MapReduce was invented by Google in 2004, made into the Hadoop open source project by Yahoo! in 2007, and now is being used increasingly as a massively parallel data processing engine for Big Data.

Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Novel architectures are born out of necessity and for some applications, including molecular dynamics, there have been endless attempts to push parallel performance. According to the leads behind a ...

Hadoop has been known as MapReduce running on HDFS, but with YARN, Hadoop 2.0 broadens pool of potential applications Hadoop has always been a catch-all for disparate open source initiatives that ...

Microsoft is making available for download the first release a new piece of cloud analytics technology developed by its eXtreme Computing Group that is known as Project Daytona. Microsoft describes ...

Finding frequent itemsets is one of the most important fields of data mining. Apriori algorithm is the most established algorithm for finding frequent itemsets from a transactional dataset; however, ...

Urs Holzle, the senior vice president of technical infrastructure and Google Fellow at Google and Google's eighth employee, announced Google is not using MapReduce anymore. But don't you worry, this ...

What are some of the cool things in the 2.0 release of Hadoop? To start, how about a revamped MapReduce? And what would you think of a high availability (HA) implementation of the Hadoop Distributed ...