Materialized View Selection: A Survey

This is a draft of my contribution to a book chapter (doi: 10.4018/978-1-60566-816-1.ch005). We mainly categorize and review the existing approaches to materialized view selection. View selection addresses the problem of choosing materialized views in the design process of data warehouses. Informally, it can be stated as, given an estimated query workload and possibly also sets of candidate views, to select a set of views, such that some operation goals (e.g., average query response time, maintenance costs, or both) are optimized and meanwhile some resource constraints are satisfied. View selection, view maintenance, and answering queries using views (Halevy, 2001) comprise a relatively complete framework for query processing in data warehousing. In this section, we discuss the challenges of and solutions to the view selection problem. We first state the formal framework of the view selection problem and some theoretical aspects based on the framework (Section 1). We then describe a taxonomy that we use to classify view selection techniques (Section 2). The main body of view selection approaches in the static setting is then discussed (Section 3), where the query workload is assumed to be known in advance. Finally, dynamic view selection approaches are introduced (Section 4). 1 Theoretical Perspectives We focus on static view selection in this section and start by introducing a model treating the view selection problem as an optimization problem. View selection is handled as an optimization problem, which can be described as a tuple (S, V,M,Q), where S is the schema together with some size estimation model, V is the set of all the possible views to choose from, M is a quantity denoting the space available for materializing views, and Q is a set of queries. The problem is to find a subset of V that optimizes the queries against Q while the storage requirement is no larger than M . The overall evaluation cost is formulated as a weighted sum over Q: E(V ) = Σq∈QE(q, V )× f q where f q denotes the frequency of query q, and E(q, V ) is the minimal possible evaluation cost of q using the selected views V . Besides the cost of queries, view maintenance can be considered in a similar way : U(V ) = Σv∈VU(v)× f v