About MapReduce MapReduce is a programming model specifically implemented for processing large data sets. The model was developed by Jeffrey Dean and Sanjay Ghemawat at Google (see “ MapReduce ...

The inspiration for Hadoop came from Google's work on MapReduce, a programming model for distributed computing—a way to allow big data to be stored and accessed on multiple server computers.

Hadoop is the most significant concrete technology behind the so called 'Big Data' revolution. Hadoop combines an economical model for storing massive quantities of data - the Hadoop Distributed File ...

The core components of Apache Hadoop are the Hadoop Distributed File System (HDFS) and the MapReduce programming model.

The underlying programming model for MapReduce has been revamped and has changed quite a bit. Chuck Lam, the author of Hadoop in Action Benefits that keep getting better include high levels of ...

Platform Computing, a provider of cluster, grid and cloud management software, has announced support for the Apache Hadoop MapReduce programming model to bring enterprise-class distributed computing ...

To many, Big Data goes hand-in-hand with Hadoop + MapReduce. But MPP (Massively Parallel Processing) and data warehouse appliances are Big Data technologies too. The MapReduce and MPP worlds have ...

Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day ...

But there are downsides. The MapReduce programming model that accesses and analyses data in HDFS can be difficult to learn and is designed for batch processing.