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From Koert Kuipers <ko...@tresata.com>
Subject Re: spark 0.8
Date Fri, 18 Oct 2013 14:59:13 GMT
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
>>>>>
>>>>
>>>>
>>>>
>>>
>>
>

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