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.

To help illustrate the MapReduce programming model, consider the problem of counting the number of occurrences of each word in a large collection of documents. The user would write code like the ...

MapReduce is a programming model developed for distributed computation on big data sets in parallel. A MapReduce model contains a map function, which performs filtering and sorting, and a reduce ...

Abstract: The big data analytics community has accepted MapReduce as a programming model for processing massive data on distributed systems such as a Hadoop cluster. MapReduce has been evolving to ...

Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to ...

The USPTO awarded search giant Google a software method patent that covers the principle of distributed MapReduce, a strategy for parallel processing that is used by the search giant. If Google ...

Abstract: There are more than 190 configuration parameters affecting the performance of MapReduce jobs on Hadoop. It is time-consuming and tedious for general users who have no deep knowledge of ...