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...

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 ...

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The design of the POSTGRES data model is described. The data model is a relational model that has been extended with abstract data types including user-defined operators and procedures, relation attributes of type procedure, and attribute and procedure inheritance. These mechanism can be used to simulate a wide variety of semantic and object-oriented data modeling constructs including aggregation and generalization, complex objects with shared subobjects, and attributes that reference tuples in other relations. 1. Introduction This paper describes the data model for POSTGRES, a next-generation extensible database management system being developed at the University of California [StR86]. The data model is based on the idea of extending the relational model developed by Codd [Cod70] with general mechanisms that can be used to simulate a variety of semantic data modeling constructs. The mechanisms include: 1) abstract data types (ADT's), 2) data of type procedure, and 3) rules. These me...

This paper deals with the transaction management aspects of the R * distributed database system. It concentrates primarily on the description of the R * commit protocols, Presumed Abort (PA) and Presumed Commit (PC). PA and PC are extensions of the well-known, two-phase (2P) commit protocol. PA is optimized for read-only transactions and a class of multisite update transactions, and PC is optimized for other classes of multisite update transactions. The optimizations result in reduced intersite message traffic and log writes, and, consequently, a better response time. The paper also discusses R*‘s approach toward distributed deadlock detection and resolution.

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...

Abstract. In this paper, we describe the design and implementation of the ADMS query optimizer. This optimizer integrates query matching into optimization and generates more e cient query plans using cached results. It features data caching and pointer caching, alternative cache replacement strategies, and di erent cache update methods. A comprehensive set of experiments were conducted using a benchmark database and synthetic queries. The results showed that pointer caching and dynamic cache update strategies substantially saved query execution time and, thus, increased query throughput under situations with fair query correlation and update load. The requirement of the disk cache space is relatively small, and the extra optimization overhead introduced is more than o set by the time saved in query evaluation. 1

Many papers have examined how to efficiently export a materialized view but to our knowledge none have studied how to efficiently import one. To import a view, i.e., to install a stream of updates, a real-time database system must process new updates in a timely fashion to keep the database "fresh," but at the same time must process transactions and ensure they meet their time constraints. In this paper, we discuss the various properties of updates and views (including staleness) that affect this tradeoff. We also examine, through simulation, four algorithms for scheduling transactions and installing updates in a soft real-time database. Keywords: soft real-time, temporal databases, materialized views, updates. 1 Introduction The problem we study in this paper arose during the ongoing implementation of the STRIP real-time database system. 1 This system [2] provides traditional database services (e.g., SQL, indexing, recovery) with real-time facilities (e.g., transaction deadlines,...

The problem of allocating the data of a database to the sites of a communication network is investigated. This problem deviates from the well-known file allocation problem in several aspects. First, the objects to be allocated are not known a priori; second, these objects are accessed by schedules that contain transmissions between objects to produce the result. A model that makes it possible to compare the cost of allocations is presented, the cost can be computed for different cost functions and for processing schedules produced by arbitrary query processing algorithms. For minimizing the total transmission cost, a method is proposed to determine the fragments to be allocated from the relations in the conceptual schema and the queries and updates executed by the users. For the same cost function, the complexity of the data allocation problem is investigated. Methods for obtaining optimal and heuristic solutions under various ways of computing the cost of an allocation are presented and compared. Two different approaches to the allocation management problem are presented and their merits are discussed.

We present a change-centric method to manage versions in a Web WareHouse of XML data. The starting points is a sequence of snapshots of XML documents we obtain from the web. By running a diff algorithm, we compute the changes between two consecutive versions. We then represent the sequence using a novel representation of changes based on completed deltas and persistent identifiers. We present the foundations of the logical representation and some aspects of the physical storage policy. The work presented here was developed in the context of the Xyleme project of massive XML warehouse for XML data from the Web. It has been implemented and tested. We briefly discuss the implementation.