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 ...

The demand for job skills related to data processing — NoSQL, Apache Hadoop, Python, and a smattering of other such skills — has hit all-time highs, according to statistics collected by tech job site ...

Hadoop has been widely embraced for its ability to economically store and analyze large data sets. Using parallel computing techniques like MapReduce, Hadoop can reduce long computation times to hours ...

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 ...

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 ...

Hadoop and MapReduce have long been mainstays of the big data movement, but some companies now need new and faster ways to extract business value from massive — and constantly growing — datasets.

The market for software related to the Hadoop and MapReduce programming frameworks for large-scale data analysis will jump from $77 million in 2011 to $812.8 million in 2016, a compound annual growth ...

Hadoop introduced a new way to simplify the analysis of large data sets, and in a very short time reshaped the big data market. In fact, today Hadoop is often synonymous with the term big data. Since ...