Alex,
Thanks for looking at the output and your feedback. I want to make sure I understand your input correctly. My cluster is a set of old dual core machines and my client is a virtual box VM with 10 GB mem allocated to it. I did some more testing (and will continue to do so to track down the problem). I found that if I move my jar file to the resource manager server on the Dell cluster and execute it local (rather than remotely) it runs to a successful completion. So there is definitely something not right somewhere and I have to believe it is a setup problem on my part, not a hardware problem. Here is the job output: Thanks - rd From: Alexander Alten-Lorenz [mailto:wget.n...@gmail.com] Sent: Friday, February 20, 2015 2:12 AM To: user@hadoop.apache.org Subject: Re: Yarn AM is abending job when submitting a remote job to cluster
15/02/20 19:38:21 INFO client.RMProxy: Connecting to ResourceManager at hadoop0.rdpratti.com/192.168.2.253:8032 15/02/20 19:38:22 INFO input.FileInputFormat: Total input paths to process : 5 15/02/20 19:38:22 INFO mapreduce.JobSubmitter: number of splits:5 15/02/20 19:38:22 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1424003606313_0015 15/02/20 19:38:22 INFO impl.YarnClientImpl: Submitted application application_1424003606313_0015 15/02/20 19:38:22 INFO mapreduce.Job: The url to track the job: http://hadoop0.rdpratti.com:8088/proxy/application_1424003606313_0015/ 15/02/20 19:38:22 INFO mapreduce.Job: Running job: job_1424003606313_0015 15/02/20 19:38:36 INFO mapreduce.Job: Job job_1424003606313_0015 running in uber mode : false 15/02/20 19:38:36 INFO mapreduce.Job: map 0% reduce 0% 15/02/20 19:38:45 INFO mapreduce.Job: map 20% reduce 0% 15/02/20 19:38:47 INFO mapreduce.Job: map 40% reduce 0% 15/02/20 19:38:52 INFO mapreduce.Job: map 80% reduce 0% 15/02/20 19:38:59 INFO mapreduce.Job: map 100% reduce 0% 15/02/20 19:39:03 INFO mapreduce.Job: map 100% reduce 25% 15/02/20 19:39:08 INFO mapreduce.Job: map 100% reduce 50% 15/02/20 19:39:09 INFO mapreduce.Job: map 100% reduce 75% 15/02/20 19:39:10 INFO mapreduce.Job: map 100% reduce 100% 15/02/20 19:39:11 INFO mapreduce.Job: Job job_1424003606313_0015 completed successfully 15/02/20 19:39:11 INFO mapreduce.Job: Counters: 50 File System Counters FILE: Number of bytes read=1628864 FILE: Number of bytes written=4240224 FILE: Number of read operations=0 FILE: Number of large read operations=0 FILE: Number of write operations=0 HDFS: Number of bytes read=5343866 HDFS: Number of bytes written=624 HDFS: Number of read operations=27 HDFS: Number of large read operations=0 HDFS: Number of write operations=8 Job Counters Launched map tasks=5 Launched reduce tasks=4 Data-local map tasks=2 Rack-local map tasks=3 Total time spent by all maps in occupied slots (ms)=43715 Total time spent by all reduces in occupied slots (ms)=30261 Total time spent by all map tasks (ms)=43715 Total time spent by all reduce tasks (ms)=30261 Total vcore-seconds taken by all map tasks=43715 Total vcore-seconds taken by all reduce tasks=30261 Total megabyte-seconds taken by all map tasks=44764160 Total megabyte-seconds taken by all reduce tasks=30987264 Map-Reduce Framework Map input records=175558 Map output records=974078 Map output bytes=5844468 Map output materialized bytes=1631237 Input split bytes=659 Combine input records=0 Combine output records=0 Reduce input groups=35 Reduce shuffle bytes=1631237 Reduce input records=974078 Reduce output records=35 Spilled Records=1948156 Shuffled Maps =20 Failed Shuffles=0 Merged Map outputs=20 GC time elapsed (ms)=862 CPU time spent (ms)=30820 Physical memory (bytes) snapshot=2817286144 Virtual memory (bytes) snapshot=13831352320 Total committed heap usage (bytes)=2295857152 Shuffle Errors BAD_ID=0 CONNECTION=0 IO_ERROR=0 WRONG_LENGTH=0 WRONG_MAP=0 WRONG_REDUCE=0 File Input Format Counters Bytes Read=5343207 File Output Format Counters Bytes Written=624
