. Global information systems involve a large number of information sources distributed over computer networks. The variety of information sources and disparity of interfaces makes the task of easily locating and efficiently accessing information over the network very cumbersome. We describe an architecture for global information systems that is especially tailored to address the challenges raised in such an environment, and distinguish our architecture from architectures of multidatabase and distributed database systems. Our architecture is based on presenting a conceptually unified view of the information space to a user, specifying rich descriptions of the contents of the information sources, and using these descriptions for optimizing queries posed in the unified view. The contributions of this paper include: (1) we identify aspects of site descriptions that are useful in query optimization; (2) we describe query optimization techniques that minimize the number of information source...

There has been extensive work in query optimization since the early ‘70s. It is hard to capture the breadth and depth of this large body of work in a short article. Therefore, I have decided to focus primarily on the optimization of SQL queries in relational database systems and present my biased and incomplete view of this field. The goal of this article is not to be comprehensive, but rather to explain the foundations and present samplings of significant work in this area. I would like to apologize to the many contributors in this area whose work I have failed to explicitly acknowledge due to oversight or lack of space. I take the liberty of trading technical precision for ease of presentation. 2.

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...

Object-Relational database management systems allow knowledgeable users to de ne new data types, as well as new methods (operators) for the types. This exibility produces an attendant complexity, which must be handled in new ways for an Object-Relational database management system to be e cient. In this paper we study techniques for optimizing queries that contain time-consuming methods. The focus of traditional query optimizers has been on the choice of join methods and orders; selections have been handled by \pushdown " rules. These rules apply selections in an arbitrary order before as many joins as possible, using the assumption that selection takes no time. However, users of Object-Relational systems can embed complex methods in selections. Thus selections may take signi cant amounts of time, and the query optimization model must be enhanced. In this paper, we carefully de ne a query cost framework that incorporates both selectivity and cost estimates for selections. We develop an algorithm called Predicate Migration, and prove that it produces optimal plans for queries with expensive methods. We then describe our implementation of Predicate Migration in the commercial Object-Relational database management system Illustra, and discuss practical issues that a ect our earlier assumptions. We compare Predicate Migration to a variety of simpler optimization techniques, and demonstrate that Predicate Migration is the best general solution to date. The alternative techniques we presentmaybe useful for constrained workloads.

This paper concentrates on query unnesting (also known as query decorrelation), an optimization that, even though improves performance considerably, is not treated properly (if at all) by most OODB systems. Our framework generalizes many unnesting techniques proposed recently in the literature and is capable of removing any form of query nesting using a very simple and efficient algorithm. The simplicity of our method is due to the use of the monoid comprehension calculus as an intermediate form for OODB queries. The monoid comprehension calculus treats operations over multiple collection types, aggregates, and quantifiers in a similar way, resulting in a uniform way of unnesting queries, regardless of their type of nesting.

We introduce a new constraint domain, aggregation constraints, that is useful in database query languages, and in constraint logic programming languages that incorporate aggregate functions. We formally study the fundamental problem of determining if a conjunction of aggregation constraints is satisfiable, and show that, for many classes of aggregation constraints, the problem is undecidable. We describe a complete and minimal axiomatization of aggregation constraints, for the SQL aggregate functions min, max, sum, count and average, over a non-empty, finite multiset on several domains. This axiomatization helps identify classes of aggregation constraints for which the satisfiability check is efficient. We present a polynomial-time algorithm that directly checks for satisfiability of a conjunction of aggregation range constraints over a single multiset; this is a practically useful class of aggregation constraints. We discuss the relationships between aggregation constraints over a non...

. Complex queries, with aggregates, views and nested subqueries are important in decision-support applications. Such queries are represented as multi-block queries where a query block may be a view definition containing aggregates or a correlated nested subquery. Beyond transformations that propagate predicates across blocks, the problem of optimizing such queries has not been addressed adequately. In this paper, we show how such queries can be optimized in a cost-based fashion. The crux of our solution is a careful treatment of group-by and aggregation operators that occur among views. 1 Introduction Complex queries, with views containing aggregates and nested subqueries, are important in decision-support applications (e.g., see TPC-D benchmark). Costbased optimization of such queries cannot be handled by most of the existing optimizers. An aggregate view is a SQL Select-Project-Join query with a group-by clause In this paper, we address the problem of cost-based optimization of que...

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This paper investigates how the vision of the Semantic Web can be carried over to the realm of email. We introduce a general notion of semantic email, in which an email message consists of an RDF query or update coupled with corresponding explanatory text. Semantic email opens the door to a wide range of automated, email-mediated applications with formally guaranteed properties. In particular, this paper introduces a broad class of semantic email processes. For example, consider the process of sending an email to a program committee, asking who will attend the PC dinner, automatically collecting the responses, and tallying them up. We define both logical and decision-theoretic models where an email process is modeled as a set of updates to a data set on which we specify goals via certain constraints or utilities. We then describe a set of inference problems that arise while trying to satisfy these goals and analyze their computational tractability. In particular, we show that for the logical model it is possible to automatically infer which email responses are acceptable w.r.t. a set of constraints in polynomial time, and for the decision-theoretic model it is possible to compute the optimal message-handling policy in polynomial time. Finally, we discuss our publicly available implementation of semantic email and outline research challenges in this realm.

New applications of information systems, such as electronic commerce and healthcare information systems, need to integrate a large number of heterogeneous databases over computer networks. Answering a query in these applications usually involves selecting relevant information sources and generating a query plan to combine the data automatically. As significant progress has been made in source selection and plan generation, the critical issue has been shifting to query optimization. This paper presents a semantic query optimization (SQO) approach to optimizing query plans of heterogeneous multidatabase systems. This approachprovides global optimization for query plans as well as local optimization for subqueries that retrieve data from individual database sources. An important feature of our local optimization algorithm is that weprove necessary and sufficient conditions to eliminate an unnecessary join in a conjunctive query of arbitrary join topology. This feature allows our...