A Comparison Study of Graph Data Processing Based on MyBSP and MapReduce

Abstract

How to effectively process massive graph data is an intractable challenging issue. In this paper, two types of parallel computation approaches were compared: MapReduce and MyBSP. MyBSP is our open source implementation which adopts the Bulk Synchronous Parallel (BSP) programming model to support iterative processing. The MapReduce-based and MyBSP-based PageRank algorithms were implemented respectively. The experimental studies were conducted to evaluate and compare the performance and scalability of our MyBSP prototype system with MapReduce model. The results revealed that the MyBSP approach outperforms MapReduce approach for iterative graph data processing with vary size of datasets.

The characteristics of artificial intelligence model description language and its research direction

“…The authors can define various operations to describe the behavioral details that cannot be described by other models, and can also use interactive forms to describe the management mode of the system. [10][11][12][13]…”