But now that we are all swimming in Big Data, MapReduce implemented on Hadoop is being packaged as a way for the rest of the world to get the power of this programming model and parallel computing ...

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: Simplified data ...

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...

This program will prepare you to create, develop and implement data models as well as work with big data sets using a real-world data cluster managed ... across clusters of commodity servers. Topics ...

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.

Hadoop’s MapReduce programming model facilitates parallel processing. Developers specify a map function to process input data and produce intermediate key-value pairs.

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 ...

Open source startup Cloudera aims to bring MapReduce style of applications to mere mortals (aka enterprises) ...

MySpace on Tuesday will release as open source a technology called Qizmt that it developed in-house to mine and crunch massive amounts of data and generate friend recommendations in its social ...