spark-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Koert Kuipers <ko...@tresata.com>
Subject Re: spark 0.8
Date Fri, 18 Oct 2013 16:46:47 GMT
name := "Simple Project"

version := "1.0"

scalaVersion := "2.9.3"

libraryDependencies += "org.apache.spark" %% "spark-core" %
"0.8.0-incubating"

resolvers += "Akka Repository" at "http://repo.akka.io/releases/"

resolvers += "Cloudera Repository" at "
https://repository.cloudera.com/artifactory/cloudera-repos/"

libraryDependencies += "org.apache.hadoop" % "hadoop-client" %
"2.0.0-mr1-cdh4.3.0"




On Fri, Oct 18, 2013 at 12:34 PM, Matei Zaharia <matei.zaharia@gmail.com>wrote:

> Can you post the build.sbt for your program? It needs to include
> hadoop-client for CDH4.3, and that should *not* be listed as provided.
>
> Matei
>
> On Oct 18, 2013, at 8:23 AM, Koert Kuipers <koert@tresata.com> wrote:
>
> ok this has nothing to do with hadoop access. even a simple program that
> uses sc.parallelize blows up in this way.
>
> so spark-shell works well on the same machine i launch this from.
>
> if i launch a simple program without using kryo for serializer and closure
> serialize i get a different error. see below.
> at this point it seems to me i have some issue with task serialization???
>
>
>
> 13/10/18 11:20:37 INFO StandaloneExecutorBackend: Got assigned task 0
> 13/10/18 11:20:37 INFO StandaloneExecutorBackend: Got assigned task 1
> 13/10/18 11:20:37 INFO Executor: Running task ID 1
> 13/10/18 11:20:37 INFO Executor: Running task ID 0
> 13/10/18 11:20:37 INFO Executor: Fetching
> http://192.168.3.171:41629/jars/simple-project_2.9.3-1.0.jar with
> timestamp 1382109635095
> 13/10/18 11:20:37 INFO Utils: Fetching
> http://192.168.3.171:41629/jars/simple-project_2.9.3-1.0.jar to
> /tmp/fetchFileTemp378181753997570700.tmp
> 13/10/18 11:20:37 INFO Executor: Adding
> file:/var/lib/spark/app-20131018112035-0014/1/./simple-project_2.9.3-1.0.jar
> to class loader
> 13/10/18 11:20:37 INFO Executor: caught throwable with stacktrace
> java.io.StreamCorruptedException: invalid type code: 00
>     at
> java.io.ObjectInputStream$BlockDataInputStream.readBlockHeader(ObjectInputStream.java:2467)
>     at
> java.io.ObjectInputStream$BlockDataInputStream.refill(ObjectInputStream.java:2502)
>     at
> java.io.ObjectInputStream$BlockDataInputStream.read(ObjectInputStream.java:2661)
>     at
> java.io.ObjectInputStream$BlockDataInputStream.read(ObjectInputStream.java:2583)
>     at java.io.DataInputStream.readFully(DataInputStream.java:178)
>     at java.io.DataInputStream.readLong(DataInputStream.java:399)
>     at
> java.io.ObjectInputStream$BlockDataInputStream.readLong(ObjectInputStream.java:2803)
>     at java.io.ObjectInputStream.readLong(ObjectInputStream.java:958)
>     at
> org.apache.spark.rdd.ParallelCollectionPartition.readObject(ParallelCollectionRDD.scala:72)
>     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>     at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
>     at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
>     at java.lang.reflect.Method.invoke(Method.java:597)
>     at
> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:969)
>     at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1852)
>     at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1756)
>     at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1326)
>     at java.io.ObjectInputStream.readObject(ObjectInputStream.java:348)
>     at
> org.apache.spark.scheduler.ResultTask.readExternal(ResultTask.scala:135)
>     at
> java.io.ObjectInputStream.readExternalData(ObjectInputStream.java:1795)
>     at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1754)
>     at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1326)
