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Hadoop Mapreduce Wordcount example gets terminated unexpectedly

I am trying Hadoop map-reduce in Linux (Ubuntu Virtual Machine) by following the link
I ran the wordcount example on a sample file. The process gets killed unexpectedly. How can I debug this ?
Initially I was getting an insufficient memory error on large data set.
15/11/28 19:24:27 INFO mapred.Task: Using ResourceCalculatorProcessTree : [ ]
15/11/28 19:24:27 INFO mapred.MapTask: Processing split: hdfs://localhost:54310/user/hduser/eg2/a.txt:0+1538
Java HotSpot(TM) 64-Bit Server VM warning: INFO: os::commit_memory(0x00000000e6093000, 104861696, 0) failed; error='Cannot allocate memory' (errno=12)
#
# There is insufficient memory for the Java Runtime Environment to continue.
# Native memory allocation (malloc) failed to allocate 104861696 bytes for committing reserved memory.
# An error report file with more information is saved as:
# /usr/local/hadoop/hs_err_pid7516.log
So I reduced the size of my files and tried again which resulted in unexpected termination.
hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0.jar wordcount /user/hduser/eg2/ /user/hduser/eg2/eg2-output2
......
......
15/11/28 18:55:44 INFO mapred.LocalJobRunner: Waiting for map tasks
15/11/28 18:55:44 INFO mapred.LocalJobRunner: Starting task: attempt_local1996683170_0001_m_000000_0
15/11/28 18:55:44 INFO mapred.Task: Using ResourceCalculatorProcessTree : [ ]
15/11/28 18:55:44 INFO mapred.MapTask: Processing split: hdfs://localhost:54310/user/hduser/eg2/a.txt:0+1538
15/11/28 18:55:45 INFO mapreduce.Job: Job job_local1996683170_0001 running in uber mode : false
15/11/28 18:55:45 INFO mapreduce.Job: map 0% reduce 0%
Killed
Why is the process getting terminated ?

Try:
Hadoop job -list
Kill all jobs and rerun it:
Hadoop job –kill <JobID>
Try checking the logs of job tracker for error
http://localhost:50070/ – web UI of the NameNode daemon
http://localhost:50030/ – web UI of the JobTracker daemon
http://localhost:50060/ – web UI of the TaskTracker daemon

The size of the data set didn't matter. Hadoop didn't have enough memory to start. I tried increasing the memory of my VM and the issue got fixed.

