Updating derived relations: detecting irrelevant and autonomously computable updates

Abstract

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 expressions 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 attributes of the relation being updated.

Query evaluation techniques for large databases

“…The next more sophisticated form of precomputation are inversions as provided in System R's "0 th " prototype [Chamberlin et al 1981a [Blakeley, Coburn, and Larson 1989;Blakeley and Martin 1990;Larson and Yang 1985;Medeiros and Tompa 1985;Tompa and Blakeley 1988;Yang and Larson 1987]. Their hope was to speed relational query processing by using derived data, possibly without storing all base data, and ensuring that their maintenance overhead would be less than their benefits in faster query processing.…”

Destabilizers and independence of XML updates

“…Static independence analysis of queries and updates has been explored both in the context of relational databases [8,23] and XML [2,27,26]. For SQL, a crude independence analysis often suffices, checking whether the relation and field names in the upPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.…”

Models and issues in data stream systems

“…Of particular importance is work on self-maintenance [15,45,71]-ensuring that enough data has been saved to maintain a view even when the base data is unavailable-and the related problem of data expiration [36]determining when certain base data can be discarded without compromising the ability to maintain a view. Nevertheless, several differences exist between materialized views and continuous queries in the data stream context: continuous queries may stream rather than store their results, they may deal with append-only input data, they may provide approximate rather than exact answers, and their processing strategy may adapt as characteristics of the data streams change.…”