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From Steve Loughran <ste...@hortonworks.com>
Subject Re: Spark 1.3.1 On Mesos Issues.
Date Fri, 05 Jun 2015 10:40:37 GMT

On 2 Jun 2015, at 00:14, Dean Wampler <deanwampler@gmail.com<mailto:deanwampler@gmail.com>>
wrote:

It would be nice to see the code for MapR FS Java API, but my google foo failed me (assuming
it's open source)...


I know that MapRFS is closed source, don't know about the java JAR. Why not ask Ted Dunning
(cc'd)  nicely to see if he can track down the stack trace for you.

So, shooting in the dark ;) there are a few things I would check, if you haven't already:

1. Could there be 1.2 versions of some Spark jars that get picked up at run time (but apparently
not in local mode) on one or more nodes? (Side question: Does your node experiment fail on
all nodes?) Put another way, are the classpaths good for all JVM tasks?
2. Can you use just MapR and Spark 1.3.1 successfully, bypassing Mesos?

Incidentally, how are you combining Mesos and MapR? Are you running Spark in Mesos, but accessing
data in MapR-FS?

Perhaps the MapR "shim" library doesn't support Spark 1.3.1.

HTH,

dean

Dean Wampler, Ph.D.
Author: Programming Scala, 2nd Edition<http://shop.oreilly.com/product/0636920033073.do>
(O'Reilly)
Typesafe<http://typesafe.com/>
@deanwampler<http://twitter.com/deanwampler>
http://polyglotprogramming.com<http://polyglotprogramming.com/>

On Mon, Jun 1, 2015 at 2:49 PM, John Omernik <john@omernik.com<mailto:john@omernik.com>>
wrote:
All -

I am facing and odd issue and I am not really sure where to go for support at this point.
 I am running MapR which complicates things as it relates to Mesos, however this HAS worked
in the past with no issues so I am stumped here.

So for starters, here is what I am trying to run. This is a simple show tables using the Hive
Context:

from pyspark import SparkContext, SparkConf
from pyspark.sql import SQLContext, Row, HiveContext
sparkhc = HiveContext(sc)
test = sparkhc.sql("show tables")
for r in test.collect():
  print r

When I run it on 1.3.1 using ./bin/pyspark --master local  This works with no issues.

When I run it using Mesos with all the settings configured (as they had worked in the past)
I get lost tasks and when I zoom in them, the error that is being reported is below.  Basically
it's a NullPointerException on the com.mapr.fs.ShimLoader.  What's weird to me is is I took
each instance and compared both together, the class path, everything is exactly the same.
Yet running in local mode works, and running in mesos fails.  Also of note, when the task
is scheduled to run on the same node as when I run locally, that fails too! (Baffling).

Ok, for comparison, how I configured Mesos was to download the mapr4 package from spark.apache.org<http://spark.apache.org/>.
 Using the exact same configuration file (except for changing the executor tgz from 1.2.0
to 1.3.1) from the 1.2.0.  When I run this example with the mapr4 for 1.2.0 there is no issue
in Mesos, everything runs as intended. Using the same package for 1.3.1 then it fails.

(Also of note, 1.2.1 gives a 404 error, 1.2.2 fails, and 1.3.0 fails as well).

So basically When I used 1.2.0 and followed a set of steps, it worked on Mesos and 1.3.1 fails.
 Since this is a "current" version of Spark, MapR is supports 1.2.1 only.  (Still working
on that).

I guess I am at a loss right now on why this would be happening, any pointers on where I could
look or what I could tweak would be greatly appreciated. Additionally, if there is something
I could specifically draw to the attention of MapR on this problem please let me know, I am
perplexed on the change from 1.2.0 to 1.3.1.

