MapR Enables Hadoop-as-a-Service with Multi-tenancy, Security and End-to-End Management
June 13, 2012
Version 2.0 benefits on-premise, cloud and hybrid deployments
MapR Technologies, Inc., the provider of the open, enterprise-grade distribution for Apache Hadoop, today announced Version 2.0 of the MapR Distribution which includes advanced monitoring, management, isolation and security for Hadoop. The latest version enables organizations to meet the needs of multiple users, groups and applications within the same cluster. In a related announcement, MapR also announced the availability of the MapR M3 and M5 editions through Amazon Web Services.
MapR provides complete visibility into all cluster activities. Every node captures and reports node, job and task metrics. The MapR Control System (MCS) displays this information in dozens of views, ranging from interactive historgrams to time charts, allowing administrators to filter, aggregate and drill-down on individual jobs and tasks. All MapReduce log files are logically centralized so they can be instantly accessed, searched and analyzed. All metrics and logs are automatically compressed, sharded and replicated in MapR's highly-available storage layer, and users can easily perform custom analytics with MapReduce, Hive, Pig or Cascading.
"Whether you're deploying on-premise, in the cloud, or a hybrid model for disaster recovery or elastic deployments, MapR has optimized the management and performance to ensure an easy and successful deployment," said Jack Norris, vice president of marketing, MapR Technologies. "Customers continue to benefit from MapR's innovations providing ease of use, dependability and increased performance."
With 2.0, MapR also provides advanced job management capabilities enabling an administrator to have complete control over the operation of the cluster, jobs and tasks. Job and data placement control ensures that data and job execution can be isolated in different areas of a cluster for performance, security or cost control. MapR now provides complete end-to-end visibility and control of hardware, software, storage, MapReduce and other components of the MapR Distribution.
Additional advances in Version 2.0 include:
- Job monitoring and management
A graphical display of time and resources consumed by jobs and tasks lets users allocate and track cluster usage, diagnose slow nodes and determine real performance metrics. The MapR Control System displays line charts and histograms that let administrators zoom in to see detailed information on a large variety of job and task statistics.
- Job and data placement control
Job placement control lets users specify exactly which nodes will run each job to take advantage of different performance profiles or limit jobs to specific physical locations. Powerful wildcard syntax lets users define groups of nodes and assign jobs to any combination of groups. Administrators can leverage MapReduce queues and ACLs to restrict specific users and groups to a subset of the nodes in the cluster. Administrators can also control data placement, enabling them to isolate specific datasets to a subset of the nodes.
- Multi-tenancy support
MapR clusters provide powerful features to logically partition a physical cluster to provide separate administration, data placement, job execution and network access.
- Central configuration
With MapR, users don't have to tune MapReduce node by node. Custom central configuration can be applied to all nodes or only the nodes of the administrators choosing, and updated as frequently as desired.
- Central logging
Logical centralization of log data makes it easy to diagnose problems such as failed jobs without searching from node to node and manually aggregating logs. MapR does this through the logical aggregation of local volumes on each node, saving time and eliminating the unnecessary copying or moving of data.
- Enhanced compression
MapR now provides compression algorithms to let users choose how to store data in the cluster. With LZ4, LZF and GZIP algorithms, MapR gives the flexibility to balance performance versus space saved.
- Enhanced security
With MapR, administrators don't need to worry about their data. MapR provides security throughout the MapReduce stack, ranging from IP address whitelisting to a secured TaskTracker and integration with PAM. In addition, MapR now supports SELinux.
- New versions of HBase™, Hive, Pig and other open source components
MapR continues to update the distribution with the latest versions of Hadoop components from the broad Hadoop ecosystem. These components are part of the tested, hardened and supported MapR Distribution. This release features new versions of Hive, HBase™ and many other open source components.
- SUSE support
MapR is now supported on three of the most popular enterprise-ready Linux distributions: Ubuntu, Red Hat Enterprise Linux (RHEL) and SUSE Linux Enterprise Server (SLES).
The Version 2.0 beta for the M3 and M5 editions of the MapR Distribution are now available for download at mapr.com/download.
About MapR Technologies
MapR Technologies is a visionary Silicon Valley software company and creator of the next-generation data platform for AI and analytics, with the scale and reliability required by enterprise-grade, mission-critical deployments. The MapR Data Platform delivers the power of dataware to accelerate data-driven innovation. Forward leaning companies such as Cisco, Philips, and Société Générale, are able to create new data-driven solutions to outperform the competition. Learn more: mapr.com.
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