Everyone knows that if MapReduce and Hadoop require elite programmers to write programs to analyze data, then the size of the market will be small. A burning question for all Hadoop vendors is ...

Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to ...

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 ...

It is an open implementation of the MapReduce algorithm and includes HDFS (Hadoop Distributed File System) for high throughput access to distributed data. What has been less visible for some time is ...

Hadoop MapReduce has been widely embraced for analyzing large, static data sets. New technology integrates a stand-alone MapReduce engine into an in-memory data grid, enabling real-time analytics on ...

Google's patent on MapReduce could potentially pose a problem for those using third-party open source implementations. Patent #7,650,331, which was granted to Google on Tuesday, defines a system ...

We just follow the MapReduce pattern and Hadoop does the rest. MapReduce with Hadoop Hadoop is mostly a Java framework, but the magically awesome Streaming utility allows us to use programs written in ...

"We knew that we were going to have to take Hadoop beyond MapReduce," Murthy says. "The programming model—the MapReduce algorithm—was limited. It can't support the very wide variety of use-cases we're ...

An Efficient Implementation of Apriori Algorithm Based on Hadoop-Mapreduce Model Finding frequent itemsets is one of the most important fields of data mining.