Return-Path: Delivered-To: apmail-hadoop-hdfs-issues-archive@minotaur.apache.org Received: (qmail 11278 invoked from network); 10 Jul 2009 18:21:28 -0000 Received: from hermes.apache.org (HELO mail.apache.org) (140.211.11.3) by minotaur.apache.org with SMTP; 10 Jul 2009 18:21:28 -0000 Received: (qmail 45382 invoked by uid 500); 10 Jul 2009 18:21:38 -0000 Delivered-To: apmail-hadoop-hdfs-issues-archive@hadoop.apache.org Received: (qmail 45312 invoked by uid 500); 10 Jul 2009 18:21:37 -0000 Mailing-List: contact hdfs-issues-help@hadoop.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: hdfs-issues@hadoop.apache.org Delivered-To: mailing list hdfs-issues@hadoop.apache.org Received: (qmail 45071 invoked by uid 99); 10 Jul 2009 18:21:37 -0000 Received: from athena.apache.org (HELO athena.apache.org) (140.211.11.136) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 10 Jul 2009 18:21:37 +0000 X-ASF-Spam-Status: No, hits=-2000.0 required=10.0 tests=ALL_TRUSTED X-Spam-Check-By: apache.org Received: from [140.211.11.140] (HELO brutus.apache.org) (140.211.11.140) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 10 Jul 2009 18:21:35 +0000 Received: from brutus (localhost [127.0.0.1]) by brutus.apache.org (Postfix) with ESMTP id E4C63234C1F2 for ; Fri, 10 Jul 2009 11:21:14 -0700 (PDT) Message-ID: <1269441045.1247250074936.JavaMail.jira@brutus> Date: Fri, 10 Jul 2009 11:21:14 -0700 (PDT) From: "Ravi Phulari (JIRA)" To: hdfs-issues@hadoop.apache.org Subject: [jira] Resolved: (HDFS-486) error : too many fetch failures In-Reply-To: <919744892.1247220794794.JavaMail.jira@brutus> MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 X-Virus-Checked: Checked by ClamAV on apache.org [ https://issues.apache.org/jira/browse/HDFS-486?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Ravi Phulari resolved HDFS-486. ------------------------------- Resolution: Invalid Closing as invalid because this error is not due to HDFS. The fetch is over HTTP, so it has nothing to do with HDFS . and this could be anything from network congestion to a bad disk. The issue is invalid, since the framework- failing to obtain the map output- reexecuted the map and completed the job successfully. If you have any issues with Map Reduce please write email to mapreduce-user at hadoop.apache.org > error : too many fetch failures > ------------------------------- > > Key: HDFS-486 > URL: https://issues.apache.org/jira/browse/HDFS-486 > Project: Hadoop HDFS > Issue Type: Bug > Environment: operating system : fedora-8 > virtual environment : using xen > hadoop-0.18.3 > Reporter: vijayan.B > Original Estimate: 48h > Remaining Estimate: 48h > > i configured the hadoop cluster environment with one physical mahine as data node and 7(2physical and 5 virtual machines) as namenode > when i submitted the sort job(from hadoop-core-example) > it finished with following error, can you explain why this is happening and how to solve this? > output from terminal ************************************************************ > [root@hadoop1 hadoop-0.18.3]# bin/hadoop jar hadoop-0.18.3-examples.jar sort input13 output1 > Running on 7 nodes to sort from hdfs://hadoop1:8022/user/root/input13 into hdfs://hadoop1:8022/user/root/output1 with 12 reduces. > Job started: Fri Jul 10 14:00:19 IST 2009 > 09/07/10 14:00:19 INFO mapred.FileInputFormat: Total input paths to process : 1 > 09/07/10 14:00:19 INFO mapred.FileInputFormat: Total input paths to process : 1 > 09/07/10 14:00:19 INFO mapred.JobClient: Running job: job_200907101344_0002 > 09/07/10 14:00:20 INFO mapred.JobClient: map 0% reduce 0% > 09/07/10 14:00:24 INFO mapred.JobClient: map 6% reduce 0% > 09/07/10 14:00:25 INFO mapred.JobClient: map 12% reduce 0% > 09/07/10 14:00:28 INFO mapred.JobClient: map 31% reduce 0% > 09/07/10 14:00:29 INFO mapred.JobClient: map 50% reduce 0% > 09/07/10 14:00:33 INFO mapred.JobClient: map 66% reduce 0% > 09/07/10 14:00:34 INFO mapred.JobClient: map 72% reduce 0% > 09/07/10 14:00:35 INFO mapred.JobClient: map 75% reduce 0% > 09/07/10 14:00:37 INFO mapred.JobClient: map 75% reduce 1% > 09/07/10 14:00:38 INFO mapred.JobClient: map 78% reduce 5% > 09/07/10 14:00:39 INFO