by Angela Guess
Derrick Harris of GigaOM reports, “Before you can get into the fun part of actually processing and analyzing big data with Hadoop, you have to configure, deploy and manage your cluster. It’s neither easy nor glamorous — data scientists get all the love — but it is necessary. Here are five tools (not from commercial distribution providers such as Cloudera or MapR) to help you do it.” First up, “Apache Ambari is an open source project for monitoring, administration and lifecycle management for Hadoop. It’s also the project that Hortonworks has chosen as the management component for the Hortonworks Data Platform. Ambari works with Hadoop MapReduce, HDFS, HBase, Pig, Hive, HCatalog and Zookeeper.”
Second, “Apache Mesos is a cluster manager that lets users run multiple Hadoop jobs, or other high-performance applications, on the same cluster at the same time. According to Twitter Open Source Manager Chris Aniszczyk, Mesos ‘runs on hundreds of production machines and makes it easier to execute jobs that do everything from running services to handling our analytics workload’.” Next on the list, “Platform MapReduce is high-performance computing expert Platform Computing’s entre into the big data space. It’s a runtime environment that supports a variety of MapReduce applications and file systems, not just those directly associated with Hadoop, and is tuned for enterprise-class performance and reliability. Platform, now part of IBM, built a respectable business managing clusters for large financial services institutions.”
photo credit: Apache
