Scientists and mathematicians have long loved Python as a vehicle for working with data and automation. Python has not lacked for libraries such as Hadoopy or Pydoop to work with Hadoop, but those ...

Apache Spark, the in-memory and real-time data processing framework for Hadoop, turned heads and opened eyes after version 1.0 debuted. The feature changes in 1.2 show Spark working not only to ...

When the Big Data moniker is applied to a discussion, it’s often assumed that Hadoop is, or should be, involved. But perhaps that’s just doctrinaire. Hadoop, at its core, consists of HDFS (the Hadoop ...

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.

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 ...

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 ...