In this paper we motivate and describe materialized views, their applications, and the problems and techniques for their maintenance. We present a taxonomy of view maintenanceproblems basedupon the class of views considered, upon the resources used to maintain the view, upon the types of modi#cations to the base data that areconsidered during maintenance, and whether the technique works for all instances of databases and modi#cations. We describe some of the view maintenancetechniques proposed in the literature in terms of our taxonomy. Finally, we consider new and promising application domains that are likely to drive work in materialized views and view maintenance. 1 Introduction What is a view? A view is a derived relation de#ned in terms of base #stored# relations. A view thus de#nes a function from a set of base tables to a derived table; this function is typically recomputed every time the view is referenced. What is a materialized view? A view can be materialized by storin...

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...

Currently, a variety of information retrieval systems are available to potential users. These services are provided by commercial enterprises (such as Dow Jones [6] and The Source [7]), while others are research efforts (the Boston Community Information System [S]). While in many cases these systems are accessed from personal computers, typically no advantage is taken of the computing resources of those machines (such as local processing and storage). In this paper we explore the possibility of using the user’s local storage capabilities to cache data at the user’s site. This would improve the response time of user queries albeit at the cost of incurring the overhead required in maintaining multiple copies. In order to reduce this overhead it may be appropriate to allow copies to diverge in a controlled fashion. This would not only make caching less costly, but would also make it possible to propagate updates to the copies more efficiently, for example, when the system is lightly loaded, when communication tariffs are lower, or by batching updates together. Just as importantly, it also makes it possible to access the copies even when the communication lines or the central site are down. Thus, we introduce the notion of quasi-copies, which embodies the ideas sketched above. We also define the types of deviations that seem useful, and discuss the available implementation strategies.

Query processing can be sped up by keeping frequently accessed users' views materialized. However, the need to access base relations in response to queries can be avoided only if the materialized view is adequately maintained. We propose a method in which all database updates to base relations are first filtered to remove from consideration those that cannot possibly affect the view. The conditions given for the detection of updates of this type, called irrelevant updates, are necessary and sufficient and are independent of the database state. For the remaining database updates, a differential algorithm can be applied to re-evaluate the view expression. The algorithm proposed exploits the knowledge provided by both the view definition expression and the database update operations. 1 Introduction In a relational database system, a database may be composed of both base and derived relations. A de- This work was supported in part by scholarship No. 35957 from Consejo Nacional de Cien...

We study the problem of efficient maintenance of materialized views that may contain duplicates. This problem is particularly important when queries against such views involve aggregate functions, which need duplicates to produce correct results. Unlike most work on the view maintenance problem that is based on an algorithmic approach, our approach is algebraic and based on equational reasoning. This approach has a number of advantages: it is robust and easily extendible to new language constructs, it produces output that can be used by query optimizers, and it simpli es correctness proofs. We use a natural extension of the relational algebra operations to bags (multisets) as our basic language. We present an algorithm that propagates changes from base relations to materialized views. This algorithm is based on reasoning about equivalence of bag-valued expressions. We prove that it is correct and preserves a certain notion of minimality that ensures that no unnecessary tuples are computed. Although it is generally only a heuristic that computing changes to the view rather than recomputing the view from scratch is more efficient, we prove results saying that under normal circumstances one should expect the change propagation algorithm to be significantly faster and more space efficient than complete recomputing of the view. We also show that our approach interacts nicely with aggregate functions, allowing their correct evaluation on views that change.

Consider a database containing not only base relations but also stored derived relations (also called materialized or concrete views). When a base relation is updated, it may also be necessary to update some of the derived relations. This paper gives sufficient and necessary conditions for detecting when an update of a base relation cannot affect a derived relation (an irrelevant update), and for detecting when a derived relation can be correctly updated using no data other than the derived relation itself and the given update operation (an autonomously computable update). The class of derived relations considered is restricted to those defined by PSJ-expressions, that is, any relational algebra expression constructed from an arbitrary number of project, select and join operations (but containing no self-joins). The class of update operations consists of insertions, deletions, and modifications, where the set of tuples to be deleted or modified is specified by a selection condition on ...

Database updates are small and incremental compared to database contents. It is therefore desirable that recomputations of active relational expressions -- such as views, derived data, integrity constraints, active queries, and monitors -- can be performed incrementally as well. We present an efficient algorithm for the incremental recomputation of active relational expressions based on finite differencing techniques. Database updates are modeled as incremental changes to database relations, and the algorithm derives, by update propagation, the minimal incremental relational expressions that need recomputation. The algorithm has applications in the maintenance of materialized views and derived data, the checking of integrity constraints, and the evaluation of active queries and monitors. Keywords--- Active Queries, Derived Data, Finite Differencing, Incremental Recomputation, Integrity Constraints, Monitors, Updates, Views I. Introduction Database management systems need to perform ...

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We present an exception handling facility suitable for languages used to implement database-intensive Information Systems. Such a mechanism facilitates the development and maintenance of more flexible software systems by supporting the abstraction of details concerning special or abnormal occurrences. We consider the type constraints imposed by the schema as well as various semantic integrity assertions to be normalcy conditions, and the key contribution of this work is to allow exceptions to these constraints to persist. To achieve this, we propose solutions to a range of problems, including sharing and computing with exceptional information, exception handling by users, the logic of constraints with exceptions, and implementation issues. We also illustrate the use of exception handling in dealing with null values, estimates, and measurements. Keywords and phrases: semantic integrity, violations of type constraints, exception handling, accommodating exceptions, conceptual models CR ...

Data warehouses contain large amounts of information, often collected from a variety of independent sources. Decisionsupport functions in a warehouse, such as on-line analytical processing (OLAP), involve hundreds of complex aggregate queries over large volumes of data. It is not feasible to compute these queries by scanning the data sets each time. Warehouse applications therefore build a large number of summary tables, or materialized aggregate views, to help them increase the system performance. As changes, most notably new transactional data, are collected at the data sources, all summary tables at the warehouse that depend upon this data need to be updated. Usually, source changes are loaded into the warehouse at regular intervals, usually once a day, in a batch window, and the warehouse is made unavailable for querying while it is updated. Since the number of summary tables that need to be maintained is often large, a critical issue for data warehousing is how to maintain the su...