Return-Path: Delivered-To: apmail-hadoop-hdfs-issues-archive@minotaur.apache.org Received: (qmail 24397 invoked from network); 13 Apr 2010 17:41:41 -0000 Received: from unknown (HELO mail.apache.org) (140.211.11.3) by 140.211.11.9 with SMTP; 13 Apr 2010 17:41:41 -0000 Received: (qmail 68997 invoked by uid 500); 13 Apr 2010 17:41:41 -0000 Delivered-To: apmail-hadoop-hdfs-issues-archive@hadoop.apache.org Received: (qmail 68907 invoked by uid 500); 13 Apr 2010 17:41:41 -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 68887 invoked by uid 99); 13 Apr 2010 17:41:40 -0000 Received: from athena.apache.org (HELO athena.apache.org) (140.211.11.136) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 13 Apr 2010 17:41:40 +0000 X-ASF-Spam-Status: No, hits=-1278.1 required=10.0 tests=ALL_TRUSTED,AWL X-Spam-Check-By: apache.org Received: from [140.211.11.22] (HELO thor.apache.org) (140.211.11.22) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 13 Apr 2010 17:41:40 +0000 Received: from thor (localhost [127.0.0.1]) by thor.apache.org (8.13.8+Sun/8.13.8) with ESMTP id o3DHfJ8G023116 for ; Tue, 13 Apr 2010 13:41:19 -0400 (EDT) Message-ID: <27084347.51281271180479324.JavaMail.jira@thor> Date: Tue, 13 Apr 2010 13:41:19 -0400 (EDT) From: "Karthik Ranganathan (JIRA)" To: hdfs-issues@hadoop.apache.org Subject: [jira] Commented: (HDFS-1094) Intelligent block placement policy to decrease probability of block loss In-Reply-To: <24967451.18401271056063147.JavaMail.jira@thor> MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/HDFS-1094?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12856510#action_12856510 ] Karthik Ranganathan commented on HDFS-1094: ------------------------------------------- Hey Brian, Yes, that would help with the data loss case but has some unfortunate side effects: 1. Data availability would be reduced - cannot access the data at all on inter-rack switch failure. 2. It would cause the data to be very unevenly distributed across the various racks. Another workaround for this is to have many smaller clusters instead of one large cluster, but that becomes a maintenance nightmare (operationally), and the application above should balance the data across these clusters. > Intelligent block placement policy to decrease probability of block loss > ------------------------------------------------------------------------ > > Key: HDFS-1094 > URL: https://issues.apache.org/jira/browse/HDFS-1094 > Project: Hadoop HDFS > Issue Type: Improvement > Components: name-node > Reporter: dhruba borthakur > Assignee: dhruba borthakur > > The current HDFS implementation specifies that the first replica is local and the other two replicas are on any two random nodes on a random remote rack. This means that if any three datanodes die together, then there is a non-trivial probability of losing at least one block in the cluster. This JIRA is to discuss if there is a better algorithm that can lower probability of losing a block. -- This message is automatically generated by JIRA. - If you think it was sent incorrectly contact one of the administrators: https://issues.apache.org/jira/secure/Administrators.jspa - For more information on JIRA, see: http://www.atlassian.com/software/jira