Return-Path: X-Original-To: archive-asf-public-internal@cust-asf2.ponee.io Delivered-To: archive-asf-public-internal@cust-asf2.ponee.io Received: from cust-asf.ponee.io (cust-asf.ponee.io [163.172.22.183]) by cust-asf2.ponee.io (Postfix) with ESMTP id 3237E200B62 for ; Fri, 29 Jul 2016 00:24:22 +0200 (CEST) Received: by cust-asf.ponee.io (Postfix) id 30CB0160AA9; Thu, 28 Jul 2016 22:24:22 +0000 (UTC) Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by cust-asf.ponee.io (Postfix) with SMTP id 7768F160A85 for ; Fri, 29 Jul 2016 00:24:21 +0200 (CEST) Received: (qmail 37990 invoked by uid 500); 28 Jul 2016 22:24:20 -0000 Mailing-List: contact commits-help@cassandra.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@cassandra.apache.org Delivered-To: mailing list commits@cassandra.apache.org Received: (qmail 37970 invoked by uid 99); 28 Jul 2016 22:24:20 -0000 Received: from arcas.apache.org (HELO arcas) (140.211.11.28) by apache.org (qpsmtpd/0.29) with ESMTP; Thu, 28 Jul 2016 22:24:20 +0000 Received: from arcas.apache.org (localhost [127.0.0.1]) by arcas (Postfix) with ESMTP id 7E1132C0D5F for ; Thu, 28 Jul 2016 22:24:20 +0000 (UTC) Date: Thu, 28 Jul 2016 22:24:20 +0000 (UTC) From: "sankalp kohli (JIRA)" To: commits@cassandra.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Updated] (CASSANDRA-10643) Implement compaction for a specific token range MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 archived-at: Thu, 28 Jul 2016 22:24:22 -0000 [ https://issues.apache.org/jira/browse/CASSANDRA-10643?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] sankalp kohli updated CASSANDRA-10643: -------------------------------------- Reviewer: (was: Jason Brown) Description: We see repeated cases in production (using LCS) where small number of users generate a large number repeated updates or tombstones. Reading data of such users brings in large amounts of data in to java process. Apart from the read itself being slow for the user, the excessive GC affects other users as well. Our solution so far is to move from LCS to SCS and back. This takes long and is an over kill if the number of outliers is small. For such cases, we can implement the point compaction of a token range. We make the nodetool compact take a starting and ending token range and compact all the SSTables that fall with in that range. We can refuse to compact if the number of sstables is beyond a max_limit. Example: nodetool -st 3948291562518219268 -et 3948291562518219269 compact keyspace table was: We see repeated cases in production (using LCS) where small number of users generate a large number repeated updates or tombstones. Reading data of such users brings in large amounts of data in to java process. Apart from the read itself being slow for the user, the excessive GC affects other users as well. Our solution so far is to move from LCS to SCS and back. This takes long and is an over kill if the number of outliers is small. For such cases, we can implement the point compaction of a token range. We make the nodetool compact take a starting and ending token range and compact all the SSTables that fall with in that range. We can refuse to compact if the number of sstables is beyond a max_limit. Example: nodetool -st 3948291562518219268 -et 3948291562518219269 compact keyspace table > Implement compaction for a specific token range > ----------------------------------------------- > > Key: CASSANDRA-10643 > URL: https://issues.apache.org/jira/browse/CASSANDRA-10643 > Project: Cassandra > Issue Type: Improvement > Components: Compaction > Reporter: Vishy Kasar > Assignee: Vishy Kasar > Labels: lcs > Attachments: 10643-trunk-REV01.txt > > > We see repeated cases in production (using LCS) where small number of users generate a large number repeated updates or tombstones. Reading data of such users brings in large amounts of data in to java process. Apart from the read itself being slow for the user, the excessive GC affects other users as well. > Our solution so far is to move from LCS to SCS and back. This takes long and is an over kill if the number of outliers is small. For such cases, we can implement the point compaction of a token range. We make the nodetool compact take a starting and ending token range and compact all the SSTables that fall with in that range. We can refuse to compact if the number of sstables is beyond a max_limit. > Example: > nodetool -st 3948291562518219268 -et 3948291562518219269 compact keyspace table -- This message was sent by Atlassian JIRA (v6.3.4#6332)