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High contention in a stock trading database: a case study

机译:股票交易数据库中的高争用:一个案例研究

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Though in general, current database systems adequately support application development and operation for online transaction processing (OLTP), increasing complexity of applications and throughput requirements reveal a number of weaknesses with respect to the data model and implementation techniques used. By presenting the experiences gained from a case study of a large, high volume stock trading system, representative for a broad class of OLTP applications, it is shown, that this particularly holds for dealing with high frequency access to a small number of data elements (hot spots). As a result, we propose extended data types and several novel mechanisms, which are easy to use and highly increase the expressional power of transaction oriented programming, that effectively cope with hot spots. Moreover, their usefulness and their ability to increased parallelism is exemplified by the stock trading application.

机译:虽然通常,当前的数据库系统充分支持在线事务处理(OLTP)的应用程序开发和操作,但是应用程序的复杂性和吞吐量要求的提高揭示了在使用的数据模型和实现技术方面的许多弱点。通过展示从大型,大量股票交易系统的案例研究中获得的经验,该案例代表了OLTP应用程序的广泛类别,它表明,这尤其适用于处理对少量数据元素的高频访问(热点)。结果,我们提出了扩展的数据类型和几种新颖的机制,这些机制易于使用并大大提高了面向事务的编程的表达能力,可以有效地应对热点问题。此外,通过股票交易应用可以例证它们的有用性和增强并行性的能力。

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