Hadoop kNN join algorithm stuck at map 100% reduce 0%

15/06/11 10:31:51 INFO mapreduce.Job: map 100% reduce 0%
I am trying to run open source kNN join MapReduce hbrj algorithm on a Hadoop 2.6.0 for single node cluster - pseudo-distributed operation installed on my laptop (OSX). (The source can be found here: http://www.cs.utah.edu/~lifeifei/knnj/). This algorithm is comprised of two MapReduce phases where the second phase uses the first phase's output files as its input. The first phase maps and reduces successfully - I can also look into the output files and everything seems right. However, when running the second phase the job is said to finish successfully even though it never reduces or even enters that stage I believe.
Here is what gets printed as I run phase 2 (I am including everything in hopes that it can be useful)
2015-06-11 10:31:47.526 java[3918:305930] Unable to load realm info from SCDynamicStore
15/06/11 10:31:48 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/06/11 10:31:49 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
15/06/11 10:31:49 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
15/06/11 10:31:49 INFO jvm.JvmMetrics: Cannot initialize JVM Metrics with processName=JobTracker, sessionId= - already initialized
15/06/11 10:31:49 INFO mapred.FileInputFormat: Total input paths to process : 64
15/06/11 10:31:49 INFO mapreduce.JobSubmitter: number of splits:64
15/06/11 10:31:50 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local1089761712_0001
15/06/11 10:31:50 INFO mapred.LocalJobRunner: OutputCommitter set in config null
15/06/11 10:31:50 INFO mapreduce.Job: The url to track the job: http://localhost:8080/
15/06/11 10:31:50 INFO mapred.LocalJobRunner: OutputCommitter is org.apache.hadoop.mapred.FileOutputCommitter
15/06/11 10:31:50 INFO mapreduce.Job: Running job: job_local1089761712_0001
15/06/11 10:31:50 INFO mapred.LocalJobRunner: Waiting for map tasks
15/06/11 10:31:50 INFO mapred.LocalJobRunner: Starting task: attempt_local1089761712_0001_m_000000_0
15/06/11 10:31:50 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
15/06/11 10:31:50 INFO mapred.Task: Using ResourceCalculatorProcessTree : null
15/06/11 10:31:50 INFO mapred.MapTask: Processing split: hdfs://localhost:9000/user/sasha/hbrj/output/part-00042:0+872
15/06/11 10:31:50 INFO mapred.MapTask: numReduceTasks: 0
15/06/11 10:31:50 INFO mapred.LocalJobRunner:
15/06/11 10:31:50 INFO mapred.Task: Task:attempt_local1089761712_0001_m_000000_0 is done. And is in the process of committing
15/06/11 10:31:50 INFO mapred.LocalJobRunner:
15/06/11 10:31:50 INFO mapred.Task: Task attempt_local1089761712_0001_m_000000_0 is allowed to commit now
15/06/11 10:31:50 INFO output.FileOutputCommitter: Saved output of task 'attempt_local1089761712_0001_m_000000_0' to hdfs://localhost:9000/user/sasha/hbrj/output2/_temporary/0/task_local1089761712_0001_m_000000
15/06/11 10:31:50 INFO mapred.MapTask: numReduceTasks: 0
15/06/11 10:31:50 INFO mapred.LocalJobRunner:
15/06/11 10:31:50 INFO mapred.Task: Task:attempt_local1089761712_0001_m_000000_0 is done. And is in the process of committing
15/06/11 10:31:50 INFO mapred.LocalJobRunner:
15/06/11 10:31:50 INFO mapred.Task: Task attempt_local1089761712_0001_m_000000_0 is allowed to commit now
15/06/11 10:31:50 INFO output.FileOutputCommitter: Saved output of task 'attempt_local1089761712_0001_m_000000_0' to hdfs://localhost:9000/user/sasha/hbrj/output2/_temporary/0/task_local1089761712_0001_m_000000
15/06/11 10:31:50 INFO mapred.LocalJobRunner: hdfs://localhost:9000/user/sasha/hbrj/output/part-00042:0+872
15/06/11 10:31:50 INFO mapred.Task: Task 'attempt_local1089761712_0001_m_000000_0' done.
continues in this fashion until...
15/06/11 10:31:51 INFO mapred.LocalJobRunner: Finishing task: attempt_local1089761712_0001_m_000012_0
15/06/11 10:31:51 INFO mapred.LocalJobRunner: Starting task: attempt_local1089761712_0001_m_000013_0
15/06/11 10:31:51 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
15/06/11 10:31:51 INFO mapred.Task: Using ResourceCalculatorProcessTree : null
15/06/11 10:31:51 INFO mapred.MapTask: Processing split: hdfs://localhost:9000/user/sasha/hbrj/output/part-00015:0+646
15/06/11 10:31:51 INFO mapred.MapTask: numReduceTasks: 0
