Group items tagged

Mahout's goal is to build scalable, Apache licensed machine learning libraries. Initially, we are interested in building out the ten machine learning libraries detailed in http://www.cs.stanford.edu/people/ang//papers/nips06-mapreducemulticore.pdf using Hadoop. While these algorithms are our initial focus, we welcome contributions of other machine learning approaches.

Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.

What if you could contribute to a computational (Map-Reduce) job by simply pointing your browser to a URL? Surely your social network wouldn't mind opening a background tab to help you crunch a dataset or two! Instead of focusing on high-throughput proprietary protocols and high-efficiency data planes to distribute and deliver the data, we could use battle tested solutions: HTTP and your favorite browser.

ZooKeeper is a high-performance coordination service for distributed applications. It exposes common services - such as naming, configuration management, synchronization, and group services - in a simple interface so you don't have to write them from scratch. You can use it off-the-shelf to implement consensus, group management, leader election, and presence protocols. And you can build on it for your own, specific needs.

Cloudera presents the MapReduce bull case