mapred.JobClient: map 89% reduce 10% > 09/07/10 14:00:40 INFO mapred.JobClient: map 89% reduce 11% > 09/07/10 14:00:41 INFO mapred.JobClient: map 90% reduce 11% > 09/07/10 14:00:42 INFO mapred.JobClient: map 99% reduce 14% > 09/07/10 14:00:43 INFO mapred.JobClient: map 99% reduce 16% > 09/07/10 14:00:44 INFO mapred.JobClient: map 99% reduce 18% > 09/07/10 14:00:45 INFO mapred.JobClient: map 99% reduce 19% > 09/07/10 14:00:47 INFO mapred.JobClient: map 99% reduce 22% > 09/07/10 14:00:48 INFO mapred.JobClient: map 100% reduce 22% > 09/07/10 14:00:50 INFO mapred.JobClient: map 100% reduce 24% > 09/07/10 14:00:52 INFO mapred.JobClient: map 100% reduce 25% > 09/07/10 14:00:53 INFO mapred.JobClient: map 100% reduce 26% > 09/07/10 14:00:54 INFO mapred.JobClient: map 100% reduce 27% > 09/07/10 14:00:58 INFO mapred.JobClient: map 100% reduce 33% > 09/07/10 14:01:00 INFO mapred.JobClient: map 100% reduce 34% > 09/07/10 14:01:03 INFO mapred.JobClient: map 100% reduce 39% > 09/07/10 14:03:29 INFO mapred.JobClient: map 100% reduce 40% > 09/07/10 14:03:42 INFO mapred.JobClient: map 100% reduce 41% > 09/07/10 14:03:50 INFO mapred.JobClient: map 100% reduce 47% > 09/07/10 14:03:51 INFO mapred.JobClient: map 100% reduce 50% > 09/07/10 14:03:52 INFO mapred.JobClient: map 100% reduce 56% > 09/07/10 14:03:57 INFO mapred.JobClient: map 100% reduce 57% > 09/07/10 14:04:00 INFO mapred.JobClient: map 100% reduce 58% > 09/07/10 14:04:05 INFO mapred.JobClient: map 100% reduce 59% > 09/07/10 14:04:07 INFO mapred.JobClient: map 100% reduce 60% > 09/07/10 14:04:09 INFO mapred.JobClient: map 100% reduce 66% > 09/07/10 14:04:10 INFO mapred.JobClient: map 100% reduce 67% > 09/07/10 14:04:12 INFO mapred.JobClient: map 100% reduce 68% > 09/07/10 14:04:13 INFO mapred.JobClient: map 100% reduce 69% > 09/07/10 14:04:14 INFO mapred.JobClient: map 100% reduce 70% > 09/07/10 14:04:20 INFO mapred.JobClient: map 100% reduce 79% > 09/07/10 14:04:21 INFO mapred.JobClient: map 100% reduce 80% > 09/07/10 14:04:22 INFO mapred.JobClient: map 100% reduce 81% > 09/07/10 14:04:23 INFO mapred.JobClient: map 100% reduce 82% > 09/07/10 14:04:33 INFO mapred.JobClient: map 100% reduce 87% > 09/07/10 14:04:42 INFO mapred.JobClient: Task Id : attempt_200907101344_0002_m_000013_0, Status : FAILED > Too many fetch-failures > 09/07/10 14:04:44 INFO mapred.JobClient: map 93% reduce 87% > 09/07/10 14:04:50 INFO mapred.JobClient: map 100% reduce 87% > 09/07/10 14:05:06 INFO mapred.JobClient: map 100% reduce 93% > 09/07/10 14:05:36 INFO mapred.JobClient: map 100% reduce 94% > 09/07/10 14:06:17 INFO mapred.JobClient: Job complete: job_200907101344_0002 > 09/07/10 14:06:17 INFO mapred.JobClient: Counters: 17 > 09/07/10 14:06:17 INFO mapred.JobClient: File Systems > 09/07/10 14:06:17 INFO mapred.JobClient: HDFS bytes read=1077612760 > 09/07/10 14:06:17 INFO mapred.JobClient: HDFS bytes written=1077285377 > 09/07/10 14:06:17 INFO mapred.JobClient: Local bytes read=1083539214 > 09/07/10 14:06:17 INFO mapred.JobClient: Local bytes written=2167083496 > 09/07/10 14:06:17 INFO mapred.JobClient: Job Counters > 09/07/10 14:06:17 INFO mapred.JobClient: Launched reduce tasks=18 > 09/07/10 14:06:17 INFO mapred.JobClient: Rack-local map tasks=2 > 09/07/10 14:06:17 INFO mapred.JobClient: Launched map tasks=18 > 09/07/10 14:06:17 INFO mapred.JobClient: Data-local map tasks=15 > 09/07/10 14:06:17 INFO mapred.JobClient: Map-Reduce Framework > 09/07/10 14:06:17 INFO mapred.JobClient: Reduce input groups=102341 > 09/07/10 14:06:17 INFO mapred.JobClient: Combine output records=0 > 09/07/10 14:06:17 INFO mapred.JobClient: Map input records=102341 > 09/07/10 14:06:17 INFO mapred.JobClient: Reduce output records=102341 > 09/07/10 14:06:17 INFO mapred.JobClient: Map output bytes=1074564177 > 09/07/10 14:06:17 INFO mapred.JobClient: Map input bytes=1077284885 > 09/07/10 14:06:17 INFO mapred.JobClient: Combine input records=0 > 09/07/10 14:06:17 INFO mapred.JobClient: Map output records=102341 > 09/07/10 14:06:17 INFO mapred.JobClient: Reduce input records=102341 > Job ended: Fri Jul 10 14:06:17 IST 2009 > The job took 357 seconds. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.