One utilisation of multidimensional databases is the field of On-line Analytical Processing (OLAP). The applications in this area are designed to make the analysis of shared multidimensional information fast PendseB. On one hand, speed can be achieved by specially devised data structures and algorithms. On the other hand, the analytical process is cyclic. In other words, the user of the OLAP application runs his or her queries one after the other. The output of the last query may be there (at least partly) in one of the previous results. Therefore caching also plays an important role in the operation of these systems. However, caching itself may not be enough to ensure acceptable performance. Size does matter: The more memory is available, the more we gain by loading and keeping information in there. Oftentimes, the cache size is fixed. This limits the performance of the multidimensional database, as well, unless we compress the data in order to move a greater proportion of them into the memory. Caching combined with proper compression methods promise further performance improvements. In this paper, we investigate how caching influences the speed of OLAP systems. Different physical representations (multidimensional and table) are evaluated. For the thorough comparison, models are proposed. We draw conclusions based on these models, and the conclusions are verified with empirical data.
Vitter @cite_5 describe an algorithm for prefetching based on compression techniques. Our paper supposes that the system does not read ahead.
@cite_5
2146104665
A form of the competitive philosophy is applied to the problem of prefetching to develop an optimal universal prefetcher in terms of fault ratio, with particular applications to large-scale databases and hypertext systems. The algorithms are novel in that they are based on data compression techniques that are both theoretically optimal and good in practice. Intuitively, in order to compress data effectively, one has to be able to predict feature data well, and thus good data compressors should be able to predict well for purposes of prefetching. It is shown for powerful models such as Markov sources and mth order Markov sources that the page fault rates incurred by the prefetching algorithms presented are optimal in the limit for almost all sequences of page accesses. >