The problem of answering queries using views is to find efficient methods of answering a query using a set of previously defined materialized views over the database, rather than accessing the database relations. The problem has recently received significant attention because of its relevance to a wide variety of data management problems. In query optimization, finding a rewriting of a query using a set of materialized views can yield a more efficient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, finding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views over a mediated schema. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the different applications of the problem, the algorithms proposed to solve it and the relevant theoretical results.

We consider the problem of computing answers to queries by using materialized views. Aside from its potential in optimizing query evaluation, the problem also arises in applications such as Global Information Systems, Mobile Computing and maintaining physical data independence. We consider the problem of finding a rewriting of a query that uses the materialized views, the problem of finding minimal rewritings, and finding complete rewritings (i.e., rewritings that use only the views). We show that all the possible rewritings can be obtained by considering containment mappings from the views to the query, and that the problems we consider are NP-complete when both the query and the views are conjunctive and don't involve built-in comparison predicates. We show that the problem has two independent sources of complexity (the number of possible containment mappings, and the complexity of deciding which literals from the original query can be deleted). We describe a polynomial time algorith...

While much work has addressed the problem of maintaining materialized views, the important question of optimizing queries in the presence of materialized views has not been resolved. In this paper, we analyze the optimization question and provide a comprehensive and efficient solution. Our solution has the desirable property that it is a simple generalization of the traditional query optimization algorithm. 1 Introduction The idea of using materialized views for the benefit of improved query processing has been proposed in the literature more than a decade ago. In this context, problems such as definition of views, composition of views, maintenance of views [BC79, KP81, SI84, BLT86, CW91, Rou91, GMS93] have been researched but one topic has been conspicuous by its absence. This concerns the problem of the judicious use of materialized views in answering a query. It may seem that materialized views should be used to evaluate a query whenever they are applicable. In fact, blind applicat...

We propose a semantic model for client-side caching and replacement in a client-server database system and compare this approach to page caching and tuple caching strategies. Our caching model is based on, and derives its advantages from, three key ideas. First, the client maintains a semantic description of the data in its cache,which allows for a compact specification, as a remainder query, of the tuples needed to answer a query that are not available in the cache. Second, usage information for replacement policies is maintained in an adaptive fashion for semantic regions, which are associated with collections of tuples. This avoids the high overheads of tuple caching and, unlike page caching, is insensitive to bad clustering. Third, maintaining a semantic description of cached data enables the use of sophisticated value functions that incorporate semantic notions of locality, not just LRU or MRU, for cache replacement. We validate these ideas with a detailed performance study that i...

Complex queries are becoming commonplace, with the growing use of decision support systems. These complex queries often have a lot of common sub-expressions, either within a single query, or across multiple such queries run as a batch. Multi-query optimization aims at exploiting common subexpressions to reduce evaluation cost. Multi-query optimization has hither-to been viewed as impractical, since earlier algorithms were exhaustive, and explore a doubly exponential search space. In this paper we demonstrate that multi-query optimization using heuristics is practical, and provides significant benefits. We propose three cost-based heuristic algorithms: Volcano-SH and Volcano-RU, which are based on simple modifications to the Volcano search strategy, and a greedy heuristic. Our greedy heuristic incorporates novel optimizations that improve efficiency greatly. Our algorithms are designed to be easily added to existing optimizers. We present a performance study comparing the algo...

We consider a variant of the view maintenance problem: How does one keep a materialized view up-to-date when the view definition itself changes? Can one do better than recomputing the view from the base relations? Traditional view maintenance tries to maintain the materialized view in response to modifications to the base relations; we try to “adapt ” the view in response to changes in the view definition. Such techniques are needed for applications where the user can change queries dynamically and see the changes in the results fast. Data archaeology, data visualization, and dynamic queries are examples of such applications. We consider all possible redefinitions of SQL SELECT-FROM-UHERE-GROUPBY, UNION, and EXCEPT views, and show how these views can be adapted using the old materialization for the cases where it is possible to do so. We identify extra information that can be kept with a materialization to facilitate redefinition. Multiple simultaneous changes to a view can be handled without necessarily materializing intermediate results. We iden-tify guidelines for users and database administrators that can be used to facilitate efficient view adaptation. 1

We present novel algorithms for the problem of using materialized views to compute answers to SQL queries with grouping and aggregation, in the presence of multiset tables. In addition to its obvious potential in query optimization, this problem is important in many applications, such as data warehousing, very large transaction recording systems, global information systems and mobile computing, where access to local or cached materialized views may be cheaper than access to the underlying database. Our contributions are the following: First, we show that in the case where the query has grouping and aggregation but the views do not, a view is usable in answering a query only if there is an isomorphism between the view and a portion of the query. Second, when the views also have grouping and aggregation we identify conditions under which the aggregation information present in a view is sufficient to perform the aggregation computations required in the query. The algorithms we describe fo...

We investigate the problem of rewriting queries with aggregate operators using views that mayormay not contain aggregate operators. A rewriting of a query is a second query that uses view predicates such that evaluating first the views and then the rewriting yields the same result as evaluating the original query. In this sense, the original query and the rewriting are equivalent modulo the view definitions. The queries and views we consider correspond to unnested SQL queries, possibly with union, that employ the operators min, max, count, and sum. Our approach is based on syntactic characterizations of the equivalence of aggregate queries. One contribution of this paper are characterizations of the equivalence of disjunctive aggregate queries, which generalize our previous results for the conjunctive case. For each operator α, we introduce several types of queries using views as candidates for rewritings. We unfold such a candidate by replacing each occurrence of a view predicate with ...

The problem of answering queries using views is to nd ecient methods of answering a query using a set of previously materialized views over the database, rather than accessing the database relations. The problem has recently received signicant attention because of its relevance to a wide variety of data management problems. In query optimization, nding a rewriting of a query using a set of materialized views can yield a more ecient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, nding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the dierent applications of the problem, the algorithms proposed to solve it and the relevant theoretical results.

Location-dependent applications are becoming very popular in mobile environments. To improve system performance and facilitate disconnection, caching is crucial to such applications. In this paper, a semantic caching scheme is used to access location dependent data in mobile computing. We first develop a mobility model to represent the moving behaviors of mobile users and formally define location dependent queries. We then investigate query processing and cache management strategies. The performance of the semantic caching scheme and its replacement strategy FAR is evaluated through a simulation study. Our results show that semantic caching is more flexible and effective for use in LDD applications than page caching, whose performance is quite sensitive to the database physical organization. We also notice that the semantic cache replacement strategy FAR, which utilizes the semantic locality in terms of locations, performs robustly under different kinds of workloads.