Thank you,

John




Full Error on 1.3.1 on Mesos:
15/05/19 09:31:26 INFO MemoryStore: MemoryStore started with capacity 1060.3 MB java.lang.NullPointerException
at com.mapr.fs.ShimLoader.getRootClassLoader(ShimLoader.java:96) at com.mapr.fs.ShimLoader.injectNativeLoader(ShimLoader.java:232)
at com.mapr.fs.ShimLoader.load(ShimLoader.java:194) at org.apache.hadoop.conf.CoreDefaultProperties.(CoreDefaultProperties.java:60)
at java.lang.Class.forName0(Native Method) at java.lang.Class.forName(Class.java:274) at org.apache.hadoop.conf.Configuration.getClassByNameOrNull(Configuration.java:1847)
at org.apache.hadoop.conf.Configuration.getProperties(Configuration.java:2062) at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:2272)
at org.apache.hadoop.conf.Configuration.loadResources(Configuration.java:2224) at org.apache.hadoop.conf.Configuration.getProps(Configuration.java:2141)
at org.apache.hadoop.conf.Configuration.set(Configuration.java:992) at org.apache.hadoop.conf.Configuration.set(Configuration.java:966)
at org.apache.spark.deploy.SparkHadoopUtil.newConfiguration(SparkHadoopUtil.scala:98) at org.apache.spark.deploy.SparkHadoopUtil.(SparkHadoopUtil.scala:43)
at org.apache.spark.deploy.SparkHadoopUtil$.(SparkHadoopUtil.scala:220) at org.apache.spark.deploy.SparkHadoopUtil$.(SparkHadoopUtil.scala)
at org.apache.spark.util.Utils$.getSparkOrYarnConfig(Utils.scala:1959) at org.apache.spark.storage.BlockManager.(BlockManager.scala:104)
at org.apache.spark.storage.BlockManager.(BlockManager.scala:179) at org.apache.spark.SparkEnv$.create(SparkEnv.scala:310)
at org.apache.spark.SparkEnv$.createExecutorEnv(SparkEnv.scala:186) at org.apache.spark.executor.MesosExecutorBackend.registered(MesosExecutorBackend.scala:70)
java.lang.RuntimeException: Failure loading MapRClient. at com.mapr.fs.ShimLoader.injectNativeLoader(ShimLoader.java:283)
at com.mapr.fs.ShimLoader.load(ShimLoader.java:194) at org.apache.hadoop.conf.CoreDefaultProperties.(CoreDefaultProperties.java:60)
at java.lang.Class.forName0(Native Method) at java.lang.Class.forName(Class.java:274) at org.apache.hadoop.conf.Configuration.getClassByNameOrNull(Configuration.java:1847)
at org.apache.hadoop.conf.Configuration.getProperties(Configuration.java:2062) at org.apache.hadoop.conf.Configuration.loadResource(Configuration.java:2272)
at org.apache.hadoop.conf.Configuration.loadResources(Configuration.java:2224) at org.apache.hadoop.conf.Configuration.getProps(Configuration.java:2141)
at org.apache.hadoop.conf.Configuration.set(Configuration.java:992) at org.apache.hadoop.conf.Configuration.set(Configuration.java:966)
at org.apache.spark.deploy.SparkHadoopUtil.newConfiguration(SparkHadoopUtil.scala:98) at org.apache.spark.deploy.SparkHadoopUtil.(SparkHadoopUtil.scala:43)
at org.apache.spark.deploy.SparkHadoopUtil$.(SparkHadoopUtil.scala:220) at org.apache.spark.deploy.SparkHadoopUtil$.(SparkHadoopUtil.scala)
at org.apache.spark.util.Utils$.getSparkOrYarnConfig(Utils.scala:1959) at org.apache.spark.storage.BlockManager.(BlockManager.scala:104)
at org.apache.spark.storage.BlockManager.(BlockManager.scala:179) at org.apache.spark.SparkEnv$.create(SparkEnv.scala:310)
at org.apache.spark.SparkEnv$.createExecutorEnv(SparkEnv.scala:186) at org.apache.spark.executor.MesosExecutorBackend.registered(MesosExecutorBackend.scala:70)





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