Return-Path: X-Original-To: apmail-hadoop-mapreduce-user-archive@minotaur.apache.org Delivered-To: apmail-hadoop-mapreduce-user-archive@minotaur.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id 2F070DE03 for ; Fri, 25 Jan 2013 09:18:35 +0000 (UTC) Received: (qmail 532 invoked by uid 500); 25 Jan 2013 09:18:30 -0000 Delivered-To: apmail-hadoop-mapreduce-user-archive@hadoop.apache.org Received: (qmail 424 invoked by uid 500); 25 Jan 2013 09:18:30 -0000 Mailing-List: contact user-help@hadoop.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: user@hadoop.apache.org Delivered-To: mailing list user@hadoop.apache.org Received: (qmail 363 invoked by uid 99); 25 Jan 2013 09:18:29 -0000 Received: from nike.apache.org (HELO nike.apache.org) (192.87.106.230) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 25 Jan 2013 09:18:29 +0000 X-ASF-Spam-Status: No, hits=1.5 required=5.0 tests=HTML_MESSAGE,RCVD_IN_DNSWL_LOW,SPF_PASS X-Spam-Check-By: apache.org Received-SPF: pass (nike.apache.org: domain of balijamahesh.mca@gmail.com designates 209.85.217.175 as permitted sender) Received: from [209.85.217.175] (HELO mail-lb0-f175.google.com) (209.85.217.175) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 25 Jan 2013 09:18:21 +0000 Received: by mail-lb0-f175.google.com with SMTP id n3so325199lbo.20 for ; Fri, 25 Jan 2013 01:18:00 -0800 (PST) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20120113; h=mime-version:x-received:in-reply-to:references:date:message-id :subject:from:to:content-type; bh=Bb1kvJozQWjxrpHNXORS+C2yL8IyD4OaCers7tymHlQ=; b=TxCmtH8vI810NuUzY0+hhz9CJ4h7ElojdsAoTIvJwQNz48/jqQno/qqR7pyO5iSVmz e8IjpnDF92qRDq45Dm0aW1jLN70viUVG6EtnZQq2D4cIuRlNOVvN6eIbYT8ibAW7KAkm p+wD28rdrN2/ltlBI3vVxRf0hmvOxYk4s5bi+dxAsUAHevaMaGcBz54e11nmHr5cAq0n FaJ2XUqkBW1xjfFfLg1lh6L4RjGzZSk87HNmEvfNzUkG8yukGr82SqxFDr6garcgP5Bc pe2HqG04nsEDMN7v7VJ6of2wXIaAijyQPk+ZFxNSzQNn/GJ8G3cCFPzchIYZmppW7M++ X4zw== MIME-Version: 1.0 X-Received: by 10.112.82.202 with SMTP id k10mr1962941lby.22.1359105480587; Fri, 25 Jan 2013 01:18:00 -0800 (PST) Received: by 10.112.74.198 with HTTP; Fri, 25 Jan 2013 01:18:00 -0800 (PST) In-Reply-To: References: Date: Fri, 25 Jan 2013 14:48:00 +0530 Message-ID: Subject: Re: mappers-node relationship From: Mahesh Balija To: user@hadoop.apache.org Content-Type: multipart/alternative; boundary=bcaec555540261fbe204d41967fb X-Virus-Checked: Checked by ClamAV on apache.org --bcaec555540261fbe204d41967fb Content-Type: text/plain; charset=ISO-8859-1 Mappers and Reducers will run in Task instances mapper/reducer instances also called as mapper/reducer slots. Each node can have multiple slots (I mean multiple mapper instances, each run in a child JVM). And this is configurable with properties like mapred.tasktracker.map.tasks.maximum and mapred.tasktracker.reduce.tasks.maximum. Also they run in parallel. Best, Mahesh Balija, CalsoftLabs. On Fri, Jan 25, 2013 at 1:16 PM, jamal sasha wrote: > Hi. > A very very lame question. > Does numbers of mapper depends on the number of nodes I have? > How I imagine map-reduce is this. > For example in word count example > I have bunch of slave nodes. > The documents are distributed across these slave nodes. > Now depending on how big the data is, it will spread across the slave > nodes.. and that is how my number of mappers are decided. > I am sure, this is wrong understanding. As in pseudo-distributed node, i > can see multiple mappers. > So question is.. how does a single node machine runs multiple mappers? is > it run in parallel or sequentially?? > Any resources to learn these > Thanks > --bcaec555540261fbe204d41967fb Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable Mappers and Reducers will run in Task instances mapper/reducer instances al= so called as mapper/reducer slots.
Each node can have multiple slots (I = mean multiple mapper instances, each run in a child JVM). And this is confi= gurable with properties like mapred.tasktracker.map.tasks.maximum and mapre= d.tasktracker.reduce.tasks.maximum.
Also they run in parallel.

Best,
Mahesh Balija,
CalsoftLabs.<= br>


On Fri, Jan 25, 2013 at 1:16 PM, = jamal sasha <jamalshasha@gmail.com> wrote:
Hi.
=A0 A very very lam= e question.
Does numbers of mapper depends on the number of nodes= I have?
How I imagine map-reduce is this.
For example in word count = example
I have bunch of slave nodes.
The documents are distributed a= cross these slave nodes.
Now depending on how big the data is, it= will spread across the slave nodes.. and that is how my number of mappers = are decided.
I am sure, this is wrong understanding. As in pseudo-distributed node,= i can see multiple mappers.
So question is.. how does a single n= ode machine runs multiple mappers? is it run in parallel or sequentially??<= /div>
Any resources to learn these
Thanks

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