The view-selection problem has an exponential-time lower bound for conjunctive queries and views

The view-selection problem is to design and materialize a set of views over a database schema, such that the choice of views minimizes the cost of evaluating the selected workload of queries, and the combined size of the materialized views does not exceed a prespecified storage limit. Important applications of the view-selection problem include query optimization, data warehouse design, and information integration.We consider the view-selection problem in relational databases, for conjunctive queries and views. Suppose somebody wants to design a view-selection algorithm that outputs a polynomial number of views for all query workloads and storage limits and produces optimal selections of views independently of actual database contents. In previous work it was shown that it is impossible to design such an algorithm when the product (as for nested-loop joins) cost model is used. That is, there exist databases for which the number of views in an optima] viewset is exponential in the size of the database schema and query workload. As a consequence, under the product-cost model the view-selection problem has an exponential-time lower bound.Efficient join algorithms have a cost that is proportional to the sum of the sizes of the input and output relations. In this paper we prove that under the more practical sum-cost model, the view-selection problem also has an exponential time lower bound. As a consequence, under the sum-cost model it is also impossible to come up with a view-selection algorithm that outputs a polynomial number of views for all query workloads and databases, yet produces optimal selections of views.

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