Advice on how to design and build your Apache Spark application for testability
Map Reduce can be used in jobs such as pattern-based searching, web access log stats, document clustering, web link-graph reversal, inverted index construction, term-vector per host, statistical machine translation and machine learning. Text indexing, search, and tokenization can also be accomplished with the Map Reduce program.
Map Reduce can also be used in different environments such as desktop grids, dynamic cloud environments, volunteer computing environments and mobile environments. Those who want to apply for Map Reduce jobs can educate themselves with the many tutorials available in the internet. Focus should be put on studying the input reader, map function, partition function, comparison function, reduce function and output writer components of the program. Hire Map Reduce Developers
Design a MapReduce-based algorithm to calculate a simple inverted index over the input set of files. Your map function should extract individual words from the input it is given, and output the word as the key and the current filename as the value. Write a Query program on top of your inverted file index in Hadoop, which will accept a user-specified word and return the IDs of the documents that co...