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Journal ArticleDOI

Dynamic query evaluation plans

Goetz Graefe, +1 more
- Vol. 18, Iss: 2, pp 358-366
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TLDR
This work aims at developing criteria when re Optimization is required, how these criteria can be implemented efficiently, and how reoptimization can be avoided by using a new technique called dynamic query evaluation plans.
Abstract
In most database systems, a query embedded in a program written in a conventional programming language is optimized when the program is compiled. The query optimizer must make assumptions about the values of the program variables that appear as constants in the query, the resources that can be committed to query evaluation, and the data in the database. The optimality of the resulting query evaluation plan depends on the validity of these assumptions. If a query evaluation plan is used repeatedly over an extended period of time, it is important to determine when reoptimization is necessary. Our work aims at developing criteria when reoptimization is required, how these criteria can be implemented efficiently, and how reoptimization can be avoided by using a new technique called dynamic query evaluation plans. We experimentally demonstrate the need for dynamic plans and outline modifications to the EXODUS optimizer generator required for creating dynamic query evaluation plans.

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Journal ArticleDOI

Query evaluation techniques for large databases

TL;DR: This survey describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.
Journal ArticleDOI

The state of the art in distributed query processing

TL;DR: The paper presents the “textbook” architecture for distributed query processing and a series of techniques that are particularly useful for distributed database systems, and discusses different kinds of distributed systems such as client-server, middleware (multitier), and heterogeneous database systems and shows how query processing works in these systems.
Proceedings ArticleDOI

CrowdDB: answering queries with crowdsourcing

TL;DR: The design of CrowdDB is described, a major change is that the traditional closed-world assumption for query processing does not hold for human input, and important avenues for future work in the development of crowdsourced query processing systems are outlined.
Proceedings ArticleDOI

An overview of query optimization in relational systems

TL;DR: 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 of query optimization.
References
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Journal ArticleDOI

Decomposition—a strategy for query processing

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Proceedings ArticleDOI

Making smalltalk a database system

TL;DR: The GemStone data model as discussed by the authors is a set-theoretic data model in an object-oriented programming environment that supports path expressions, declarative semantics and object history in the OPAL language.
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