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	<title><![CDATA[mapreduce Resources | ZDNet]]></title>
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	<description><![CDATA[White papers, case studies, technical articles, and blog posts relating to mapreduce]]></description>
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		<title><![CDATA[MapScale: A Cloud Environment for Scientific Computing]]></title>
		<link><![CDATA[http://whitepapers.zdnet.com/abstract.aspx?docid=1188555]]></link>
		<description><![CDATA[Parallel programming languages have sought out many different means by which many numbers of cores can be utilized for a common goal. Programming languages such as MPI provide a low-level, message passing system, while others such as UPC provide a high-level, shared memory model. Both of these languages and many...]]></description>
		<s:doctype><![CDATA[White papers]]></s:doctype>
		<pubDate>Fri, 12 Jun 2009 00:00:00 -0700</pubDate>
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		<title><![CDATA[Amazon launches Hadoop data crunching service]]></title>
		<link><![CDATA[http://talkback.zdnet.com/5208-10532-0.html?forumID=1&threadID=62806&messageID=1160014&start=0]]></link>
		<description><![CDATA[Amazon launches Hadoop data crunching serviceMaking MapReduce MainstreamHadoop is great for teams of developers to crunch data. However, the "tipping point" in bringing the value of MapReduce to companies is by providing enterprise-class database features such as security, tight SQL integration, and more. Aster Data offers nCluster on the Amazon...]]></description>
		<s:doctype><![CDATA[Discussion threads]]></s:doctype>
		<pubDate>Thu, 02 Apr 2009 08:42:00 -0700</pubDate>
		<category domain="http://updates.zdnet.com/tags/databases.html"><![CDATA[Databases]]></category>
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		<category domain="http://rss.financialcontent.com/stocksymbol">AMZN</category>
		<category domain="tickers">AMZN</category>
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		<title><![CDATA[A technical look at how parallel processing brings vast new capabilities to large-scale BI and data analysis]]></title>
		<link><![CDATA[http://blogs.zdnet.com/Gardner/?p=2770]]></link>
		<description><![CDATA[The core problem we've solved is the ability for our engine to redistribute the data and the computation on the fly, as these queries and analysis are being performed. ... The combination of the software-switch interconnect, which Greenplum built into the Greenplum product, and the underlying use of commodity parallel...]]></description>
		<s:doctype><![CDATA[Blog posts]]></s:doctype>
		<pubDate>Mon, 05 Jan 2009 15:12:18 -0800</pubDate>
		<category domain="http://updates.zdnet.com/tags/business+intelligence.html"><![CDATA[Business Intelligence]]></category>
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		<category domain="http://updates.zdnet.com/tags/dana+gardner.html"><![CDATA[Dana Gardner]]></category>
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		<title><![CDATA[Greenplum pushes envelope with MapReduce and parallelism enhancements to its extreme-scale data offering]]></title>
		<link><![CDATA[http://talkback.zdnet.com/5208-11475-0.html?forumID=1&threadID=52478&messageID=989614&start=0]]></link>
		<description><![CDATA[Greenplum pushes envelope with MapReduce and parallelism enhancements to its extreme-scale data offeringMapReduce overviewFor those who are interested in MapReduce in relation to a RDBMS I have an overview here http://blog.tonybain.com/tony_bain/2008/09/what-is-mapreduce.html]]></description>
		<s:doctype><![CDATA[Discussion threads]]></s:doctype>
		<pubDate>Mon, 29 Sep 2008 13:51:00 -0700</pubDate>
		<category domain="http://updates.zdnet.com/tags/mapreduce.html"><![CDATA[MapReduce]]></category>
		<category domain="http://updates.zdnet.com/tags/parallelism+enhancement.html"><![CDATA[parallelism enhancement]]></category>
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		<title><![CDATA[Greenplum pushes envelope with MapReduce and parallelism enhancements to its extreme-scale data offering]]></title>
		<link><![CDATA[http://blogs.zdnet.com/Gardner/?p=2737]]></link>