>     at java.io.ObjectInputStream.readObject(ObjectInputStream.java:348)
>     at
> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:39)
>     at
> org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:61)
>     at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:153)
>     at
> java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:895)
>     at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:918)
>     at java.lang.Thread.run(Thread.java:662)
>
>
>
> On Fri, Oct 18, 2013 at 10:59 AM, Koert Kuipers <koert@tresata.com> wrote:
>
>> i created a tiny sbt project as described here:
>> apache.org/docs/latest/quick-start.html#a-standalone-app-in-scala<http://spark.incubator.apache.org/docs/latest/quick-start.html#a-standalone-app-in-scala>
>>
>> it has the correct dependencies: spark-core and the correct hadoop-client
>> for my platform. i tried both the generic spark-core dependency and
>> spark-core dependency compiled against my platform. it runs fine in local
>> mode, but when i switch to the cluster i still always get the following
>> exceptions on tasks:
>>
>> 13/10/18 10:25:53 ERROR Executor: Uncaught exception in thread
>> Thread[pool-5-thread-1,5,main]
>>
>> java.lang.NullPointerException
>>     at
>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
>>     at
>> java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:895)
>>     at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:918)
>>     at java.lang.Thread.run(Thread.java:662)
>>
>> after adding some additional debugging to Executor i see the cause is
>> this:
>> 13/10/18 10:54:47 INFO Executor: caught throwable with stacktrace
>> java.lang.NullPointerException
>>     at
>> org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$2.apply(Executor.scala:155)
>>     at
>> org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$2.apply(Executor.scala:155)
>>     at org.apache.spark.Logging$class.logInfo(Logging.scala:48)
>>     at org.apache.spark.executor.Executor.logInfo(Executor.scala:36)
>>     at
>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:155)
>>
>>     at
>> java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:895)
>>     at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:918)
>>     at java.lang.Thread.run(Thread.java:662)
>>
>> so it seems the offending line is:
>> logInfo("Its epoch is " + task.epoch)
>>
>> i am guessing accessing epoch on the task is throwing the NPE. any ideas?
>>
>>
>>
>> On Thu, Oct 17, 2013 at 8:12 PM, Koert Kuipers <koert@tresata.com> wrote:
>>
>>> sorry one more related question:
>>> i compile against a spark build for hadoop 1.0.4, but the actual
>>> installed version of spark is build against cdh4.3.0-mr1. this also used to
>>> work, and i prefer to do this so i compile against a generic spark build.
>>> could this be the issue?
>>>
>>>
>>> On Thu, Oct 17, 2013 at 8:06 PM, Koert Kuipers <koert@tresata.com>wrote:
>>>
>>>> i have my spark and hadoop related dependencies as "provided" for my
>>>> spark job. this used to work with previous versions. are these now supposed
>>>> to be compile/runtime/default dependencies?
>>>>
>>>>
>>>> On Thu, Oct 17, 2013 at 8:04 PM, Koert Kuipers <koert@tresata.com>wrote:
>>>>
>>>>> yes i did that and i can see the correct jars sitting in lib_managed
>>>>>
>>>>>
>>>>> On Thu, Oct 17, 2013 at 7:56 PM, Matei Zaharia <
>>>>> matei.zaharia@gmail.com> wrote:
>>>>>
>>>>>> Koert, did you link your Spark job to the right version of HDFS as
>>>>>> well? In Spark 0.8, you have to add a Maven dependency on "hadoop-client"
>>>>>> for your version of Hadoop. See
>>>>>> http://spark.incubator.apache.org/docs/latest/quick-start.html#a-standalone-app-in-scala
for
>>>>>> example.
>>>>>>
>>>>>> Matei
>>>>>>
>>>>>> On Oct 17, 2013, at 4:38 PM, Koert Kuipers <koert@tresata.com>
