Comments for Data Beta http://databeta.wordpress.com on computing and data .. in permanent beta Wed, 21 Oct 2009 05:02:21 +0000 http://wordpress.com/ hourly 1 Comment on MapReduce Online! (and some gimmes) by jmh http://databeta.wordpress.com/2009/10/18/mapreduce-online/#comment-104 jmh Wed, 21 Oct 2009 05:02:21 +0000 http://databeta.wordpress.com/?p=206#comment-104 More coverage in <a href="http://radar.oreilly.com/2009/10/pipelining-and-real-time-analytics-with-mapreduce-online.html" rel="nofollow">O'Reilly Radar</a> More coverage in O’Reilly Radar

]]> Comment on MapReduce Online! (and some gimmes) by MapReduce Online Comes Out! | The Chung Lab. http://databeta.wordpress.com/2009/10/18/mapreduce-online/#comment-103 MapReduce Online Comes Out! | The Chung Lab. Tue, 20 Oct 2009 02:16:35 +0000 http://databeta.wordpress.com/?p=206#comment-103 [...] who is a Ph.D student in UC Berkeley accomplishes MapReduce Online. Today, I heard this news from Data Beta. Actually, It is amazing works since the original MapReduce is specialized and designed for only [...] [...] who is a Ph.D student in UC Berkeley accomplishes MapReduce Online. Today, I heard this news from Data Beta. Actually, It is amazing works since the original MapReduce is specialized and designed for only [...]

]]> Comment on MapReduce Online! (and some gimmes) by Top Posts « WordPress.com http://databeta.wordpress.com/2009/10/18/mapreduce-online/#comment-102 Top Posts « WordPress.com Tue, 20 Oct 2009 00:43:38 +0000 http://databeta.wordpress.com/?p=206#comment-102 [...] MapReduce Online! (and some gimmes) Hadoop MapReduce is a batch-processing system.  Why?  Because that’s the way Google described their MapReduce [...] [...] [...] MapReduce Online! (and some gimmes) Hadoop MapReduce is a batch-processing system.  Why?  Because that’s the way Google described their MapReduce [...] [...]

]]> Comment on MapReduce Online! (and some gimmes) by Interesting enhancements to MapReduce « Hans Gilde’s weblog http://databeta.wordpress.com/2009/10/18/mapreduce-online/#comment-101 Interesting enhancements to MapReduce « Hans Gilde’s weblog Mon, 19 Oct 2009 16:28:00 +0000 http://databeta.wordpress.com/?p=206#comment-101 [...] 19, 2009 Interesting paper about changes to M-R, in part to enable online processing. Ideas like pipelining and better [...] [...] 19, 2009 Interesting paper about changes to M-R, in part to enable online processing. Ideas like pipelining and better [...]

]]> Comment on MapReduce Online! (and some gimmes) by MapReduce Onlie Comes Out! | Dive into A Data Deluge http://databeta.wordpress.com/2009/10/18/mapreduce-online/#comment-100 MapReduce Onlie Comes Out! | Dive into A Data Deluge Mon, 19 Oct 2009 15:50:02 +0000 http://databeta.wordpress.com/?p=206#comment-100 [...] who is a Ph.D student in UC Berkeley, accomplishes MapReduce Online. Today, I heard this news from Data Beta. Actually, It is amazing works since the original MapReduce is specialized and designed for only [...] [...] who is a Ph.D student in UC Berkeley, accomplishes MapReduce Online. Today, I heard this news from Data Beta. Actually, It is amazing works since the original MapReduce is specialized and designed for only [...]

]]> Comment on MapReduce Online! (and some gimmes) by The 30 hottest webdesign-related links on the web « Adrian Zyzik's Weblog http://databeta.wordpress.com/2009/10/18/mapreduce-online/#comment-99 The 30 hottest webdesign-related links on the web « Adrian Zyzik's Weblog Mon, 19 Oct 2009 13:58:05 +0000 http://databeta.wordpress.com/?p=206#comment-99 [...] MapReduce Online! (and some gimmes) Data Beta [...] [...] MapReduce Online! (and some gimmes) Data Beta [...]

]]> Comment on MapReduce Online! (and some gimmes) by uberVU - social comments http://databeta.wordpress.com/2009/10/18/mapreduce-online/#comment-93 uberVU - social comments Mon, 19 Oct 2009 04:48:58 +0000 http://databeta.wordpress.com/?p=206#comment-93 <strong>Social comments and analytics for this post...</strong> This post was mentioned on Twitter by neil_conway: Blog post on our pipelined version of Hadoop, which does running approx answers and stream processing (continuous M/R): http://tr.im/CgSE... Social comments and analytics for this post…

This post was mentioned on Twitter by neil_conway: Blog post on our pipelined version of Hadoop, which does running approx answers and stream processing (continuous M/R): http://tr.im/CgSE...

]]> Comment on MapReduce Online! (and some gimmes) by Twitter Trackbacks for MapReduce Online! (and some gimmes) « Data Beta [databeta.wordpress.com] on Topsy.com http://databeta.wordpress.com/2009/10/18/mapreduce-online/#comment-92 Twitter Trackbacks for MapReduce Online! (and some gimmes) « Data Beta [databeta.wordpress.com] on Topsy.com Mon, 19 Oct 2009 04:42:57 +0000 http://databeta.wordpress.com/?p=206#comment-92 [...] MapReduce Online! (and some gimmes) « Data Beta databeta.wordpress.com/2009/10/18/mapreduce-online – view page – cached * Posted in database, gimmes, map reduce, parallelism, research * Tagged hadoop, HOP, online aggregation, stream queries — From the page [...] [...] MapReduce Online! (and some gimmes) « Data Beta databeta.wordpress.com/2009/10/18/mapreduce-online – view page – cached * Posted in database, gimmes, map reduce, parallelism, research * Tagged hadoop, HOP, online aggregation, stream queries — From the page [...]

]]> Comment on The Cloud Goes BOOM: First Strike by I Do Declare: Pocket-Sized Paxos and 2PC « Data Beta http://databeta.wordpress.com/2009/07/13/the-cloud-goes-boom/#comment-91 I Do Declare: Pocket-Sized Paxos and 2PC « Data Beta Mon, 12 Oct 2009 21:08:25 +0000 http://databeta.wordpress.com/?p=162#comment-91 [...] Data Beta on computing and data .. in permanent beta About « The Cloud Goes BOOM: First Strike [...] [...] Data Beta on computing and data .. in permanent beta About « The Cloud Goes BOOM: First Strike [...]

]]> Comment on Diverging views on Big Data density, and some gimmes by birthday messages http://databeta.wordpress.com/2009/05/14/bigdata-node-density/#comment-81 birthday messages Fri, 11 Sep 2009 18:27:08 +0000 http://databeta.wordpress.com/?p=140#comment-81 The reason you see a lot of people talk about using Hadoop on plain text data is that many data sets come into a system that way and are not queried often enough to justify converting to anything else. A perfect example is web search. Every night, you might crawl a number of web pages and end up with raw text data. You then scan these pages to update an index, and never do anything else with them. The reason you see a lot of people talk about using Hadoop on plain text data is that many data sets come into a system that way and are not queried often enough to justify converting to anything else. A perfect example is web search. Every night, you might crawl a number of web pages and end up with raw text data. You then scan these pages to update an index, and never do anything else with them.

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