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 ...

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 ...

Some algorithms translate poorly to Map-Reduce—the partitioning of data and computation to individual nodes makes some computations (graph processing for instance) difficult. And, the implementation ...

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

According to ScaleOut CEO Bill Bain, with hServer, the analytics capability — the MapReduce algorithm — is used not just to analyse the data but also to update that data in parallel.

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 ...

In earlier versions, Platfora’s software would generate batch-oriented MapReduce jobs to do the grunt work of finding patterns in the data, and used interactive SQL queries using the Hive engine for ...

Cascading is a new processing API for data processing on Hadoop clusters, and supports building complex processing workflows using an expressive, declarative API.

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 ...