On Coupling Multi-Systems Through Data Sharing

Abstract

The demand for larger transaction rates and the inability of single-system-based transaction processors to keep up with demand have resulted in the growth of multi-processor-based database systems. The focus here is on coupling in a locally distributed system through multi-system data sharing in which all systems have direct access to the data. This paper addresses the following questions; i) How does a workload running on a single system today perform if migrated to a multi-system? ii) What are the multi-system locking design issues that limit multi-system performance and what is the maximum number of systems that may be effectively coupled? iii) Can alternative locking designs increase the number of systems that may be effectively coupled? Our analysis is based on traces from large mainframe systems running IBM's IMS database management system. We have developed a hierarchical modeling methodology that starts by synthesizing a multi-system IMS lock trace and a reference trace from single-system traces. The multi-system traces are used in trace-driven simulations to predict lock contention and database I/O increase in multi-system environment and to generate workload parameters. These parameters are used in event-driven simulation models to examine the overall performance under different system structures. Performance results are presented for realistic system parameters to determine the performance impact of various design parameters. Lock contention is found to be the critical factor in determining the coupling effectiveness and the effect of alternative locking design to reduce lock contention is studied. The limit on coupling is explored and the analysis indicates that, for this workload, on the order of 6 to 12 systems may be effectively coupled through data sharing, depending on system structure and locking design. Copyright © 1987 by The Institute of Electrical and Electronics Engineers, Inc.