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	<title>Comments on: Known applications of MapReduce</title>
	<atom:link href="http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/feed/" rel="self" type="application/rss+xml" />
	<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/</link>
	<description>Choices in data management and analysis</description>
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		<title>By: Confluence: Philip Zeyliger</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-118625</link>
		<dc:creator>Confluence: Philip Zeyliger</dc:creator>
		<pubDate>Sun, 26 Apr 2009 21:49:03 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-118625</guid>
		<description>&lt;strong&gt;Hadoop-MR Use Cases...&lt;/strong&gt;

I&#039;m trying to college known uses of Hadoop/GFS/MapReduce, and categorize them somewhat.&#160; When possible, citations are great.......</description>
		<content:encoded><![CDATA[<p><strong>Hadoop-MR Use Cases&#8230;</strong></p>
<p>I&#8217;m trying to college known uses of Hadoop/GFS/MapReduce, and categorize them somewhat.&nbsp; When possible, citations are great&#8230;&#8230;.</p>
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		<title>By: Winning with Data: Aster Data Systems Blog &#187; Blog Archive &#187; The Importance of Visibility Across Rows</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-117956</link>
		<dc:creator>Winning with Data: Aster Data Systems Blog &#187; Blog Archive &#187; The Importance of Visibility Across Rows</dc:creator>
		<pubDate>Wed, 22 Apr 2009 18:49:09 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-117956</guid>
		<description>[...] Examples abound. Consider a SQL/MR function which applies a complex model to score the data in the database, whether it&#8217;s scoring a customer for insurance risk, scoring an internet user for an ad&#8217;s effectiveness, or scoring a snippet of text for its sentiment. These functions often construct a data structure in memory to accelerate scoring, which works very well with the SQL/MR API: build the data structure once and reuse it across a large number of rows. [...]</description>
		<content:encoded><![CDATA[<p>[...] Examples abound. Consider a SQL/MR function which applies a complex model to score the data in the database, whether it&#8217;s scoring a customer for insurance risk, scoring an internet user for an ad&#8217;s effectiveness, or scoring a snippet of text for its sentiment. These functions often construct a data structure in memory to accelerate scoring, which works very well with the SQL/MR API: build the data structure once and reuse it across a large number of rows. [...]</p>
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	<item>
		<title>By: Infology.Ru &#187; Blog Archive &#187; Несколько тезисов о MapReduce</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-101097</link>
		<dc:creator>Infology.Ru &#187; Blog Archive &#187; Несколько тезисов о MapReduce</dc:creator>
		<pubDate>Mon, 03 Nov 2008 18:31:24 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-101097</guid>
		<description>[...] Три основных области применения MapReduce [...]</description>
		<content:encoded><![CDATA[<p>[...] Три основных области применения MapReduce [...]</p>
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	</item>
	<item>
		<title>By: Infology.Ru &#187; Blog Archive &#187; Три подхода к распараллеливанию процесса преобразования данных</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-98926</link>
		<dc:creator>Infology.Ru &#187; Blog Archive &#187; Три подхода к распараллеливанию процесса преобразования данных</dc:creator>
		<pubDate>Thu, 09 Oct 2008 20:36:37 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-98926</guid>
		<description>[...] «Темой Недели»: MapReduce. Когда я опубликовал список канонических приложений MapReduce, мои друзья из компании Aster Data предложили мне еще одно [...]</description>
		<content:encoded><![CDATA[<p>[...] «Темой Недели»: MapReduce. Когда я опубликовал список канонических приложений MapReduce, мои друзья из компании Aster Data предложили мне еще одно [...]</p>
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	<item>
		<title>By: Infology.Ru &#187; Blog Archive &#187; Почему MapReduce так важен для хранилищ данных?</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-98539</link>
		<dc:creator>Infology.Ru &#187; Blog Archive &#187; Почему MapReduce так важен для хранилищ данных?</dc:creator>
		<pubDate>Sun, 05 Oct 2008 06:59:11 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-98539</guid>
		<description>[...] По существу, вы можете сделать все, что угодно с одной записью* - это шаг map. Но вы сильно ограничены в том, как вы можете объединить информацию о многих (часто промежуточных) записях – это шаг reduce. Тем не менее, шаг reduce позволяет вам выполнять подсчет, суммирование и другие операции агрегирования. Сей факт, вкупе с универсальной мощью шагов map, делает MapReduce полезным, по меньшей мере, для трех важных классов приложений: [...]</description>
		<content:encoded><![CDATA[<p>[...] По существу, вы можете сделать все, что угодно с одной записью* &#8211; это шаг map. Но вы сильно ограничены в том, как вы можете объединить информацию о многих (часто промежуточных) записях – это шаг reduce. Тем не менее, шаг reduce позволяет вам выполнять подсчет, суммирование и другие операции агрегирования. Сей факт, вкупе с универсальной мощью шагов map, делает MapReduce полезным, по меньшей мере, для трех важных классов приложений: [...]</p>
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	<item>
		<title>By: Winning with Data: Aster Data Systems Blog &#187; Blog Archive &#187; MapReduce Educational Resources</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-97253</link>
		<dc:creator>Winning with Data: Aster Data Systems Blog &#187; Blog Archive &#187; MapReduce Educational Resources</dc:creator>
		<pubDate>Wed, 10 Sep 2008 15:45:30 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-97253</guid>
		<description>[...] If you are unable to attend, or eager to understand, here are some MapReduce resources you may find informative: Aster’s whitepaper on In-Database MapReduce; Google Labs’ MapReduce research paper; Curt Monash’s post on Known Applications of MapReduce. [...]</description>
		<content:encoded><![CDATA[<p>[...] If you are unable to attend, or eager to understand, here are some MapReduce resources you may find informative: Aster’s whitepaper on In-Database MapReduce; Google Labs’ MapReduce research paper; Curt Monash’s post on Known Applications of MapReduce. [...]</p>
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	<item>
		<title>By: MapReduce sound bites &#124; DBMS2 -- DataBase Management System Services</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-95948</link>
		<dc:creator>MapReduce sound bites &#124; DBMS2 -- DataBase Management System Services</dc:creator>
		<pubDate>Thu, 28 Aug 2008 18:47:19 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-95948</guid>
		<description>[...] Three major applications of MapReduce [...]</description>
		<content:encoded><![CDATA[<p>[...] Three major applications of MapReduce [...]</p>
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	<item>
		<title>By: Luke Lonergan</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-95945</link>
		<dc:creator>Luke Lonergan</dc:creator>
		<pubDate>Thu, 28 Aug 2008 17:13:59 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-95945</guid>
		<description>There is a coding tutorial available at this link in the middle of the page: http://www.greenplum.com/resources/mapreduce/

