This article—the first in a series on Hadoop—explores the Hadoop framework, including its fundamental elements, such as the Hadoop file system (HDFS), and node types that are commonly used. Learn how to install and configure a single-node Hadoop cluster, and delve into the MapReduce application. Finally, discover ways to monitor and manage Hadoop using its core Web interfaces.

Google has granted a license for a recently granted MapReduce process patent to the Apache Software Foundation for the Apache Hadoop open source framework for distributed computing

Hadoop is a library for writing distributed data processing programs using the MapReduce framework. It's got all the makings of a blogosphere hit: cluster computing, large datasets, parallelism, algorithms published by Google, and open source.

Hadoop is a distributed computing platform that provides a framework for storing and processing petabytes of data. Because it is Java-based, Hadoop runs on Linux, Windows, Solaris, BSD, and Mac OS X. Hadoop is widely used in organizations that demand a scalable, economical (read commodity hardware), efficent, and reliable platform for processing vast amounts of data.

The first article in this series showed how to use Hadoop in a single-node cluster. This article continues with a more advanced setup that uses multiple nodes for parallel processing. It demonstrates the various node types required for multinode clusters and explores MapReduce functionality in a parallel environment.

Cloudera is releasing a Linux distro for Hadoop, the cloud-computing technology behind Facebook, Google and others. Cloudera's Hadoop is aimed at regular enterprise data centers.

Last month’s Hadoop Summit in Santa Clara, California, saw a number of interesting developments around this increasingly hot open source project…

Creating a business around free software is hardly a new idea: Cygnus Solutions, based around Stallman's GCC, was set up in 1989. But here's one with a trendy twist: a company based on the open source *cloud computing* app Hadoop, an Apache Project

Blue Cloud itself consists of Xen and PowerVM virtualized Linux operating-system images and Hadoop parallel workload scheduling, all supported by IBM Tivoli server-management software.