wrote:
>>>>>>
>>>>>> i got the job a little further along by also setting this:
>>>>>> System.setProperty("spark.closure.serializer",
>>>>>> "org.apache.spark.serializer.KryoSerializer")
>>>>>>
>>>>>> not sure why i need to... but anyhow, now my workers start and then
>>>>>> they blow up on this:
>>>>>>
>>>>>> 13/10/17 19:22:57 ERROR Executor: Uncaught exception in thread
>>>>>> Thread[pool-5-thread-1,5,main]
>>>>>> java.lang.NullPointerException
>>>>>>     at
>>>>>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
>>>>>>     at
>>>>>> java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:895)
>>>>>>     at
>>>>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:918)
>>>>>>     at java.lang.Thread.run(Thread.java:662)
>>>>>>
>>>>>>
>>>>>> which is:
>>>>>>  val metrics = attemptedTask.flatMap(t => t.metrics)
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Thu, Oct 17, 2013 at 7:30 PM, dachuan <hdc1112@gmail.com>
wrote:
>>>>>>
>>>>>>> thanks, Mark.
>>>>>>>
>>>>>>>
>>>>>>> On Thu, Oct 17, 2013 at 6:36 PM, Mark Hamstra <
>>>>>>> mark@clearstorydata.com> wrote:
>>>>>>>
>>>>>>>> SNAPSHOTs are not fixed versions, but are floating names
associated
>>>>>>>> with whatever is the most recent code.  So, Spark 0.8.0 is
the current
>>>>>>>> released version of Spark, which is exactly the same today
as it was
>>>>>>>> yesterday, and will be the same thing forever.  Spark 0.8.1-SNAPSHOT
is
>>>>>>>> whatever is currently in branch-0.8.  It changes every time
new code is
>>>>>>>> committed to that branch (which should be just bug fixes
and the few
>>>>>>>> additional features that we wanted to get into 0.8.0, but
that didn't quite
>>>>>>>> make it.)  Not too long from now there will be a release
of Spark 0.8.1, at
>>>>>>>> which time the SNAPSHOT will got to 0.8.2 and 0.8.1 will
be forever frozen.
>>>>>>>>  Meanwhile, the wild new development is taking place on the
master branch,
>>>>>>>> and whatever is currently in that branch becomes 0.9.0-SNAPSHOT.
 This
>>>>>>>> could be quite different from day to day, and there are no
guarantees that
>>>>>>>> things won't be broken in 0.9.0-SNAPSHOT.  Several months
from now there
>>>>>>>> will be a release of Spark 0.9.0 (unless the decision is
made to bump the
>>>>>>>> version to 1.0.0), at which point the SNAPSHOT goes to 0.9.1
and the whole
>>>>>>>> process advances to the next phase of development.
>>>>>>>>
>>>>>>>> The short answer is that releases are stable, SNAPSHOTs are
not,
>>>>>>>> and SNAPSHOTs that aren't on maintenance branches can break
things.  You
>>>>>>>> make your choice of which to use and pay the consequences.
>>>>>>>>
>>>>>>>>
>>>>>>>> On Thu, Oct 17, 2013 at 3:18 PM, dachuan <hdc1112@gmail.com>
wrote:
>>>>>>>>
>>>>>>>>> yeah, I mean 0.9.0-SNAPSHOT. I use git clone and that's
what I
>>>>>>>>> got.. what's the difference? I mean SNAPSHOT and non-SNAPSHOT.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On Thu, Oct 17, 2013 at 6:15 PM, Mark Hamstra <
>>>>>>>>> mark@clearstorydata.com> wrote:
>>>>>>>>>
>>>>>>>>>> Of course, you mean 0.9.0-SNAPSHOT.  There is no
Spark 0.9.0, and
>>>>>>>>>> won't be for several months.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Thu, Oct 17, 2013 at 3:11 PM, dachuan <hdc1112@gmail.com>wrote:
>>>>>>>>>>
>>>>>>>>>>> I'm sorry if this doesn't answer your question
directly, but I
>>>>>>>>>>> have tried spark 0.9.0 and hdfs 1.0.4 just now,
it works..
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> On Thu, Oct 17, 2013 at 6:05 PM, Koert Kuipers
<
>>>>>>>>>>> koert@tresata.com> wrote:
>>>>>>>>>>>
>>>>>>>>>>>> after upgrading from spark 0.7 to spark 0.8
i can no longer
>>>>>>>>>>>> access any files on HDFS.
>>>>>>>>>>>>  i see the error below. any ideas?
>>>>>>>>>>>>
