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 ...

Platform Computing supports a wide range of customers, many of which are embarking on MapReduce initiatives as a way of managing the extreme growth in unstructured data, Scott Campbell, director, ...

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.

Google's patent on MapReduce could potentially pose a problem for those using third-party open source implementations. Patent #7,650,331, which was granted to Google on Tuesday, defines a system ...

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