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.

Extracting business value from the ‘big data’ contained in these unstructured, distributed file systems is becoming increasingly important. Distributed programming models such as MapReduce enable this ...

Extracting business value from the ‘big data’ contained in these unstructured, distributed file systems is becoming increasingly important. Distributed programming models such as MapReduce enable this ...

To many, Big Data goes hand-in-hand with Hadoop + MapReduce. But MPP (Massively Parallel Processing) and data warehouse appliances are Big Data technologies too. The MapReduce and MPP worlds have ...

Spotting Big Data trends, without MapReduce Big Data is not always about Hadoop, and it's not always about new technologies.

About MapReduce 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 ...

Cloud and grid software provider Platform Computing has announced support for the Apache Hadoop MapReduce programming model.

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.

Hadoop’s MapReduce programming model facilitates parallel processing. Developers specify a map function to process input data and produce intermediate key-value pairs.