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我在Amazon Elastic MapReduce集羣上從命令行運行Mahout 0.6，嘗試使用canopy-cluster〜1500短文檔，並且作業保持失敗，出現「Error：Java heap space 「 信息。在彈性MapReduce上的Mahout：Java堆空間
基於這裏和其他地方前面的問題，我已經拍成每個內存旋鈕可以找我：
的conf/hadoop-env.sh：將所有的堆空間有高達1.5GB的小型實例，甚至4GB的大型實例。
的conf/mapred-site.xml中：添加mapred {地圖，減少} .child.java.opts特性，並設置其值爲-Xmx4000m
$ MAHOUT_HOME /斌/象夫：增加JAVA_HEAP_MAX並將MAHOUT_HEAPSIZE設置爲6GB（在大型實例中）。
而問題仍然存在。我一直在反對這個問題太久 - 有人有什麼建議嗎？
完整的命令和輸出看起來像這樣（大實例的集羣上運行，在希望它會緩解這個問題）：
[email protected]:~$ mahout-distribution-0.6/bin/mahout canopy -i sparse-data/2010/tf-vectors -o canopy-out/2010 -dm org.apache.mahout.common.distance.TanimotoDistanceMeasure -ow -t1 0.5 -t2 0.005 -cl
run with heapsize 6000
-Xmx6000m
MAHOUT_LOCAL is not set; adding HADOOP_CONF_DIR to classpath.
Running on hadoop, using HADOOP_HOME=/home/hadoop
No HADOOP_CONF_DIR set, using /home/hadoop/conf
MAHOUT-JOB: /home/hadoop/mahout-distribution-0.6/mahout-examples-0.6-job.jar
12/04/29 19:50:23 INFO common.AbstractJob: Command line arguments: {--clustering=null, --distanceMeasure=org.apache.mahout.common.distance.TanimotoDistanceMeasure, --endPhase=2147483647, --input=sparse-data/2010/tf-vectors, --method=mapreduce, --output=canopy-out/2010, --overwrite=null, --startPhase=0, --t1=0.5, --t2=0.005, --tempDir=temp}
12/04/29 19:50:24 INFO common.HadoopUtil: Deleting canopy-out/2010
12/04/29 19:50:24 INFO canopy.CanopyDriver: Build Clusters Input: sparse-data/2010/tf-vectors Out: canopy-out/2010 Measure: [email protected]8 t1: 0.5 t2: 0.0050
12/04/29 19:50:24 INFO mapred.JobClient: Default number of map tasks: null
12/04/29 19:50:24 INFO mapred.JobClient: Setting default number of map tasks based on cluster size to : 24
12/04/29 19:50:24 INFO mapred.JobClient: Default number of reduce tasks: 1
12/04/29 19:50:25 INFO mapred.JobClient: Setting group to hadoop
12/04/29 19:50:25 INFO input.FileInputFormat: Total input paths to process : 1
12/04/29 19:50:25 INFO mapred.JobClient: Running job: job_201204291846_0004
12/04/29 19:50:26 INFO mapred.JobClient: map 0% reduce 0%
12/04/29 19:50:45 INFO mapred.JobClient: map 27% reduce 0%
[ ... Continues fine until... ]
12/04/29 20:05:54 INFO mapred.JobClient: map 100% reduce 99%
12/04/29 20:06:12 INFO mapred.JobClient: map 100% reduce 0%
12/04/29 20:06:20 INFO mapred.JobClient: Task Id : attempt_201204291846_0004_r_000000_0, Status : FAILED
Error: Java heap space
12/04/29 20:06:41 INFO mapred.JobClient: map 100% reduce 33%
12/04/29 20:06:44 INFO mapred.JobClient: map 100% reduce 68%
[.. REPEAT SEVERAL ITERATIONS, UNITL...]
