Buffering schemes for permanent data

The availability of larger RAM spaces for DBMSs provides interesting opportunities for performance enhancements, especially in buffer management. In this paper we propose and compare two alternative strategies for the buffer management of permanent data (i.e., the data committed by transactions) called block buffering and attribute buffering. These strategies use statistics to capture the changing locality of a reference string. We model and demonstrate the impact of locality on the performance of buffering. We also analyze and compare the effect of both the attribute and predicate dimensions of locality on buffering, varying a number of parameters including the degree of locality, RAM size, and RAM utilization.