Return-Path: Delivered-To: apmail-hadoop-core-user-archive@www.apache.org Received: (qmail 26910 invoked from network); 29 Feb 2008 05:55:45 -0000 Received: from hermes.apache.org (HELO mail.apache.org) (140.211.11.2) by minotaur.apache.org with SMTP; 29 Feb 2008 05:55:45 -0000 Received: (qmail 99484 invoked by uid 500); 29 Feb 2008 05:55:39 -0000 Delivered-To: apmail-hadoop-core-user-archive@hadoop.apache.org Received: (qmail 99443 invoked by uid 500); 29 Feb 2008 05:55:39 -0000 Mailing-List: contact core-user-help@hadoop.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: core-user@hadoop.apache.org Delivered-To: mailing list core-user@hadoop.apache.org Received: (qmail 99433 invoked by uid 99); 29 Feb 2008 05:55:39 -0000 Received: from nike.apache.org (HELO nike.apache.org) (192.87.106.230) by apache.org (qpsmtpd/0.29) with ESMTP; Thu, 28 Feb 2008 21:55:39 -0800 X-ASF-Spam-Status: No, hits=1.2 required=10.0 tests=SPF_NEUTRAL X-Spam-Check-By: apache.org Received-SPF: neutral (nike.apache.org: local policy) Received: from [216.145.54.173] (HELO mrout3.yahoo.com) (216.145.54.173) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 29 Feb 2008 05:54:49 +0000 Received: from SNV-EXPF01.ds.corp.yahoo.com (snv-expf01.ds.corp.yahoo.com [207.126.227.250]) by mrout3.yahoo.com (8.13.6/8.13.6/y.out) with ESMTP id m1T5sifs024499 for ; Thu, 28 Feb 2008 21:54:44 -0800 (PST) DomainKey-Signature: a=rsa-sha1; s=serpent; d=yahoo-inc.com; c=nofws; q=dns; h=received:x-mimeole:content-class:mime-version: content-type:content-transfer-encoding:subject:date:message-id: in-reply-to:x-ms-has-attach:x-ms-tnef-correlator:thread-topic: thread-index:references:from:to:return-path:x-originalarrivaltime; b=2lX+RuIJ7yGg+KgC91UEeEvInYXIsuhr+pzBb2fSPBQMxe8CcHrW1DYFySYMmzcW Received: from SNV-EXVS08.ds.corp.yahoo.com ([207.126.227.8]) by SNV-EXPF01.ds.corp.yahoo.com with Microsoft SMTPSVC(6.0.3790.3959); Thu, 28 Feb 2008 21:54:44 -0800 X-MimeOLE: Produced By Microsoft Exchange V6.5 Content-class: urn:content-classes:message MIME-Version: 1.0 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable Subject: RE: long write operations and data recovery Date: Thu, 28 Feb 2008 21:53:59 -0800 Message-ID: <84E52AD05F6F884AAFF3344FE4C95991011E5DB4@SNV-EXVS08.ds.corp.yahoo.com> In-Reply-To: X-MS-Has-Attach: X-MS-TNEF-Correlator: Thread-Topic: long write operations and data recovery Thread-Index: Ach6bdEUYVT+s7naT6yc45AquJDsngABy2igAAhvs3A= References: <47C757C5.5040403@invitemedia.com> From: "dhruba Borthakur" To: X-OriginalArrivalTime: 29 Feb 2008 05:54:44.0767 (UTC) FILETIME=[958BB2F0:01C87A97] X-Virus-Checked: Checked by ClamAV on apache.org I agree with Joydeep. For batch processing, it is sufficient to make the application not assume that HDFS is always up and active. However, for real-time applications that are not batch-centric, it might not be sufficient. There are a few things that HDFS could do to better handle Namenode outages: 1. Make Clients handle transient Namenode downtime. This requires that Namenode restarts are fast, clients can handle long Namenode outages, etc.etc. 2. Design HDFS Namenode to be a set of two, an active one and a passive one. The active Namenode could continuously forward transactions to the passive one. In case of failure of the active Namenode, the passive could take over. This type of High-Availability would probably be very necessary for non-batch-type-applications. Thanks, dhruba -----Orivery necessaginal Message----- From: Joydeep Sen Sarma [mailto:jssarma@facebook.com]=20 Sent: Thursday, February 28, 2008 6:06 PM To: core-user@hadoop.apache.org Subject: RE: long write operations and data recovery We have had a lot of peace of mind by building a data pipeline that does not assume that hdfs is always up and running. If the application is primarily non real-time log processing - I would suggest batch/incremental copies of data to hdfs that can catch up automatically in case of failures/downtimes. we have a rsync like map-reduce job that monitors a log directories and keeps pulling new data in (and suspect lot of other users do similar stuff as well). Might be a useful notion to generalize and put in contrib. -----Original Message----- From: Steve Sapovits [mailto:ssapovits@invitemedia.com]=20 Sent: Thursday, February 28, 2008 4:54 PM To: core-user@hadoop.apache.org Subject: Re: long write operations and data recovery > How does replication affect this? If there's at least one replicated > client still running, I assume that takes care of it? Never mind -- I get this now after reading the docs again. My remaining point of failure question concerns name nodes. The docs say manual=20 intervention is still required if a name node goes down. How is this typically managed in production environments? It would seem even a short name node outage in a=20 data intestive environment would lead to data loss (no name node to give the data to). --=20 Steve Sapovits Invite Media - http://www.invitemedia.com ssapovits@invitemedia.com