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

That being the case, I'm going to assume that you've already built a Hadoop cluster (check out the last article if you need help with that), and I'll show you how to use a hive script to process data.

RainStor Big Data Analytics on Hadoop addresses some of the big problems with Hadoop, namely the complexity of interacting with it, the time it takes to run MapReduce jobs on large datasets and ...

The core idea is to run TensorFlow jobs as reliably and flexibly as other first-class citizens on Hadoop including MapReduce and Spark, LinkedIn said.

The venerable C programming language isn't going away, as shown by Google's open sourcing of a framework to let Big Data devs run native C code in Hadoop: MapReduce for C.