| 638 | | * '''Description:''' MapReduce is a programming model and distributed processing platform implementation for generating and processing large data sets using clusters of computers. Pioneered by Google and first presented in 2004, the MapReduce programming model has gained significant momentum in commercial, research and open-source projects since, and Google have updated and republished their seminal paper in 2008. |
| 639 | | |
| 640 | | The scalability achieved using MapReduce to implement data processing across a large volume of CPUs, whether on a single server or multiple machines is an attractive proposition. The Boost.MapReduce library is a MapReduce implementation across a plurality of CPU cores rather than machines. The library is implemented as a set of C++ class templates, and is a header-only library. It does, however, depend upon many other Boost libraries, such as Boost.System, Boost.FileSystem and Boost.Thread. |
| | 638 | * '''Description:''' The Boost.MapReduce library is an implementation of the MapReduce programming model for scalable parallel processing across a plurality of CPU cores. The library is implemented as a set of C++ class templates, and is a header-only library. It does, however, depend upon many other Boost libraries, such as Boost.System, Boost.FileSystem and Boost.Thread. |