		<description><![CDATA[It seems that data infrastructure vendors are rushing to the realization that older database architectures have hit a wall in terms of scale and performance. The general solution favors exploiting parallelism to the hilt and aligning database and logic functions in close proximity, while also exploiting MapReduce approaches to provide...]]></description>
		<s:doctype><![CDATA[Blog posts]]></s:doctype>
		<pubDate>Mon, 29 Sep 2008 06:50:49 -0700</pubDate>
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		<category domain="http://rss.financialcontent.com/stocksymbol">ORCL</category>
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		<title><![CDATA[Databases leverage MapReduce technology to radically juice data scale, performance, analytics]]></title>
		<link><![CDATA[http://talkback.zdnet.com/5208-11475-0.html?forumID=1&threadID=51327&messageID=963811&start=0]]></link>
		<description><![CDATA[Databases leverage MapReduce technology to radically juice data scale, performance, analyticsAster In-Database MapReduce Available NowDana - great article – thanks for covering this. Many agree this is a game-changing innovation for the database industry. I'd just like to point out:  [1] Aster In-Database MapReduce is available now for evaluation...]]></description>
		<s:doctype><![CDATA[Discussion threads]]></s:doctype>
		<pubDate>Wed, 27 Aug 2008 11:10:00 -0700</pubDate>
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		<title><![CDATA[Databases leverage MapReduce technology to radically juice data scale, performance, analytics]]></title>
		<link><![CDATA[http://blogs.zdnet.com/Gardner/?p=2718]]></link>
		<description><![CDATA[With better data reach and inclusion, come better results. So BI allows leaders can establish the trends early that will determine their future success or failures. In a fast-paced, global, hyper competitive business landscape these insights are the currency of success for the future. The better you do BI, the...]]></description>
		<s:doctype><![CDATA[Blog posts]]></s:doctype>
		<pubDate>Wed, 27 Aug 2008 09:18:34 -0700</pubDate>
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		<title><![CDATA[Google's parallel programming model]]></title>
		<link><![CDATA[http://blogs.zdnet.com/emergingtech/?p=803]]></link>
		<description><![CDATA[Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day on commodity-based clusters. The latest statistics included in the paper are from September 2007. They show that...]]></description>
		<s:doctype><![CDATA[Blog posts]]></s:doctype>
		<pubDate>Mon, 14 Jan 2008 09:17:06 -0800</pubDate>
		<category domain="http://updates.zdnet.com/tags/google+inc..html"><![CDATA[Google Inc.]]></category>
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		<category domain="http://rss.financialcontent.com/stocksymbol">GOOG</category>
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		<title><![CDATA[A Grid Based System for Data Mining Using MapReduce]]></title>
		<link><![CDATA[http://whitepapers.zdnet.com/abstract.aspx?docid=388765]]></link>
		<description><![CDATA[This paper discusses a Grid data mining system based on the MapReduce paradigm of computing. The MapReduce paradigm emphasizes system automation of fault tolerance and redundancy, while keeping the programming model for the user very simple. MapReduce is built closely on top of a distributed file system that allows efficient...]]></description>
		<s:doctype><![CDATA[White papers]]></s:doctype>
		<pubDate>Tue, 17 Jul 2007 00:00:00 -0700</pubDate>
		<category domain="http://updates.zdnet.com/tags/university+of+puerto+rico.html"><![CDATA[University Of Puerto Rico]]></category>
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		<title><![CDATA[Google's secret of success? Dealing with failure]]></title>
		<link><![CDATA[http://talkback.zdnet.com/5208-9588-0.html?forumID=1&threadID=8636&messageID=173705&start=0]]></link>
		<description><![CDATA[Google's secret of success? Dealing with failureI wonder what they use for the desktopIs it linux or MS?Smart Idea!Develop and test on what the average person uses.  What a concept!Downloadable links for GFS and Mapreduce papersThe USENIX links require a current USENIX account to download the actual paper, but...]]></description>
		<s:doctype><![CDATA[Discussion threads]]></s:doctype>
		<pubDate>Thu, 03 Mar 2005 05:17:00 -0800</pubDate>
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