Distributed query processing optimization objectives

Abstract

The authors examine objectives, or measures of cost, which can be used in optimizing queries in a distributed database (DDB). They include the delay and dollar cost due to the network data transfer, CPU processing or a combination of both, and cost measures in terms of the size of partial results. These measures are used in distributed query processing modeling on a testbed of queries to examine the effect of choosing one measure of cost in optimizing strategies on their cost expressed in other measures and the cost of strategies generated by a two-phased approach. Results indicate that best strategies are generated when optimization considers cost measured in terms of both CPU processing and a network data transfer. They also confirm that the two-phased optimization yields close to optimal strategies.<>