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Mahout, mail # user - Exception during running RowSimilarityJob-Mapper-EntriesToVectorsReducer job
WangRamon
2011-10-19, 08:16
Sebastian Schelter
2011-10-19, 08:20
WangRamon
2011-10-19, 08:27
Sebastian Schelter
2011-10-19, 08:29
WangRamon
2011-10-19, 08:33
WangRamon
2011-10-19, 08:53
Sebastian Schelter
2011-10-19, 08:55
Ted Dunning
2011-10-19, 13:58
WangRamon
2011-10-20, 01:58
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Re: Exception during running RowSimilarityJob-Mapper-EntriesToVectorsReducer job
Ted Dunning 2011-10-19, 13:56
First of all 2 nodes is a very small hadoop cluster. It is not uncommon to have odd problems with such a small cluster and you certainly are very unlikely to see any significant speedup.

Are you running out of disk space?

Sent from my iPhone

On Oct 19, 2011, at 2:16, WangRamon <[EMAIL PROTECTED]> wrote:

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> Hi Guys I'm continuing running the test case with a 1GB data file which contains 600000 users and 2000000 items, all the jobs are running in a 2 two nodes cluster, each node has 32GB RAM and 8 core CPU, the RecommenderJob running until it reach RowSimilarityJob-Mapper-EntriesToVectorsReducer Job, see below for the error log: 11/10/18 23:09:34 INFO mapred.JobClient:  map 11% reduce 1%
> 11/10/18 23:12:46 INFO mapred.JobClient:  map 11% reduce 2%
> 11/10/18 23:13:55 INFO mapred.JobClient:  map 12% reduce 2%
> 11/10/18 23:18:22 INFO mapred.JobClient:  map 13% reduce 2%
> 11/10/18 23:22:50 INFO mapred.JobClient:  map 14% reduce 2%
> 11/10/18 23:27:08 INFO mapred.JobClient:  map 15% reduce 2%
> 11/10/18 23:28:15 INFO mapred.JobClient:  map 15% reduce 3%
> 11/10/18 23:31:42 INFO mapred.JobClient:  map 16% reduce 3%
> 11/10/18 23:33:36 INFO mapred.JobClient: Task Id : attempt_201110181002_0007_r_000000_0, Status : FAILED
> java.io.IOException: Task: attempt_201110181002_0007_r_000000_0 - The reduce copier failed
> at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:380)
> at org.apache.hadoop.mapred.Child.main(Child.java:170)
> Caused by: java.io.IOException: Intermediate merge failed
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.doInMemMerge(ReduceTask.java:2576)
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.run(ReduceTask.java:2501)
> Caused by: java.lang.RuntimeException: java.io.EOFException
> at org.apache.hadoop.io.WritableComparator.compare(WritableComparator.java:103)
> at org.apache.hadoop.mapred.Merger$MergeQueue.lessThan(Merger.java:373)
> at org.apache.hadoop.util.PriorityQueue.upHeap(PriorityQueue.java:123)
> at org.apache.hadoop.util.PriorityQueue.put(PriorityQueue.java:50)
> at org.apache.hadoop.mapred.Merger$MergeQueue.merge(Merger.java:447)
> at org.apache.hadoop.mapred.Merger$MergeQueue.merge(Merger.java:381)
> at org.apache.hadoop.mapred.Merger.merge(Merger.java:107)
> at org.apache.hadoop.mapred.Merger.merge(Merger.java:93)
> at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$InMemFSMergeThread.doInMemMerge(ReduceTask.java:2551)
> ... 1 more
> Caused by: java.io.EOFException
> at java.io.DataInputStream.readByte(DataInputStream.java:250)
> at org.apache.mahout.math.Varint.readUnsignedVarInt(Varint.java:159)
> at org.apache.mahout.math.Varint.readSignedVarInt(Varint.java:140)
> at org.apache.mahout.math.hadoop.similarity.SimilarityMatrixEntryKey.readFields(SimilarityMatrixEntryKey.java:64)
> at org.apache.hadoop.io.WritableComparator.compare(WritableComparator.java:97)
> ... 9 more11/10/18 23:33:37 INFO mapred.JobClient:  map 16% reduce 0%
> 11/10/18 23:35:57 INFO mapred.JobClient:  map 17% reduce 0% I googled a lot and find i should increase "mapred.reduce.tasks" property in Hadoop, so I set it to 8 in my environment and restart this Job only, so far so good, the job is still running by now, but it's still a little slow, so here comes my questions: 1) does it be so slow for this job RowSimilarityJob-Mapper-EntriesToVectorsReducer Job ?2) what does this property "mapred.reduce.tasks" do? And why it can effect RowSimilarityJob-Mapper-EntriesToVectorsReducer Job ? (Maybe i should ask this 2nd question in hadoop user list... but i think people here are both pro at hadoop :) )3) what can i do to increase the speed for this job? Any ideas? Thanks in advance! Ramon