基于模板的web服务器上的高效资源管理

Eli Courtwright, C. Yue, Haining Wang
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引用次数: 3

摘要

在多线程web服务器中最常用的请求处理模型是线程每请求,其中一个单独的线程被绑定为每个web请求服务。然而,随着在现代web服务器中使用模板技术生成动态内容的流行,这种传统的请求处理模型已经落后,无法为基于模板的web应用程序提供有效的资源管理支持。更准确地说,尽管基于模板的动态网页的内容代码和表示代码可以被分离到不同的文件中,但它们仍然由同一个线程处理。因此,web服务器资源,特别是数据库连接资源,无法得到有效的共享和利用。在本文中,我们提出了一种新的请求调度方法,该方法将单个web请求由多个线程池中的不同线程服务,以解析请求头、执行数据库查询和呈现模板。该方案保证了在呈现模板或提供静态内容时宝贵的数据库连接的高利用率。我们在CherryPy(一个典型的支持模板的多线程web服务器)中实现了所提出的方案,并使用Django web模板实现的标准TPC-W基准测试来评估其性能。我们的评估表明,该方案将大多数网页的平均响应时间减少了两个数量级,并在高负载下将web服务器的总体吞吐量提高了31.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient resource management on template-based web servers
The most commonly used request processing model in multithreaded web servers is thread-per-request, in which an individual thread is bound to serve each web request. However, with the prevalence of using template techniques for generating dynamic contents in modern web servers, this conventional request processing model lags behind and cannot provide efficient resource management support for template-based web applications. More precisely, although content code and presentation code of a template-based dynamic web page can be separated into different files, they are still processed by the same thread. As a result, web server resources, especially database connection resources, cannot be efficiently shared and utilized. In this paper, we propose a new request scheduling method, in which a single web request is served by different threads in multiple thread pools for parsing request headers, performing database queries, and rendering templates. The proposed scheme ensures the high utilization of the precious database connections, while templates are being rendered or static contents are being served. We implemented the proposed scheme in CherryPy, a representative template-enabled multithreaded web server, and we evaluated its performance using the standard TPC-W benchmark implemented with the Django web templates. Our evaluation demonstrates that the proposed scheme reduces the average response times of most web pages by two orders of magnitude and increases the overall web server throughput by 31.3%under heavy loads.
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