Robotics and AI

Hadoop map reducing for analysing Information

Hadoop Mapreduce may be a framework for process massive information sets in parallel across a Hadoop cluster. Data analysis uses a two-step map and reduces method. The job configuration supplies map and reduce analysis functions and also the Hadoop framework provides the scheduling, distribution, and parallelization services. The top level unit of labour in Map reduce may be a job. A job usually has a map and a reduce phase, though the reduce phase can be omitted. For example, consider a Map reduce job that counts the number of times every word is used across a group of documents. The map section counts the words in every document, then the reduce section aggregates the per-document information into word counts spanning the whole collection.