Data Warehouse Evolution: Trade-Offs between Quality and Cost of Query Rewritings

Query rewriting has been used as a query optimization technique for several decades to reduce the computational cost of a query. It has generally been assumed that any rewritten query will generate the identical query result as the original query, in terms of both the query interface and the query extent. Hence, this is called “equivalent query rewriting”. Recently, query rewriting with relaxed semantics has been proposed as a means of retaining the validity of a data warehouse (i.e., materialized queries) in a changing environment [2, 3, 4]. Attributes in the query interface can be classified as essential or dispensable (if it cannot be retained) according to the query definer’s preferences. Similarly, preferences for query extent can be specified, for example, to indicate whether a subset of the original result is acceptable or not. A query rewriting is said to be acceptable if it preserves the essential information of the original query and satisfies the constraint on the view extent. Since each rewriting may preserve the original query to a different degree, a potentially large number of acceptable yet nonequivalent query rewritings may be found. Therefore, we need to systematically select the most promising rewriting out of all possible ones. Research issues that must be answered for solving this problem are outlined below. We have found that the two most important factors influencing the desirability of a query rewriting are: the information preserved by the rewriting w.r.t. the original query result (quality) and the cost of acquiring the query results (cost). A rewriting is more desired than others if it is “semantically close” to the original one and could be acquired economically. We have designed the first analytic model, Quality-Cost Model (QC Model), to assess rewritings on both factors [1]. A rewriting has a better quality in terms of the query