CAREER: Designing a Predictable Database - An Overlooked Virtue

四十年来对数据库系统的研究主要集中在提高平均原始性能上。这种对更快性能的竞争忽略了数据库管理系统的可预测性，这是可以理解的。然而，随着数据库系统变得越来越复杂，其不稳定和不可预测的性能已成为数据库用户和管理员都面临的主要挑战。随着任务关键型业务应用程序对其数据库的依赖日益增加，维护高水平的数据库性能（即服务水平保证）现在比以往任何时候都更加重要。云用户发现，由于当今数据库的高度非线性和不可预测的特性，提供和调优数据库实例非常具有挑战性。即使对于已部署的数据库，性能调优在某种程度上也已经变成了一种神秘的艺术，使合格的数据库管理员成为一种可怕的资源。在这个项目中，我们恢复了数据库系统设计中缺失的可预测性的优点。首先，我们以有原则的方式量化数据库中不确定性的主要来源。然后，通过重新思考数据库系统的传统设计，我们构建了新一代数据库，这些数据库在其查询处理的各个阶段（从物理设计到内存管理和查询调度）中将可预测性视为头等公民。此外，为了适应现有的数据库系统（它们在设计上是不可预测的），我们提供了有效的工具和方法来更准确地预测它们的性能。以自底向上的方式和有原则的方式构建可预测的数据库，为改进现有数据库产品提供了很好的见解，并且可以推动未来数据库设计和实现方式的根本转变。有关该项目的更多信息，请访问https://web.eecs.umich.edu/~mozafari/predictabledb

Four decades of research on database systems has mostly focused on improving average raw performance. This competition for faster performance has, understandably, neglected predictability of our database management systems. However, as database systems have become more complex, their erratic and unpredictable performance has become a major challenge facing database users and administrators alike. With the increasing reliance of mission-critical business applications on their databases, maintaining high levels of database performance (i.e., service level guarantees) is now more important than ever. Cloud users find it challenging to provision and tune their database instances, due to the highly non-linear and unpredictable nature of today's databases. Even for deployed databases, performance tuning has become somewhat of a black art, rendering qualified database administrators a scare resource.In this project, we restore the missing virtue of predictability in the design of database systems. First, we quantify the major sources of uncertainty in a database in a principled manner. Then, by rethinking the traditional design of a database system, we architect a new generation of databases that treat predictability as a first class-citizen in their various stages of query processing, from physical design to memory management and query scheduling. Moreover, to accommodate existing database systems (which are not predictable by design), we provide effective tools and methodologies for predicting their performance more accurately. Building a predictable database in a bottom-up fashion and in a principled manner, offers great insight into improving existing database products and can instigate a radical shift in the way that future databases are designed and implemented. For more information on this project, please visit https://web.eecs.umich.edu/~mozafari/predictabledb