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Digging Database Statistics and Costs Parameters for Distributed Query Processing

机译:挖掘数据库统计信息和成本参数以进行分布式查询处理

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Cost parameters and database statistics are the basis of query optimization techniques. However, in distributed and heterogeneous database systems, acquiring and treating information in order to help the optimization process are often tasks of a global query processor, which adapts its functionalities to a specific system architecture. Moreover, this acquisition process involves a large number of parameters and requires customized methods to retrieve data from specific sources. DIG (Distributed Information Gatherer) is a provider of data statistics and query costs that, through an independent and flexible service, aims to support global query optimization processing in distributed and heterogeneous database systems over autonomous data sources. We have developed a DIG prototype and experimented it with specific wrappers for a query middleware on both semi-structured data sources and an object DBMS.
机译:成本参数和数据库统计信息是查询优化技术的基础。但是,在分布式和异构数据库系统中,获取和处理信息以帮助优化过程通常是全局查询处理器的任务,全局查询处理器会将其功能适应特定的系统体系结构。此外,该获取过程涉及大量参数,并且需要定制的方法来从特定来源检索数据。 DIG(分布式信息收集器)是数据统计和查询成本的提供者,它通过独立且灵活的服务,旨在支持自治数据源上的分布式和异构数据库系统中的全局查询优化处理。我们已经开发了DIG原型,并针对半结构化数据源和对象DBMS上的查询中间件使用了特定的包装器对其进行了试验。

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