Hadoop MapReduce has been widely embraced for analyzing large, static data sets. New technology integrates a stand-alone MapReduce engine into an in-memory data grid, enabling real-time analytics on ...

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 ...

Geared for beginners, Hadoop Fundamentals I from Big Data University is focused on the basics of Hadoop, including the Hadoop architecture, HDFS, MapReduce, Pig, Hive, JAQL, Flume and other ...

GridGain announced In-Memory Accelerator for Hadoop, offering benefits of in-memory computing to Hadoop applications. InfoQ spoke with Nikita Ivanov from GridGain about the product's architecture.

While MapReduce is proprietary technology, the Apache Foundation has implemented its own open source map-reduce framework, called Hadoop.

If you set up pseudo-distributed (or distributed) Hadoop, you'll gain the benefit of two spartan-but-useful Web interfaces. The NameNode Web interface allows you to browse logs and browse the Hadoop ...

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

MapR's latest Hadoop distribution includes support for Hadoop 2.2 with YARN, but is also backward compatible with the MapReduce 1.x scheduler, promising organizations a risk-free upgrade path to ...

Hadoop is hard. There’s just no way around that. Setting up and running a cluster is hard, and so is developing applications that make sense of, and create value from, big data. What Hadoop really ...

MapReduce, Chubby and Hadoop Energy drink Red Bull sponsors air races. In New York, colorful propeller aircraft raced around and through inflated gates. The gates looked like the blow-up animals in ...