15/06/11 10:31:51 INFO mapreduce.Job: Job job_local1089761712_0001 running in uber mode : false
15/06/11 10:31:51 INFO mapreduce.Job: map 100% reduce 0%
15/06/11 10:31:51 INFO mapred.LocalJobRunner:
15/06/11 10:31:51 INFO mapred.Task: Task:attempt_local1089761712_0001_m_000013_0 is done. And is in the process of committing
15/06/11 10:31:51 INFO mapred.LocalJobRunner:
15/06/11 10:31:51 INFO mapred.Task: Task attempt_local1089761712_0001_m_000013_0 is allowed to commit now
15/06/11 10:31:51 INFO output.FileOutputCommitter: Saved output of task 'attempt_local1089761712_0001_m_000013_0' to hdfs://localhost:9000/user/sasha/hbrj/output2/_temporary/0/task_local1089761712_0001_m_000013
15/06/11 10:31:51 INFO mapred.LocalJobRunner: hdfs://localhost:9000/user/sasha/hbrj/output/part-00015:0+646
15/06/11 10:31:51 INFO mapred.Task: Task 'attempt_local1089761712_0001_m_000013_0' done.
15/06/11 10:31:51 INFO mapred.LocalJobRunner: Finishing task: attempt_local1089761712_0001_m_000013_0
15/06/11 10:31:51 INFO mapred.LocalJobRunner: Starting task: attempt_local1089761712_0001_m_000014_0
Starting task ... Finishing task
repeats in the manner as seen below (which is the last task) and the job is said to complete successfully:
15/06/11 10:31:53 INFO mapred.MapTask: numReduceTasks: 0
15/06/11 10:31:53 INFO mapred.LocalJobRunner:
15/06/11 10:31:53 INFO mapred.Task: Task:attempt_local1089761712_0001_m_000063_0 is done. And is in the process of committing
15/06/11 10:31:53 INFO mapred.LocalJobRunner:
15/06/11 10:31:53 INFO mapred.Task: Task attempt_local1089761712_0001_m_000063_0 is allowed to commit now
15/06/11 10:31:53 INFO output.FileOutputCommitter: Saved output of task 'attempt_local1089761712_0001_m_000063_0' to hdfs://localhost:9000/user/sasha/hbrj/output2/_temporary/0/task_local1089761712_0001_m_000063
15/06/11 10:31:53 INFO mapred.LocalJobRunner: hdfs://localhost:9000/user/sasha/hbrj/output/part-00004:0+178
15/06/11 10:31:53 INFO mapred.Task: Task 'attempt_local1089761712_0001_m_000063_0' done.
15/06/11 10:31:53 INFO mapred.LocalJobRunner: Finishing task: attempt_local1089761712_0001_m_000063_0
15/06/11 10:31:53 INFO mapred.LocalJobRunner: map task executor complete.
15/06/11 10:31:54 INFO mapreduce.Job: Job job_local1089761712_0001 completed successfully
15/06/11 10:31:54 INFO mapreduce.Job: Counters: 20
File System Counters
FILE: Number of bytes read=96487226
FILE: Number of bytes written=106993472
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=1157797
HDFS: Number of bytes written=884212
HDFS: Number of read operations=8576
HDFS: Number of large read operations=0
HDFS: Number of write operations=4224
Map-Reduce Framework
Map input records=793
Map output records=793
Input split bytes=6848
Spilled Records=0
Failed Shuffles=0
Merged Map outputs=0
GC time elapsed (ms)=42
Total committed heap usage (bytes)=12124160000
File Input Format Counters
Bytes Read=28599
File Output Format Counters
Bytes Written=21848
What I have done so far:
I have found a similar question here: Hadoop WordCount example stuck at map 100% reduce 0% and followed some of the advice given. In particular:
At one point I configured Yarn so that I could go into localhost:8088 and monitor the job. All the mappers worked correctly - no failures, and the job ended abruptly right after the last mapper was successful, that is no reducers were ever started. Mapper was shown as 100% and reduce as 0%.
Using this command:
cat /path/to/logs/*.log | grep ERROR
returned nothing.
As I can see the output of the mapper stage I believe the problem does not lie there.
I have tried debugging: putting print statements in the configure method of the Reduce and the reduce method itself. None of them got printed when I rerun the file.
Additional note: Since the algorithm I am using was published and is supposed to work, I believe the problem could possibly arise from the fact that the code is 3 years old and was written for Hadoop 0.20.2 version but I guess I should not be too sure of this.
I understand that this is a specific question but I hope that someone could point me in the right direction. I would be happy to include anything else you might find useful. Any help is greatly appreciated!

