A new WG21 paper is available. A copy is linked below, and the paper will also appear in the next normal WG21 mailing. If you are not a committee member, please use the comments section below or the std-proposals forum for public discussion.

Document number: N3563

Date: 2013-03-15

C++ Mapreduce

by Chris Mysen, Lawrence Crowl, Adam Berkan

Excerpt:

For large scale distributed problems, the map-reduce framework has proven to be a highly effective way at creating highly parallel workflows working over distributed filesystems on petabyte scale operations and has been used for analysis, machine learning, and implementation of many distributed computation problems at Google.

This proposal outlines the details of a version of mapreduce which is logically simple but very extensible, based heavily off of both distributed and threaded versions of mapreduce, allowing for implementations which work as distributed, threaded, or both. There are some simplifications in this implementation which are detailed later, but much of the flexibility of many of the implemented map-reduces is retained.