Learn about the emerging trends and challenges in MapReduce and big data, such as data variety, volume, velocity, security, and analysis. Discover techniques and tools to optimize your applications.

The rapid growth of large-data processing has brought in the MapReduce programming model as a widely accepted solution. However, MapReduce limits itself to a one map-to-one-reduce framework. Meanwhile ...

<P>MapReduce is a leading programming model for big data analytics. It uses pure functional concepts that benefit the highest level of parallelism granularity. Programming in this model is in ...

Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth ...

Big data adoption continues to grow. Big Data covers data volumes from petabytes to exabytes and is essentially a distributed processing mechanism. MapReduce is a framework for data processing model.

Mapreduce is a programming model for processing and generating large data sets. 4 Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs and a ...

MapReduce is a programming model specifically implemented for processing large data sets. The model was developed by Jeffrey Dean and Sanjay Ghemawat at Google (see “MapReduce: Simplified data ...