As views in a data warehouse become more complex, the view maintenance process can become very complicated and potentially very inefficient. Storing auxiliary views in the warehouse can reduce the complexity and improve the efficiency of view maintenance, and the same auxiliary views can help in efficiently answering lineage tracing queries over the warehouse views.  In this paper, we study the problem of selecting auxiliary views to materialize in order to minimize the total view maintenance and lineage tracing cost. We consider relational views with arbitrary use of aggregation operators, and we define an initial search space for our optimization problem based on a normal form for such view definitions.  We present several auxiliary view selection algorithms, and to study their performance we conduct experiments using the TPC-D benchmark in addition to synthetic view definitions and statistics. The results of our experiments show: (1) the exhaustive algorithm that selects the optimal set of auxiliary views is far too expensive in many cases; (2) two heuristic algorithms that we present select good (often optimal) sets of auxiliary views in a much shorter time; (3) even auxiliary views selected by a very simple algorithm can significantly reduce the overall view maintenance and lineage tracing cost.
['Yingwei Cui', 'Jennifer Widom']
Storing Auxiliary Data for Efficient Maintenance and Lineage Tracing of Complex Views