MapR Integrates Hadoop Distro With Google Compute Engine

 
 
By Chris Preimesberger  |  Posted 2012-07-06 Email Print this article Print
 
 
 
 
 
 
 

MapR on the Google Compute Engine will soon be available as a free private beta for a select number of users.

Data analytics software provider MapR Technologies has made its enterprise-grade Apache Hadoop distribution available to run on the new Google Compute Engine, introduced at Google I/O in San Francisco on June 28.

MapR on the Google Compute Engine will be available as a free private beta for a select number of users, MapR said. Those interested in big data analytics should review and fill out the nomination form.

The combination of the new Google service and MapR's Hadoop enables users to provision large MapR clusters on demand and to deploy it as a cloud-based analytics system.

Google originally developed MapReduce to become its internal search framework, which later inspired the community development of Hadoop under Doug Cutting at Yahoo. Now, through MapR's distribution for Hadoop, IT managers can use Google's infrastructure for big data analytics.

MapR demonstrated what it claimed to be a price/performance breakthrough on stage at the Google I/O conference by completing a 1TB TeraSort job in 1 minute, 20 seconds. This result was achieved on a Google Compute Engine cluster in the cloud with 1,256 nodes, 1,256 disks and 5,024 cores€”at a cost of about $16 for the entire subscription-based transaction.

This result compares with the existing world record of 1 minute, 2 seconds that was set with a physical cluster with more than four times the disks, twice as many cores, 200 more servers and at an estimated cost of more than $5 million.

The integration of MapR with Google Compute Engine includes a menu of standard MapR compute configurations. Users have the flexibility within Google Compute Engine to pay on demand and spin up more than 1,000 node clusters if necessary.

 
 
 
 
Chris Preimesberger Chris Preimesberger was named Editor-in-Chief of Features & Analysis at eWEEK in November 2011. Previously he served eWEEK as Senior Writer, covering a range of IT sectors that include data center systems, cloud computing, storage, virtualization, green IT, e-discovery and IT governance. His blog, Storage Station, is considered a go-to information source. Chris won a national Folio Award for magazine writing in November 2011 for a cover story on Salesforce.com and CEO-founder Marc Benioff, and he has served as a judge for the SIIA Codie Awards since 2005. In previous IT journalism, Chris was a founding editor of both IT Manager's Journal and DevX.com and was managing editor of Software Development magazine. His diverse resume also includes: sportswriter for the Los Angeles Daily News, covering NCAA and NBA basketball, television critic for the Palo Alto Times Tribune, and Sports Information Director at Stanford University. He has served as a correspondent for The Associated Press, covering Stanford and NCAA tournament basketball, since 1983. He has covered a number of major events, including the 1984 Democratic National Convention, a Presidential press conference at the White House in 1993, the Emmy Awards (three times), two Rose Bowls, the Fiesta Bowl, several NCAA men's and women's basketball tournaments, a Formula One Grand Prix auto race, a heavyweight boxing championship bout (Ali vs. Spinks, 1978), and the 1985 Super Bowl. A 1975 graduate of Pepperdine University in Malibu, Calif., Chris has won more than a dozen regional and national awards for his work. He and his wife, Rebecca, have four children and reside in Redwood City, Calif.Follow on Twitter: editingwhiz
 
 
 
 
 
 
 

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