Key things to note about Greenplum&#039;s MR implementation:
- It&#039;s very similar in form and expression to Google and Hadoop
- Extensions for Joins and Pipelined task execution
- Native parallel file access
- Parallelism is full and transparent to the programmer

In summary: we have implemented MapReduce within which you can write SQL, Perl, Python and many more languages.  It is straightforward to use MR programs written for Hadoop or Google and port them to Greenplum.</description>
		<content:encoded><![CDATA[<p>There is a coding tutorial available at this link in the middle of the page: <a href="http://www.greenplum.com/resources/mapreduce/" onclick="javascript:pageTracker._trackPageview('/www.greenplum.com');" rel="nofollow">http://www.greenplum.com/resources/mapreduce/</a></p>
<p>Key things to note about Greenplum&#8217;s MR implementation:<br />
- It&#8217;s very similar in form and expression to Google and Hadoop<br />
- Extensions for Joins and Pipelined task execution<br />
- Native parallel file access<br />
- Parallelism is full and transparent to the programmer</p>
<p>In summary: we have implemented MapReduce within which you can write SQL, Perl, Python and many more languages.  It is straightforward to use MR programs written for Hadoop or Google and port them to Greenplum.</p>
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	<item>
		<title>By: The Great MapReduce Debate &#124; DBMS2 -- DataBase Management System Services</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-95914</link>
		<dc:creator>The Great MapReduce Debate &#124; DBMS2 -- DataBase Management System Services</dc:creator>
		<pubDate>Thu, 28 Aug 2008 02:46:04 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-95914</guid>
		<description>[...] Three major applications of MapReduce [...]</description>
		<content:encoded><![CDATA[<p>[...] Three major applications of MapReduce [...]</p>
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	<item>
		<title>By: Why MapReduce matters to SQL data warehousing &#124; DBMS2 -- DataBase Management System Services</title>
		<link>http://www.dbms2.com/2008/08/26/known-applications-of-mapreduce/comment-page-1/#comment-95868</link>
		<dc:creator>Why MapReduce matters to SQL data warehousing &#124; DBMS2 -- DataBase Management System Services</dc:creator>
		<pubDate>Wed, 27 Aug 2008 09:22:03 +0000</pubDate>
		<guid isPermaLink="false">http://www.dbms2.com/?p=500#comment-95868</guid>
		<description>[...] Three major applications of MapReduce [...]</description>
		<content:encoded><![CDATA[<p>[...] Three major applications of MapReduce [...]</p>
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