>>>>>>>>>>>> i am running spark standalone on a cluster
that also has
>>>>>>>>>>>> CDH4.3.0 and rebuild spark accordingly. the
jars in lib_managed look good
>>>>>>>>>>>> to me.
>>>>>>>>>>>>
>>>>>>>>>>>> i noticed similar errors in the mailing list
but found no
>>>>>>>>>>>> suggested solutions.
>>>>>>>>>>>>
>>>>>>>>>>>> thanks! koert
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> 13/10/17 17:43:23 ERROR Executor: Exception
in task ID 0
>>>>>>>>>>>> java.io.EOFException
>>>>>>>>>>>> 	at java.io.ObjectInputStream$BlockDataInputStream.readFully(ObjectInputStream.java:2703)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readFully(ObjectInputStream.java:1008)
>>>>>>>>>>>> 	at org.apache.hadoop.io.DataOutputBuffer$Buffer.write(DataOutputBuffer.java:68)
>>>>>>>>>>>> 	at org.apache.hadoop.io.DataOutputBuffer.write(DataOutputBuffer.java:106)
>>>>>>>>>>>> 	at org.apache.hadoop.io.UTF8.readChars(UTF8.java:258)
>>>>>>>>>>>> 	at org.apache.hadoop.io.UTF8.readString(UTF8.java:250)
>>>>>>>>>>>> 	at org.apache.hadoop.mapred.FileSplit.readFields(FileSplit.java:87)
>>>>>>>>>>>> 	at org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:280)
>>>>>>>>>>>> 	at org.apache.hadoop.io.ObjectWritable.readFields(ObjectWritable.java:75)
>>>>>>>>>>>> 	at org.apache.spark.SerializableWritable.readObject(SerializableWritable.scala:39)
>>>>>>>>>>>> 	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native
Method)
>>>>>>>>>>>> 	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
>>>>>>>>>>>> 	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
>>>>>>>>>>>> 	at java.lang.reflect.Method.invoke(Method.java:597)
>>>>>>>>>>>> 	at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:969)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1852)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1756)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1326)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1950)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1874)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1756)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1326)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readObject(ObjectInputStream.java:348)
>>>>>>>>>>>> 	at org.apache.spark.scheduler.ResultTask.readExternal(ResultTask.scala:135)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readExternalData(ObjectInputStream.java:1795)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1754)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1326)
>>>>>>>>>>>> 	at java.io.ObjectInputStream.readObject(ObjectInputStream.java:348)
>>>>>>>>>>>> 	at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:39)
>>>>>>>>>>>> 	at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:61)
>>>>>>>>>>>> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:153)
>>>>>>>>>>>> 	at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:895)
>>>>>>>>>>>> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:918)
>>>>>>>>>>>> 	at java.lang.Thread.run(Thread.java:662)
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> --
>>>>>>>>>>> Dachuan Huang
>>>>>>>>>>> Cellphone: 614-390-7234
>>>>>>>>>>> 2015 Neil Avenue
>>>>>>>>>>> Ohio State University
>>>>>>>>>>> Columbus, Ohio
>>>>>>>>>>> U.S.A.
>>>>>>>>>>> 43210
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> --
>>>>>>>>> Dachuan Huang
>>>>>>>>> Cellphone: 614-390-7234
>>>>>>>>> 2015 Neil Avenue
>>>>>>>>> Ohio State University
>>>>>>>>> Columbus, Ohio
>>>>>>>>> U.S.A.
>>>>>>>>> 43210
>>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> --
>>>>>>> Dachuan Huang
>>>>>>> Cellphone: 614-390-7234
>>>>>>> 2015 Neil Avenue
>>>>>>> Ohio State University
>>>>>>> Columbus, Ohio
>>>>>>> U.S.A.
>>>>>>> 43210
>>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
>

Mime
View raw message