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A Map-Reduce System with an Alternate API for Multi-Core Environments
 

Summary: A Map-Reduce System with an Alternate API for
Multi-Core Environments
Wei Jiang Vignesh T. Ravi Gagan Agrawal
Department of Computer Science and Engineering
The Ohio State University Columbus OH 43210
{jiangwei,raviv,agrawal}@cse.ohio-state.edu
Abstract--Map-reduce framework has received a significant
attention and is being used for programming both large-scale
clusters and multi-core systems. While the high productivity
aspect of map-reduce has been well accepted, it is not clear
if the API results in efficient implementations for different sub-
classes of data-intensive applications. In this paper, we present
a system MATE (Map-reduce with an AlternaTE API), that
provides a high-level, but distinct API. Particularly, our API
includes a programmer-managed reduction object, which results
in lower memory requirements at runtime for many data-
intensive applications. MATE implements this API on top of the
Phoenix system, a multi-core map-reduce implementation from
Stanford.
We evaluate our system using three data mining applications

  

Source: Agrawal, Gagan - Department of Computer Science and Engineering, Ohio State University

 

Collections: Computer Technologies and Information Sciences