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From Apache Wiki <wikidi...@apache.org>
Subject [Hadoop Wiki] Update of "PoweredBy" by SomeOtherAccount
Date Thu, 08 Sep 2011 23:27:21 GMT
Dear Wiki user,

You have subscribed to a wiki page or wiki category on "Hadoop Wiki" for change notification.

The "PoweredBy" page has been changed by SomeOtherAccount:

spam removal and some other small fixes

  This page documents an alphabetical list of institutions that are using Hadoop for educational
or production uses. Companies that offer services on or based around Hadoop are listed in
[[Distributions and Commercial Support]] .
+ ''When applicable, please include details about your cluster hardware and size.''
@@ -20, +22 @@

    * We use Hadoop and HBase in several areas from social services to structured data storage
and processing for internal use.
    * We currently have about 30 nodes running HDFS, Hadoop and HBase in clusters ranging
from 5 to 14 nodes on both production and development. We plan a deployment on an 80 nodes
    * We constantly write data to HBase and run MapReduce jobs to process then store it back
to HBase or external systems.
    * Our production cluster has been running since Oct 2008.
   * [[http://www.adyard.de|adyard]]
@@ -281, +282 @@

    * 30 node AWS EC2 cluster (varying instance size, currently EBS-backed) managed by Chef
& Poolparty running Hadoop 0.20.2+228, Pig 0.5.0+30, Azkaban 0.04, [[http://github.com/infochimps/wukong|Wukong]]
    * Used for ETL & data analysis on terascale datasets, especially social network data
(on [[http://api.infochimps.com|api.infochimps.com]])
-  * [[http://www.blackpatroner.eu|Bl├Ąckpatroner CO]]
   * [[http://www.iterend.com/|Iterend]]
    * using 10 node hdfs cluster to store and process retrieved data on.
@@ -321, +321 @@

    * HBase & Hadoop version 0.20
   * [[http://www.legolas-media.com|Legolas Media]]
-  * [[http://www.vittleende.se|Tandblekning CO]]
   * [[http://www.linkedin.com|LinkedIn]]
    * We have multiple grids divided up based upon purpose. They are composed of the following
types of hardware:
@@ -628, +627 @@

    * 10 node cluster (Dual-Core AMD Opteron 2210, 4GB RAM, 1TB/node storage)
    * Run Naive Bayes classifiers in parallel over crawl data to discover event information
- ''When applicable, please include details about your cluster hardware and size.''

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