A methodology for managing database and code changes in a regression testing framework

R. Salama, J. McGuire, Michael Rosenberg
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引用次数: 1

Abstract

Large system development typically involves changes to code and database components. In these environments, testing continues to be the biggest challenge. Since release cycles include both database and code changes, thorough testing of existing schemas and code base is paramount. Code needs to be tested with a static database, database changes need to be tested on a static code base, and finally, both changes need to be tested together. In this paper we present the testing framework built during the development of Morgan Stanley's enterprise-wide time-series database, Horizon. The database, built using Kx's KDB+/Q, holds both tick-by-tick data originating from real-time feeds as well as periodic data received at regular intervals from vendors. The plant consists of several hundred cooperating processes which connect to real-time feeds, create in-memory databases, persist in-memory databases to disk on a regular basis, manage data set locations, and service client connections. At present, the database plant's size is approximately 1PB with an anticipated growth of .5PB/year.
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一种在回归测试框架中管理数据库和代码更改的方法
大型系统开发通常涉及对代码和数据库组件的更改。在这些环境中,测试仍然是最大的挑战。由于发布周期包括数据库和代码更改,因此对现有模式和代码库进行彻底测试是至关重要的。代码需要使用静态数据库进行测试,数据库更改需要在静态代码库上进行测试,最后,这两种更改需要一起进行测试。在本文中,我们提出了在摩根斯坦利的企业级时间序列数据库Horizon开发过程中构建的测试框架。该数据库使用Kx的KDB+/Q构建,既保存来自实时提要的逐点数据,也保存从供应商定期接收的定期数据。该工厂由数百个协作进程组成,这些进程连接到实时提要、创建内存数据库、定期将内存数据库持久化到磁盘、管理数据集位置和服务客户机连接。目前,数据库工厂的规模约为1PB,预计每年增长0.5 pb。
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