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A distributed MapReduce algorithm for face matching based monitoring movement of individuals over large surveillance space is presented in [8].

Section 3 gives a brief presentation of MapReduce model.

More specifically, the contribution of this study is (i) to design novel distributed parallel kernel density regression and partial linear regression algorithms over the SPARK MapReduce paradigm for big data and (ii) to validate the algorithms, analyzing their accuracy, scalability, and speedup by means of numerical experiments.

Conforme Dean e Ghemawat (2008), em 2008, o Google apresentou um modelo de programacao denominado MapReduce, que e especialmente interessante para a construcao de aplicacoes desse tipo.

These tools are largely either programming languages or models for building software that can make sense of big data (such as MapReduce, MALLET, R), implementation frameworks for launching such software (such as Hadoop, Azure), or ways of visualizing data (such as D3.js).

Big data application is composed by combination of MarkLogic database and MapReduce of Hadoop.

When the Apache Hadoop project started, MapReduce V1 was the only choice as a Compute model (Execution Engine) on Hadoop.

Google faced a similar database constraint around 2000 that prompted development of MapReduce, "a programming model and an associated implementation for processing and generating large data sets," as described by the company's Dean and Ghemawat in a 2004 paper.

Hunk is now also available directly from the Amazon Elastic MapReduce console and priced on an hourly basis.

Thus, network bandwidth of Data node and operations of disk IO can be reduced effectively if only migration of data of task MapReduce is reduced.

With the fast deployment of cloud computing, MapReduce architectures are becoming the major technologies for mobile cloud computing.