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

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 ...

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 ...

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 ...

MapReduce is a programming model, designed by Google for batch processing massive datasets in parallel using distributed computing.

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.

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 ...

This is a comprehensive Apache Hadoop and Spark comparison, covering their differences, features, benefits, and use cases.