Hi Craig, Yes, there is interest! I think what would is needed for this to be a useful library: 1) compare to the C phoenix library http://mapreduce.stanford.edu The library has just been updated to v2 and supports linux x86_64 (provides many datasets/examples and it could be benchmarked against. There is also a great paper/video/slides describing the library) 2) have a plan so that the library can eventually range from working on 1 multi-core system to distributed It should work with the great open source projects - http://kosmosfs.sf.net (C++ distributed file system) - http://hypertable.org (C++ distributed db, which already works on top of kfs) Both kfs and hypertable lack a C++ mapreduce library to work with and use a java one) Do you plan to set a project/mailing list ? regards On Sun, Jun 14, 2009 at 11:45 PM, Craig Henderson<cdm.henderson@googlemail.com> wrote:
MapReduce is a programming model from Google that is designed for scalable data processing. Google's implementation is for scalability over many thousands of commodity machines, but there is value in using the idiom on multi-core processors to partition processing to efficiently use the CPU available, and avoid the complexities of multi-threaded development.
I have a implemented a MapReduce runtime library in C++ using Boost and would like to see if there is interest from you all to submit the library to Boost. I have preliminary documentation on my website at http://www.craighenderson.co.uk/mapreduce/