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 ...

Lack of multiple data source support – Current implementations of the Hadoop MapReduce programming model only support a single distributed file system; the most common being HDFS.

Hadoop is the most significant concrete technology behind the so called 'Big Data' revolution. Hadoop combines an economical model for storing massive quantities of data - the Hadoop Distributed File ...

The core components of Apache Hadoop are the Hadoop Distributed File System (HDFS) and the MapReduce programming model.

The underlying programming model for MapReduce has been revamped and has changed quite a bit. Chuck Lam, the author of Hadoop in Action Benefits that keep getting better include high levels of ...

Technical Terms MapReduce: A programming model that simplifies distributed data processing by dividing tasks into map and reduce functions operating in a parallel, fault-tolerant manner.

Hunk is a relatively new product from Splunk for exploring and visualizing Hadoop and other NoSQL data stores. New in this release is support for Amazon’s Elastic MapReduce.

Platform Computing, a provider of cluster, grid and cloud management software, has announced support for the Apache Hadoop MapReduce programming model to bring enterprise-class distributed computing ...

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 ...

This is a comprehensive Apache Hadoop and Spark comparison, covering their differences, features, benefits, and use cases.

Lack of multiple data source support – Current implementations of the Hadoop MapReduce programming model only support a single distributed file system; the most common being HDFS.