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 ...

Hadoop 2.0 makes MapReduce less compulsory and the distributed file system more reliable.

Hadoop in a post-MapReduce world Those familiar with MapReduce will wonder how Tez is different. Tez is a broader, more powerful framework that maintains MapReduce’s strengths while overcoming ...

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 ...

Big data analytic software vendors who run on Hadoop are increasingly replacing their MapReduce engines with Apache Spark and other in-memory analytic engines as the runtime of choice. Many of these ...