Performance Analysis of WHIPS Incremental Maintenance

Incremental maintenance incorporates new changes automatically and continuously into a data warehouse, and seems to be the best maintenance solution for very large warehouses. However, the performance of incremental maintenance algorithms is not well understood, and commercial incremental maintenance systems are still not widely available. In this paper, we study the performance of WHIPS, a prototype system developed at Stanford focusing on warehouse maintenance. We examine the efficiency of change propagation and study factors that determine the efficiency. We also compare the relative performance of different warehouse maintenance techniques. 1 Introduction A data warehouse stores integrated data from multiple, often distributed and autonomous data sources, and is typically used for decision support. One of the major challenges is to correctly and efficiently update the warehouse as the source data changes. There are basically two categories of techniques for this: refreshing and in..