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
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 coresat 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
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.