III: Small: Database Algorithms for Modern CPU Memory Hierarchies

III：小型：现代 CPU 内存层次结构的数据库算法

• 批准号: 1422488
• 负责人: Kenneth Ross
• 金额: $ 50万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1422488&HistoricalAwards=false
• 关键词: III; Small; Database; Algorithms; Modern

A modern database server typically runs on a cluster of machines with a large amount of RAM, to ensure fast query responses when the commonly accessed data (or even the whole database) can fit in main memory. Data may reside in remote or local memory, or in one of several levels of cache; each type of memory has its own characteristic size and performance properties. This project will develop query processing algorithms and a query processing system tailored to such memory hierarchies. Analytic database systems have emerged as a key technology for extracting actionable information from "big data" collections ranging from medicine to science to business. Improvements in the performance of core database operations achieved by the project will have impact on many application domains. The project will also contribute to education by contributing technology for use in teaching database system implementation techniques.The project will develop a database architecture with efficient partitioning as the core operation, using different partitioning techniques at each level of the memory hierarchy. In-place partitioning will be employed where appropriate to avoid allocating extra memory, with only a small decrease in partitioning speed. Partitioning will be used as a building block for other operators such as sorting, joins and aggregation. A variety of database algorithms will be implemented, taking advantage of the efficiency of partitioning to perform well at scale. Network transfer volumes will be reduced using specialized join algorithms, since such transfers are likely to be the bottleneck for queries involving large distributed joins. These algorithms will form the basis of a database system prototype to be developed during the course of the project. The project will provide new techniques to exploit modern machines for efficient analytic query processing. The proposed system will significantly improve the throughput of data-intensive queries.For further information see the project web site at: http://www.cs.columbia.edu/~kar/cpumem.html

现代数据库服务器通常在带有大量RAM的机器群上运行，以确保当常见的数据（甚至整个数据库）可以适合主内存时，请确保快速查询响应。数据可能位于远程或本地内存中，也可以存在于几个级别的缓存之一中；每种内存都有其自己的特征大小和性能属性。 该项目将开发查询处理算法和针对此类内存层次结构的查询处理系统。分析数据库系统已成为一种关键技术，用于从医学到科学再到业务的“大数据”收集中提取可行的信息。项目实现的核心数据库操作的性能的改善将对许多应用程序域产生影响。该项目还将通过为教学数据库系统实施技术提供贡献技术来为教育做出贡献。该项目将使用在内存层次结构的每个级别上使用不同的分区技术来开发以有效分区为核心操作的数据库体系结构。在适当的情况下，将采用现场分区，以避免分配额外的内存，而分区速度只有很小的降低。分区将用作其他操作员，例如排序，加入和聚合的构建块。将实现各种数据库算法，利用分区的效率在大规模上表现良好。 网络传输量将使用专门的联接算法减少，因为此类转移可能是涉及大型分布式联接的查询的瓶颈。 这些算法将构成项目过程中要开发的数据库系统原型的基础。该项目将提供新技术来利用现代机器进行有效的分析查询处理。拟议的系统将显着改善数据密集型查询的吞吐量。有关更多信息，请参见项目网站：http：//www.cs.columbia.edu/~kar/~kar/cpumem.html