The Family of Map-Reduce

Sakr, Sherif; Liu, Anna

doi:10.1007/978-1-4614-9242-9_1

Cited by 2 publications

(1 citation statement)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The distributed databases based processing of Big Data has many advantages especially related to distributed storage and parallel abilities (Wu et al, 2013). The MapReduce (Krishnanal et al, 2010) algorithm is one of the most efficient algorithms in this context (Sakr and Liu, 2014) (Polo, 2013). It is used to perform aggregated queries on a DDB.…”

Section: Introductionmentioning

confidence: 99%

Big Data in Complex Systems

Hassanien¹,

Azar²,

Snåšel³

et al. 2015

Studies in Big Data

View full text Add to dashboard Cite

The series "Studies in Big Data" (SBD) publishes new developments and advances in the various areas of Big Data-quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economics and life sciences. The books of the series refer to the analysis and understanding of large, complex, and/or distributed data sets generated from recent digital sources coming from sensors or other physical instruments as well as simulations, crowd sourcing, social networks or other internet transactions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence incl. neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence, data mining, modern statistics and Operations research, as well as self-organizing systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.More information about this series at

show abstract

Section: Introductionmentioning

confidence: 99%