Page-query compaction of secondary memory auxiliary databases

Abstract

Prestoring redundant data in secondary memory auxiliary databases is an idea that can often yield improved retrieval performance through better clustering of related data. The clusters can be based on either whole query results or, as this paper indicates, on more specialized units called page-queries. The deliberate redundancy introduced by the designer is typically accompanied by much unnecessary redundancy among the elements of the auxiliary database. This paper presents algorithms for efficiently removing unwanted redundancy in auxiliary databases organized into page-query units. The algorithms presented here extend prior work done for secondary memory compaction in two respects: First, since it is generally not possible to remove all unwanted redundancies, the paper shows how can the compaction be done to remove the most undesirable redundancy from a system performance point-of-view. For example, among the factors considered in determining the worst redundancies are the update behavior and the effects of a particular compaction scheme on memory utilization. Second, unlike traditional approaches for database compaction which aim merely at reducing the storage space, this paper considers the paging characteristics in deciding on an optimal compaction scheme. This is done through the use of page-queries. Simulation results are presented and indicate that page-query compaction results in less storage requirements and more time savings than could be obtained by standard non-page-query compaction.