And that it is caused by this exception, as I've found out 2013-12-19 13:14:28,237 ERROR [pipe-uplink-handler] org.apache.hadoop.mapred.pipes.BinaryProtocol: java.io.EOFException at java.io.DataInputStream.readByte(DataInputStream.java:267) at org.apache.hadoop.io.WritableUtils.readVLong(WritableUtils.java:308) at org.apache.hadoop.io.WritableUtils.readVInt(WritableUtils.java:329) at org.apache.hadoop.mapred.pipes.BinaryProtocol$UplinkReaderThread.run(BinaryProtocol.java:125)
On 18 December 2013 10:52, Silvina Caíno Lores <silvi.ca...@gmail.com>wrote: > I forgot to mention that the wordcount pipes example runs successfully. > > > On 18 December 2013 10:50, Silvina Caíno Lores <silvi.ca...@gmail.com>wrote: > >> Hi everyone, >> >> I'm working with a single node cluster and a Hadoop Pipes job that throws >> the following exception on execution: >> >> 13/12/18 10:44:55 INFO mapreduce.Job: Running job: job_1387359324416_0002 >> 13/12/18 10:45:03 INFO mapreduce.Job: Job job_1387359324416_0002 running >> in uber mode : false >> 13/12/18 10:45:03 INFO mapreduce.Job: map 0% reduce 0% >> 13/12/18 10:45:08 INFO mapreduce.Job: Task Id : >> attempt_1387359324416_0002_m_000000_0, Status : FAILED >> Error: java.io.IOException >> at >> org.apache.hadoop.mapred.pipes.OutputHandler.waitForAuthentication(OutputHandler.java:186) >> at >> org.apache.hadoop.mapred.pipes.Application.waitForAuthentication(Application.java:195) >> at org.apache.hadoop.mapred.pipes.Application.<init>(Application.java:150) >> at >> org.apache.hadoop.mapred.pipes.PipesMapRunner.run(PipesMapRunner.java:69) >> at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:430) >> at org.apache.hadoop.mapred.MapTask.run(MapTask.java:342) >> at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:171) >> at java.security.AccessController.doPrivileged(Native Method) >> at javax.security.auth.Subject.doAs(Subject.java:415) >> at >> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1515) >> at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:166) >> >> /// same exception several times /// >> >> 13/12/18 10:45:25 INFO mapreduce.Job: map 93% reduce 0% >> 13/12/18 10:45:26 INFO mapreduce.Job: map 100% reduce 100% >> 13/12/18 10:45:26 INFO mapreduce.Job: Job job_1387359324416_0002 failed >> with state FAILED due to: Task failed task_1387359324416_0002_m_000000 >> Job failed as tasks failed. failedMaps:1 failedReduces:0 >> >> >> I don't really get why the job is at 100% if it actually failed by the >> way. >> >> Any ideas? Thanks in advance! >> >> Best, >> Silvina >> >> >> >> >> >> >
