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Caching Strategies for Data-Intensive Web Sites

机译:缓存数据密集型网站的策略

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Data-intensive Web sites were large volumes of pages whose content is dynamically extracted from a database. Such Web sites have very high software development and maintenance costs and in general offer poor response times due to the heavy interactin with the database system. This paper introduces the Weave management system developed at INRIA, which alleviates the above shortcomings of data-intensive Web sites. Weave relies on the declarative specification of Web sites and offers a number of tools for the easy implementation, deployment and monitoring of the specified site. Weave features a customizable cache system that implements the optimal data materialization strategy according to the Web site's specifics: it can cache database data, XML fragments and HTML files. To explore Weave's performance we have built a Web site based on the TPC/D benchmark database using the WeaveBench test platform. We conducted a number of experiments with various data materialization strategies supported by our system. Results clearly show that in the general case, a mix of different caching policies is required to achieve optimal performance.
机译:数据密集型网站是大量的页面,其内容从数据库动态提取。此类网站具有非常高的软件开发和维护成本,并且通常提供由于数据库系统的重互动引起的响应时间差。本文介绍了在inria开发的编织管理系统,减轻了数据密集型网站的上述缺点。 Weave依赖于网站的声明性规范,并提供了许多工具,用于轻松实现,部署和监视指定站点。 Weave采用可定制的缓存系统,根据网站的细节实现最佳数据实现策略:它可以缓存数据库数据,XML片段和HTML文件。为了探索Weave的性能,我们使用WeaveBench测试平台基于TPC / D基准数据库构建了一个网站。我们进行了许多实验,具有我们系统支持的各种数据实现策略。结果清楚地表明,在一般情况下,需要混合不同的缓存政策来实现最佳性能。

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