Hello Ashish,
Alexander reference is great. Adding to that, you can also find latest Hadoop
docker image from below
https://registry.hub.docker.com/u/sequenceiq/hadoop-docker/
Set up is as simple as that
1. Install Docker
2. Build and Pull above Image
3. Start Container (if any errors, let us know)
Hope it helps!!!
Thanks and Regards,
S.RagavendraGanesh
Hadoop Support Team
ViSolve Inc.| <http://www.visolve.com/> www.visolve.com
From: Alexander Alten-Lorenz [mailto:wget.n...@gmail.com]
Sent: Monday, February 02, 2015 3:07 PM
To: user@hadoop.apache.org
Cc: Harun Rešit Zafer
Subject: Re: Multiple separate Hadoop clusters on same physical machines
http://blog.sequenceiq.com/blog/2014/06/19/multinode-hadoop-cluster-on-docker/
Ambari based, but works quite well
On 02 Feb 2015, at 10:33, Ashish Kumar9 <ashis...@in.ibm.com
<mailto:ashis...@in.ibm.com> > wrote:
Is there any good reference material available to follow to test docker and
hadoop integration .
From: <hadoop.supp...@visolve.com <mailto:hadoop.supp...@visolve.com> >
To: "'Harun Reşit Zafer'" <harun.za...@tubitak.gov.tr
<mailto:harun.za...@tubitak.gov.tr> >, <user@hadoop.apache.org
<mailto:user@hadoop.apache.org> >
Date: 02/02/2015 02:57 PM
Subject: RE: Multiple separate Hadoop clusters on same physical machines
_____
Hello Harun,
Your question is very interesting and will be useful for future Hadoop setups
for startup/individuals too.
Normally for testing purposes, we prefer you to use pseudo-distributed
environments (i.e. installation of all cluster files in single node). You can
refer few links which will guide you through the whole process below for
reference:
<https://districtdatalabs.silvrback.com/creating-a-hadoop-pseudo-distributed-environment>
https://districtdatalabs.silvrback.com/creating-a-hadoop-pseudo-distributed-environment
Individual Pseudo Distributed Cluster Implementation:
<http://www.thegeekstuff.com/2012/02/hadoop-pseudo-distributed-installation/>
http://www.thegeekstuff.com/2012/02/hadoop-pseudo-distributed-installation/
<http://hbase.apache.org/book.html#quickstart_pseudo>
http://hbase.apache.org/book.html#quickstart_pseudo
and please check for others.
>From our 20 years of Server & its related Industrial experience, we recommend
>you to use VM/Instances for production & Business Critical environment. Other
>way around, if you are developing some products related to Hadoop, you can use
>docker & other related resources for development. As shipment to production
>will become stress free with the use of these tools with cluster environment
>setup.
Feel free to ask for further queries.
Thanks and Regards,
S.RagavendraGanesh
Hadoop Support Team
ViSolve Inc.| <http://www.visolve.com/> www.visolve.com
From: Alexander Pivovarov [ <mailto:apivova...@gmail.com>
mailto:apivova...@gmail.com]
Sent: Monday, February 02, 2015 12:56 PM
To: user@hadoop.apache.org <mailto:user@hadoop.apache.org>
Subject: Re: Multiple separate Hadoop clusters on same physical machines
start several vms and install hadoop on each vm
keywords: kvm, QEMU
On Mon, Jan 26, 2015 at 1:18 AM, Harun Reşit Zafer <harun.za...@tubitak.gov.tr
<mailto:harun.za...@tubitak.gov.tr> > wrote:
Hi everyone,
We have set up and been playing with Hadoop 1.2.x and its friends (Hbase, pig,
hive etc.) on 7 physical servers. We want to test Hadoop (maybe different
versions) and ecosystem on physical machines (virtualization is not an option)
from different perspectives.
As a bunch of developer we would like to work in parallel. We want every team
member play with his/her own cluster. However we have limited amount of servers
(strong machines though).
So the question is, by changing port numbers, environment variables and other
configuration parameters, is it possible to setup several independent clusters
on same physical machines. Is there any constraints? What are the possible
difficulties we are to face?
Thanks in advance
--
Harun Reşit Zafer
TÜBİTAK BİLGEM BTE
Bulut Bilişim ve Büyük Veri Analiz Sistemleri Bölümü
T +90 262 675 3268 <tel:%2B90%20262%20675%203268>
W http://www.hrzafer.com <http://www.hrzafer.com/>