12/04/29 20:37:58 INFO mapred.JobClient: map 100% reduce 0%
12/04/29 20:38:09 INFO mapred.JobClient: Job complete: job_201204291846_0004
12/04/29 20:38:09 INFO mapred.JobClient: Counters: 23
12/04/29 20:38:09 INFO mapred.JobClient: Job Counters
12/04/29 20:38:09 INFO mapred.JobClient: Launched reduce tasks=4
12/04/29 20:38:09 INFO mapred.JobClient: SLOTS_MILLIS_MAPS=94447
12/04/29 20:38:09 INFO mapred.JobClient: Total time spent by all reduces waiting after reserving slots (ms)=0
12/04/29 20:38:09 INFO mapred.JobClient: Total time spent by all maps waiting after reserving slots (ms)=0
12/04/29 20:38:09 INFO mapred.JobClient: Rack-local map tasks=1
12/04/29 20:38:09 INFO mapred.JobClient: Launched map tasks=1
12/04/29 20:38:09 INFO mapred.JobClient: Failed reduce tasks=1
12/04/29 20:38:09 INFO mapred.JobClient: SLOTS_MILLIS_REDUCES=23031
12/04/29 20:38:09 INFO mapred.JobClient: FileSystemCounters
12/04/29 20:38:09 INFO mapred.JobClient: HDFS_BYTES_READ=24100612
12/04/29 20:38:09 INFO mapred.JobClient: FILE_BYTES_WRITTEN=49399745
12/04/29 20:38:09 INFO mapred.JobClient: File Input Format Counters
12/04/29 20:38:09 INFO mapred.JobClient: Bytes Read=24100469
12/04/29 20:38:09 INFO mapred.JobClient: Map-Reduce Framework
12/04/29 20:38:09 INFO mapred.JobClient: Map output materialized bytes=49374728
12/04/29 20:38:09 INFO mapred.JobClient: Combine output records=0
12/04/29 20:38:09 INFO mapred.JobClient: Map input records=409
12/04/29 20:38:09 INFO mapred.JobClient: Physical memory (bytes) snapshot=2785939456
12/04/29 20:38:09 INFO mapred.JobClient: Spilled Records=409
12/04/29 20:38:09 INFO mapred.JobClient: Map output bytes=118596530
12/04/29 20:38:09 INFO mapred.JobClient: CPU time spent (ms)=83190
12/04/29 20:38:09 INFO mapred.JobClient: Total committed heap usage (bytes)=2548629504
12/04/29 20:38:09 INFO mapred.JobClient: Virtual memory (bytes) snapshot=4584386560
12/04/29 20:38:09 INFO mapred.JobClient: Combine input records=0
12/04/29 20:38:09 INFO mapred.JobClient: Map output records=409
12/04/29 20:38:09 INFO mapred.JobClient: SPLIT_RAW_BYTES=143
Exception in thread "main" java.lang.InterruptedException: Canopy Job failed processing sparse-data/2010/tf-vectors
at org.apache.mahout.clustering.canopy.CanopyDriver.buildClustersMR(CanopyDriver.java:349)
at org.apache.mahout.clustering.canopy.CanopyDriver.buildClusters(CanopyDriver.java:236)
at org.apache.mahout.clustering.canopy.CanopyDriver.run(CanopyDriver.java:145)
at org.apache.mahout.clustering.canopy.CanopyDriver.run(CanopyDriver.java:109)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
at org.apache.mahout.clustering.canopy.CanopyDriver.main(CanopyDriver.java:61)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:68)
at org.apache.hadoop.util.ProgramDriver.driver(ProgramDriver.java:139)
at org.apache.mahout.driver.MahoutDriver.main(MahoutDriver.java:188)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hadoop.util.RunJar.main(RunJar.java:156)
感謝您的回覆！澄清：我更改的配置全部在EMR主節點上，而不是在本地計算機上。相同的聚類可以處理相同數據集的較小變化;任何想法除了內存問題可能會導致問題？ –
你正在運行你自己的集羣嗎？無論如何，我沒有看到內存是問題。跑步者一直未能完成等待工作中沒有發生什麼事的工作。去檢查工作人員的日誌？ –
在日誌Sean中提到了OOM，我們可以看到在12/04/29 20:06:20失敗的任務失敗，我想所有的重新嘗試都失敗了。我不熟悉天篷，但是決定4個減少任務的是什麼？ –