Making aggregate views self-maintainable

Data in the warehouse can be seen as materialized views generated from the underlying multiple data sources. Materialized views are used to speedup qu ery processing on large amounts of data. These views need to be maintained in response to updates in the source data. This is often done using increme ntal techniques that access data from underlying sources. In the data wareh ousing scenario, accessing base relations can be difficult, sometimes data sources may be unavailable, since these relations are distributed across di fferent sources. For these reasons, the issue of self-maintainability of th e view is an important issue in data warehousing. In this paper we show tha t the warehouse views can be made self-maintainable if some additional rela tions, called auxiliary relations, derived from the intermediate results of the view computation can be materialized in the warehouse. We give an algo rithm for determining what auxiliary relations need to be materialized in o rder to make a materialized view self-maintainable. We then propose an effi cient self-maintainable incremental algorithm that computes the updates to both the materialized view and the additional relations. The primary object ive is to minimize the overall maintenance cost of a given view and the aux iliary relations. One important feature of our algorithm is that it derives the 'exact change' to every materialized additional relation, including th e materialized view, without accessing the view itself. This feature is imp ortant to ensure the correctness of the update to views defined by aggregat e functions, and also important in active database applications where trigg ers are fired by updates to the view. Finally, we compare the maintenance c ost of our incremental algorithm to that of counting algorithm and recomput ing the view from scratch (naive algorithm). (C) 2000 Elsevier Science B.V. All rights reserved.