Why hadoop just stuck there after I set the map compression properties?

Here's the code snippet that works fine:
Configuration conf = new Configuration();
//PROBLEM PART!!!!!
//conf.setBoolean("mapred.compress.map.output", true);
//conf.set("mapred.output.compression.type", "BLOCK");
//conf.setClass("mapred.map.output.compression.codec", GzipCodec.class, CompressionCodec.class);
Job job = new Job(conf, "WordCount");
job.setJarByClass(WordCount.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setMapperClass(WordCountMap.class);
job.setReducerClass(Reduce.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
job.waitForCompletion(true);
But if I enable the PROBLEM PART in the code snippet above, the output of console will stuck at:
13/12/26 18:08:06 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
13/12/26 18:08:06 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
13/12/26 18:08:06 WARN mapred.JobClient: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
13/12/26 18:08:06 INFO input.FileInputFormat: Total input paths to process : 20
13/12/26 18:08:06 WARN snappy.LoadSnappy: Snappy native library not loaded
13/12/26 18:08:06 INFO mapred.JobClient: Running job: job_local1943436108_0001
13/12/26 18:08:06 INFO mapred.LocalJobRunner: Waiting for map tasks
13/12/26 18:08:06 INFO mapred.LocalJobRunner: Starting task: attempt_local1943436108_0001_m_000000_0
13/12/26 18:08:07 INFO util.ProcessTree: setsid exited with exit code 0
13/12/26 18:08:07 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin#731d2572
13/12/26 18:08:07 INFO mapred.MapTask: Processing split: hdfs://localhost:9000/user/jude/input/capacity-scheduler.xml:0+7457
13/12/26 18:08:07 INFO mapred.MapTask: io.sort.mb = 100
13/12/26 18:08:07 INFO mapred.MapTask: data buffer = 79691776/99614720
13/12/26 18:08:07 INFO mapred.MapTask: record buffer = 262144/327680
13/12/26 18:08:07 INFO mapred.MapTask: Starting flush of map output
13/12/26 18:08:07 INFO compress.CodecPool: Got brand-new compressor
13/12/26 18:08:07 INFO mapred.MapTask: Starting flush of map output
13/12/26 18:08:07 INFO mapred.JobClient: map 0% reduce 0%
13/12/26 18:08:12 INFO mapred.LocalJobRunner:
13/12/26 18:08:13 INFO mapred.JobClient: map 5% reduce 0%
//no more
I just intend to compress the output of map, is there anything wrong with my code? Thanks a lot!

Using compression requires Hadoop to use native libraries for your platform, but apparently you don't have them (or have not configured the path to the libraries correctly). This is the message that is explaining the problem:
[...] NativeCodeLoader: Unable to load native-hadoop library for your platform...
Possible solutions:
Most common problem is to have the 32-bit libraries on a 64-bit architecture. You can download the pre-compiled 64 native libraries OR compile them yourself using mvn package -Pdist,**native**,docs.
Or, you may need to configure the path to the native libraries correctly; see these other questions on how to do this: use -Djava.libray.path, or LD_LIBRARY_PATH.

