内存数据库中混合工作负载的数据结构

J. Krueger, M. Grund, Martin Boissier, A. Zeier, H. Plattner
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引用次数: 10

摘要

传统上,企业数据管理被划分为独立的系统。在线事务处理(Online Transaction Processing, OLTP)系统通过对完整实体的检索和修改进行优化,专注于日常业务。在线分析处理(OLAP)系统启动对特定属性的查询,因为这些应用程序经过优化,以支持基于从许多实例收集的信息做出决策。同时,硬件和数据库应用程序也在不断改进。例如,当前的主内存大小与面向列的数据组织相结合,提供了全新的可能性,例如对事务性数据进行实时分析查询。特别是主存数据库系统领域的最新发展提出了一个问题,即这些数据库是否能够在一个系统中处理OLAP和OLTP工作负载。本文讨论了使用适当的数据结构管理工作负载和分析的主存数据库系统的需求。
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Data structures for mixed workloads in in-memory databases
Traditionally, enterprise data management is divided into separate systems. Online Transaction Processing (OLTP) systems are focused on the day to day business by being optimized for retrieving and modifying complete entities. Online Analytical Processing (OLAP) systems initiate queries on specific attributes as these applications are optimized to support decision making based on the information gathered from many instances. In parallel both hardware and database applications are subject to steady improvements. For example, today's size of main memory in combination with the column oriented organization of data offer completely new possibilities such as real time analytical ad hoc queries on transactional data. Especially latest development in the area of main memory database systems raises the question whether those databases are capable of handling both OLAP and OLTP workloads in one system. This Paper discusses requirements for main memory database systems managing both workloads and analyses using appropriate data structures.
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