Efficient mid-query re-optimization of sub-optimal query execution plans

For a number of reasons, even the best query optimizers can very often produce sub-optimal query execution plans, lead-ing to a significant degradation of performance. This is es-pecially true in databases used for complex decision support queries and/or object-relational databases. In this paper, we describe an algorithm that detects sub-optimality of a query execution plan during query execution and attempts to correct the problem. The basic idea is to collect statis-tics at key points during the execution of a complex query. These statistics are then used to optimize the execution of the query, either by improving the resource allocation for that query, or by changing the execution plan for the re-mainder of the query. To ensure that this does not signifi-cantly slow down the normal execution of a query, the Query Optimizer carefully chooses what statistics to collect, when to collect them, and the circumstances under which to re-optimize the query. We describe an implementation of this algorithm in the Paradise Database System, and we report on performance studies, which indicate that this can result in significant improvements in the performance of complex queries.

OPT++: An Object-Oriented Implementation for Extensible Database Query Optimization

In this paper we describe the design and implementation of OPT++, a tool for Extensible Database Query Optimization that uses an object-oriented design to simplify the task of implementing, extending, and modifying an optimizer. Building an optimizer using OPT++ makes it easy to extend the query algebra (to add new query algebra operators and physical implementation algorithms to the system), easy to change the search space explored, and also easy to change the search strategy used. Furthermore, OPT++ comes equipped with a number of search strategies that are available for use by an Optimizer-- Implementor. OPT++ considerably simplifies both, the task of implementing an optimizer for a new database system, and the task of experimenting with various optimization techniques and strategies to decide what techniques are best suited for that database system. We present the results of performance studies which validate our design and show that, in spite of its flexibility, OPT++ can be used ..

OPT++: An Object-Oriented Implementation for Extensible Database Query Optimization

In this paper we describe the design and implementation of OPT++, a tool for Extensible Database Query Optimization that uses an object-oriented design to simplify the task of implementing, extending, and modifying an optimizer. Building an optimizer using OPT++ makes it easy to extend the query algebra (to add new query algebra operators and physical implementation algorithms to the system), easy to change the search space, and also to change the search strategy. Furthermore, OPT++ comes equipped with a number of search strategies that are available for use by an OI. OPT++ considerably simplifies both, the task of implementing an optimizer for a new database system, and the task of evaluating alternative optimization techniques and strategies to decide what techniques are best suited for that database system. We present the results of a series of performance studies. These results validate our design and show that, in spite of its flexibility, OPT++ can be used to build efficient opti..

The QUIQ Engine: A Hybrid IRDB System

For applications that involve rapidly changing textual data and also require traditional DBMS capabilities, current systems are unsatisfactory. In this paper, we describe a hybrid IR-DB system that serves as the basis for the QUIQConnect product, a collaborative customer support application. We present the novel query paradigm and system architecture, along with performance results.

Client-server paradise

This paper describes the design and implementation of Paradise, a database system designed for handling GIS type of applications. The current version of Paradise, uses a client{server architecture and provides an extended{relational data model for modeling GIS applications. Paradise supports an extended version of SQL and provides a graphical user interface for querying and browsing the database. We also describe the results of benchmarking Paradise using the Sequoia 2000 storage benchmark.