Words Count output shows mapred instead of mapreduce

I just configured my Ubuntu 13.10 to work in pseudo-distributed mode for my mapreduce code development. I had installed hadoop 0.20.2 version of hadoop. Everything sis running fine and I am able to start all five deamons as well.
On same machine I had downloaded eclipse and added all hadoop based libraries into it. I am able to run my map reduce word count example also from eclipse IDE directly. Only thing which is bothering me is that while I run my word count example it prints in console something like this:
13/09/23 16:11:05 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your
platform... using builtin-java classes where applicable
13/09/23 16:11:05 WARN mapred.JobClient: No job jar file set. User classes may not be found. See
JobConf(Class) or JobConf#setJar(String).
13/09/23 16:11:05 INFO input.FileInputFormat: Total input paths to process : 1
13/09/23 16:11:06 INFO mapred.JobClient: Running job: job_local_0001
13/09/23 16:11:06 INFO util.ProcessTree: setsid exited with exit code 0
13/09/23 16:11:06 INFO mapred.Task: Using ResourceCalculatorPlugin :
org.apache.hadoop.util.LinuxResourceCalculatorPlugin#c931fc
13/09/23 16:11:06 INFO mapred.MapTask: io.sort.mb = 100
13/09/23 16:11:07 INFO mapred.JobClient: map 0% reduce 0%
13/09/23 16:11:07 INFO mapred.MapTask: data buffer = 79691776/99614720
13/09/23 16:11:07 INFO mapred.MapTask: record buffer = 262144/327680
13/09/23 16:11:08 INFO mapred.MapTask: Starting flush of map output
13/09/23 16:11:08 INFO mapred.MapTask: Finished spill 0
13/09/23 16:11:08 INFO mapred.Task: Task:attempt_local_0001_m_000000_0 is done. And is in the
process of commiting
13/09/23 16:11:09 INFO mapred.LocalJobRunner:
13/09/23 16:11:09 INFO mapred.Task: Task 'attempt_local_0001_m_000000_0' done.
13/09/23 16:11:09 INFO mapred.Task: Using ResourceCalculatorPlugin :
org.apache.hadoop.util.LinuxResourceCalculatorPlugin#1342ba4
13/09/23 16:11:09 INFO mapred.LocalJobRunner:
13/09/23 16:11:09 INFO mapred.Merger: Merging 1 sorted segments
13/09/23 16:11:10 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total
size: 48 bytes
13/09/23 16:11:10 INFO mapred.LocalJobRunner:
13/09/23 16:11:10 INFO mapred.Task: Task:attempt_local_0001_r_000000_0 is done. And is in the
process of commiting
13/09/23 16:11:10 INFO mapred.LocalJobRunner:
13/09/23 16:11:10 INFO mapred.Task: Task attempt_local_0001_r_000000_0 is allowed to commit now
13/09/23 16:11:10 INFO output.FileOutputCommitter: Saved output of task
'attempt_local_0001_r_000000_0' to outputWords
13/09/23 16:11:10 INFO mapred.JobClient: map 100% reduce 0%
13/09/23 16:11:12 INFO mapred.LocalJobRunner: reduce > reduce
13/09/23 16:11:12 INFO mapred.Task: Task 'attempt_local_0001_r_000000_0' done.
13/09/23 16:11:12 WARN mapred.LocalJobRunner: job_local_0001
java.lang.NoClassDefFoundError: org/apache/commons/httpclient/HttpMethod
at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:284)
Caused by: java.lang.ClassNotFoundException: org.apache.commons.httpclient.HttpMethod
at java.net.URLClassLoader$1.run(URLClassLoader.java:217)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:205)
at java.lang.ClassLoader.loadClass(ClassLoader.java:321)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:294)
at java.lang.ClassLoader.loadClass(ClassLoader.java:266)
... 1 more
Exception in thread "Thread-1" java.lang.NoClassDefFoundError:
org/apache/commons/httpclient/HttpMethod
at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:300)
Caused by: java.lang.ClassNotFoundException: org.apache.commons.httpclient.HttpMethod
at java.net.URLClassLoader$1.run(URLClassLoader.java:217)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:205)
at java.lang.ClassLoader.loadClass(ClassLoader.java:321)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:294)
at java.lang.ClassLoader.loadClass(ClassLoader.java:266)
... 1 more
13/09/23 16:11:13 INFO mapred.JobClient: map 100% reduce 100%
13/09/23 16:11:13 INFO mapred.JobClient: Job complete: job_local_0001
13/09/23 16:11:13 INFO mapred.JobClient: Counters: 20
13/09/23 16:11:13 INFO mapred.JobClient: File Output Format Counters
13/09/23 16:11:13 INFO mapred.JobClient: Bytes Written=42
13/09/23 16:11:13 INFO mapred.JobClient: FileSystemCounters
13/09/23 16:11:13 INFO mapred.JobClient: FILE_BYTES_READ=534
13/09/23 16:11:13 INFO mapred.JobClient: FILE_BYTES_WRITTEN=63640
13/09/23 16:11:13 INFO mapred.JobClient: File Input Format Counters
13/09/23 16:11:13 INFO mapred.JobClient: Bytes Read=63
13/09/23 16:11:13 INFO mapred.JobClient: Map-Reduce Framework
13/09/23 16:11:13 INFO mapred.JobClient: Map output materialized bytes=52
13/09/23 16:11:13 INFO mapred.JobClient: Map input records=4
13/09/23 16:11:13 INFO mapred.JobClient: Reduce shuffle bytes=0
13/09/23 16:11:13 INFO mapred.JobClient: Spilled Records=8
13/09/23 16:11:13 INFO mapred.JobClient: Map output bytes=110
13/09/23 16:11:13 INFO mapred.JobClient: Total committed heap usage (bytes)=231350272
13/09/23 16:11:13 INFO mapred.JobClient: CPU time spent (ms)=0
13/09/23 16:11:13 INFO mapred.JobClient: SPLIT_RAW_BYTES=124
13/09/23 16:11:13 INFO mapred.JobClient: Combine input records=12
13/09/23 16:11:13 INFO mapred.JobClient: Reduce input records=4
13/09/23 16:11:13 INFO mapred.JobClient: Reduce input groups=4
13/09/23 16:11:13 INFO mapred.JobClient: Combine output records=4
13/09/23 16:11:13 INFO mapred.JobClient: Physical memory (bytes) snapshot=0
13/09/23 16:11:13 INFO mapred.JobClient: Reduce output records=4
13/09/23 16:11:13 INFO mapred.JobClient: Virtual memory (bytes) snapshot=0
13/09/23 16:11:13 INFO mapred.JobClient: Map output records=12
In above output if you see there are few things I am not sure are correct:
its printing mapred.JobClient: Mapred is old library of hadoop so how can i make it to mapreduce ( alreday added recent new library into eclipse still getting same mapred message)
Why is this error coming : java.lang.NoClassDefFoundError
I am able to get output directory generated with proper results also.
Let me know if need any other details.
Hope to get an answer.
Happy hadooping!!!

