Parallel Algorithms for the Execution of Relational Database Operations Revisited On Grids

Abstract

This paper presents an analytical discussion of algorithms for relational database operations in a grid environment, compares the findings with the classical generalized multiprocessor framework, and describes an optimization algorithm to maximize performance for a heterogeneous environment. We develop a concise but comprehensive analytical model of parallel algorithms for sorting, joining, and aggregation. In our approach we focus on a limited number of characteristic parameters to keep the analytical model clear. It is shown that an expressive model can be built upon just three characteristic parameter sets, namely the node processing performance and the network and the disk bandwidths. These parameters are the input for the optimization process for the orchestration of the execution workflow on the grid. Based on these results the paper proves that using smart enhancement to exploit the heterogeneity of the grid, the performance of the algorithms for database operations can be increased remarkably.