Optimizing Hierarchical Access in OLAP Environment

In online analytic processing (OLAP) deployments, different users, lines of businesses and business units often create adhoc aggregation hierarchies tailor-made for specific reporting or analytical applications. As a result, a large number of these application specific hierarchies accumulate over time. System administrators typically are not able to optimize all these hierarchical accesses by hand due to the large number of hierarchies. However, many optimization opportunities exist due to the significant amount of overlap between some hierarhies. In this paper, we sketch a novel method for optimizing OLAP aggregation queries using precomputed aggregates on other overlapping hierarchies. Our method detects common sub-structures among hierarchies and provides a rewriting algorithm to exploit any precomputations on these shared sub-structures.