException: Job aborted due 
 to stage failure: Task 10 in stage 0.0 failed 4 times, most recent failure: 
 Lost task 10.3 in stage 0.0 (TID 127, hpblade05): 
 java.lang.IllegalStateException: unread block data
   at 
 java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2393)
   at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1378)
   at 
 java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1963)
   at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1887)
   at 
 java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1770)
   at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1346)
   at java.io.ObjectInputStream.readObject(ObjectInputStream.java:368)
   at 
 org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:68)
   at 
 org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:94)
   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:185)
   at 
 java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
   at 
 java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
   at java.lang.Thread.run(Thread.java:679)
 Driver stacktrace:
   at 
 org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
   at 
 org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
   at 
 org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
   at 
 scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
   at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
   at 
 org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
   at 
 org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
   at 
 org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
   at scala.Option.foreach(Option.scala:236)
   at 
 org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
   at 
 org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
   at 
 org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
   at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
 15/04/28 15:33:18 ERROR scheduler.LiveListenerBus: Listener 
 EventLoggingListener threw an exception
 java.lang.reflect.InvocationTargetException
   at sun.reflect.GeneratedMethodAccessor3.invoke(Unknown Source)
   at 
 sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
   at java.lang.reflect.Method.invoke(Method.java:606)
   at 
 org.apache.spark.scheduler.EventLoggingListener$$anonfun$logEvent$3.apply(EventLoggingListener.scala:144)
   at 
 org.apache.spark.scheduler.EventLoggingListener$$anonfun$logEvent$3.apply(EventLoggingListener.scala:144)
   at scala.Option.foreach(Option.scala:236)
   at