May 01, 2013 (10:05 AM EDT)
MapR Brings Search To Hadoop
Read the Original Article at InformationWeek
Last fall MapR set out to improve on HBase, Hadoop's built-in NoSQL database. On Wednesday it delivered on that promise and it announced a next move: integrating search capabilities with its M7 Hadoop distribution with partner LucidWorks.
With the latest MapR M7 release, available immediately, the company says it has delivered higher performance and easier administration for both Hadoop and HBase by forging its own path on certain aspects of Hadoop infrastructure and administration. Specifically, M7 does away with region servers, table splits and merges, and data compaction steps tied to standard Apache software. Instead it implements an architecture exclusive to MapR for snapshotting, high availability and system recovery.
"We've eliminated the tradeoffs that organizations face in terms of getting scale, consistency, reliability and continuous low-latency performance in one solution, but M7 works across all these dimensions," MapR VP of marketing Jack Norris told InformationWeek.
MapR points to advantages including instant recovery from hardware or software errors, the ability to do online schema modifications for HBase applications, and performance specs exceeding 1 million operations per second on a 10-node Hadoop cluster.
[ Want more on improvements to Hadoop's NoSQL database? Read MapR Promises A Better HBase. ]
To support search, MapR introduced the beta offering of LucidWorks Search software integrated with the M7 platform. The search technologies will be optional, and plans call for general release next quarter. LucidWorks offers a supported software distribution, consulting and training for open source Apache Lucene/Solr search, and it adds commercial development platforms designed to simplify and accelerate the building of search applications.
With search integrated directly with Hadoop, customers will have an easier time building out recommendation engines for retail scenarios, fraud-detection for financial transactions and predictive applications for any number of industries, according to Norris.
"You could do some of these applications in a MapReduce framework, but if you need online performance, MapReduce latency is a problem and having a search platform is extremely useful," Norris explained. MapR can stream data from Hadoop clusters into the search engine from NFS, the file system used in M7 in place of HDFS.
LucidWorks offers an enterprise-hardened and secured version of Apache Lucene/Solr. The software provides a REST-based API, ODBC connectivity, provisions for LDAP and NIS security, and connections to HDFS and NFS among other features.
MapR will provide first-level support for the new search option, but LucidWorks will be available for deeper problem solving when tougher problems emerge, according to Norris. The cost of the LucidWorks Search option was not disclosed.
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