You are getting --
Exception in thread "Thread-1" java.lang.NoClassDefFoundError:
org/apache/commons/httpclient/HttpMethod
because, you haven't included some dependent jars in your classpath.
Try including the following too located inside your lib/ directory and retry --
commons-httpclient-3.1.jar
commons-cli-1.2.jar
commons-logging-1.0.4.jar
commons-logging-api-1.0.4.jar
log4j-1.2.15.jar
commons-cli-1.2.jar
jackson-core-asl-1.5.2.jar
jackson-mapper-asl-1.5.2.jar
If including these doesn't work, please include all the jars in the lib/ directory.
Furthermore, mapred.JobClient is not deprecated and referenced by Hadoop (both mapred API or mapreduce API).

Hadoop example job fails in Standalone mode with: "Unable to load native-hadoop library"

I'm trying to get the simplest Hadoop "hello world" setup to work, but when I run the following command:
hadoop jar /usr/share/hadoop/hadoop-examples-1.0.4.jar grep input output 'dfs[a-z.]+'
I get the following warning:
12/11/30 16:36:40 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
And a full error trace that looks like:
12/11/30 16:57:18 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
12/11/30 16:57:18 WARN snappy.LoadSnappy: Snappy native library not loaded
12/11/30 16:57:18 INFO mapred.FileInputFormat: Total input paths to process : 6
12/11/30 16:57:18 INFO mapred.JobClient: Running job: job_local_0001
12/11/30 16:57:18 INFO util.ProcessTree: setsid exited with exit code 0
12/11/30 16:57:18 INFO mapred.Task: Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin#7d4ecfa4
12/11/30 16:57:18 INFO mapred.MapTask: numReduceTasks: 1
12/11/30 16:57:18 INFO mapred.MapTask: io.sort.mb = 100
12/11/30 16:57:18 WARN mapred.LocalJobRunner: job_local_0001
java.lang.OutOfMemoryError: Java heap space
at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.<init>(MapTask.java:949)
at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:428)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:372)
at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:212)
12/11/30 16:57:19 INFO mapred.JobClient: map 0% reduce 0%
12/11/30 16:57:19 INFO mapred.JobClient: Job complete: job_local_0001
12/11/30 16:57:19 INFO mapred.JobClient: Counters: 0
12/11/30 16:57:19 INFO mapred.JobClient: Job Failed: NA
java.io.IOException: Job failed!
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:1265)
at org.apache.hadoop.examples.Grep.run(Grep.java:69)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
at org.apache.hadoop.examples.Grep.main(Grep.java:93)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:68)
at org.apache.hadoop.util.ProgramDriver.driver(ProgramDriver.java:139)
at org.apache.hadoop.examples.ExampleDriver.main(ExampleDriver.java:64)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at org.apache.hadoop.util.RunJar.main(RunJar.java:156)
I'm running Ubuntu 12.04 and Java version:
java version "1.7.0"
Java(TM) SE Runtime Environment (build 1.7.0-b147)
Java HotSpot(TM) 64-Bit Server VM (build 21.0-b17, mixed mode)
Any ideas?

The warning tells you that the compression codec is not (properly) installed for Hadoop.
To install the Snappy compression, have a look at: http://code.google.com/p/hadoop-snappy/
However, a more serious issue is the OutOfMemoryError you get. Check you input, increase
the heap size, if necessary. You might also have a look at this related question:
out of Memory Error in Hadoop