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Flexible and adaptable buffer management techniques for database management systems

机译:用于数据库管理系统的灵活且适应性强的缓冲区管理技术

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The problem of buffer management in database management systems is concerned with the efficient main memory allocation and management for answering database queries. Previous works on buffer allocation are based either exclusively on the availability of buffers at runtime or on the access patterns of queries. In this paper, we first propose a unified approach for buffer allocation in which both of these considerations are taken into account. Our approach is based on the notion of marginal gains which specify the expected reduction in page faults by allocating extra buffers to a query. Then, we extend this approach to support adaptable buffer allocation. An adaptable buffer allocation algorithm automatically optimizes itself for the specific query workload. To achieve this adaptability, we propose using runtime information, such as the load of the system, in buffer allocation decisions. Our approach is to use a simple queuing model to predict whether a buffer allocation will improve the performance of the system. Thus, this paper provides a more theoretical basis for buffer allocation. Simulation results show that our methods based on marginal gains and our predictive methods consistently outperform existing allocation strategies. In addition, the predictive methods have the added advantage of adjusting their allocation to changing workloads.
机译:数据库管理系统中的缓冲区管理问题与有效的主内存分配和用于回答数据库查询的管理有关。先前有关缓冲区分配的工作完全基于运行时缓冲区的可用性或查询的访问模式。在本文中,我们首先提出了一种统一的缓冲区分配方法,其中考虑了这两个方面。我们的方法基于边际收益的概念,该边际收益通过为查询分配额外的缓冲区来指定预期的页面错误减少。然后,我们将这种方法扩展为支持自适应缓冲区分配。自适应的缓冲区分配算法可针对特定查询工作量自动优化自身。为了实现这种适应性,我们建议在缓冲区分配决策中使用运行时信息(例如系统负载)。我们的方法是使用简单的排队模型来预测缓冲区分配是否会提高系统性能。因此,本文为缓冲区分配提供了更多的理论依据。仿真结果表明,基于边际收益的方法和预测方法始终优于现有的分配策略。此外,预测方法还具有调整其分配以适应不断变化的工作负载的优势。

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