When your data and work grow, and you still want to produce results in a timely manner, you start to think big. Your one beefy server reaches its limits. You need a way to spread your work across many ...

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A complete implementation of the Hadoop MapReduce word count pipeline with Mapper, Reducer, Combiner, and custom Partitioner — runnable locally in Python with the original Java source as reference.

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.

Orchestrate Hadoop MapReduce Streaming jobs through Luigi, reading from and writing to HDFS with automatic dependency resolution and idempotent execution. Running MapReduce jobs manually requires ...

Google and its MapReduce framework may rule the roost when it comes to massive-scale data processing, but there’s still plenty of that goodness to go around. This article gets you started with Hadoop, ...

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 ...