Le modèle MapReduce est conçu pour lire, traiter et écrire des volumes massifs de données. Des bonnes feuilles issues de l'ouvrage Big Data chez Eni.

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...

But now that we are all swimming in Big Data, MapReduce implemented on Hadoop is being packaged as a way for the rest of the world to get the power of this programming model and parallel computing ...

Spotting Big Data trends, without MapReduce As Trendspottr shows us, sometimes hardcore algorithms, even older ones, provide new breakthroughs. Written by Andrew Brust, Contributor June 4, 2012 at ...

Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day ...

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 ...

With growth in unstructured big data, RDBMS is inadequate for big data analytics. Know how to use SQL and MapReduce for big data analytics, instead.

But there are downsides. The MapReduce programming model that accesses and analyses data in HDFS can be difficult to learn and is designed for batch processing.