On-Line Reorganization

在线重组

• 批准号: 9610001
• 负责人: Betty Salzberg
• 金额: $ 23万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-01 至 2001-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9610001&HistoricalAwards=false
• 关键词: Line; Reorganization

The goal of this research project is to design, analyze and simulate restartable algorithms for on-line reorganization in parallel database management systems (DBMSs). The approach includes the description of explicit logging operations to assure consistency and preserve incremental improvements in the face of possible system failures at any site. Each algorithm is carefully detailed to work with standard concurrency and recovery modules in large DBMSs. Most large databases will soon be managed by parallel DBMSs (i.e., DBMSs on clusters of workstations, each managing its own collections of disks, connected by LANs and running the same software), so parallel algorithms are important. Earlier work in a centralized setting, by the Prof. Salzberg and her students Chendong Zou and Allyn Dimock, included algorithms for shrinking sparsely populated B-trees and for moving records (for example, to improve clustering). This project continues this work and expands it to a parallel setting. The project investigates the question of incrementally and lazily updating distributed dictionaries and indexes when records are moved from disks at one site to disks at another. This project represents the only work on on-line reorganization done in an academic setting which considers recovery and logging. Prof. Salzberg collaborates with Svein-Olaf Hvasshovd and Svein-Eric Bratsberg of Telenor Research (Norway's telephone company) using the parallel DBMS ClustRa as a testbed for the algorithmic work. Because this project considers recovery and because of the industrial collaboration, the results of this research are likely to able to be used in online reorganization utilities in commercial parallel DBMSs. ?

本研究计画的目标是设计、分析与模拟可重新启动的演算法，以在平行资料库管理系统（DBMS）中进行线上重组。该方法包括明确的日志操作的描述，以确保一致性，并保持在任何站点可能出现的系统故障的增量改进。每一个算法都被仔细地详细描述，以便与大型DBMS中的标准并发和恢复模块一起工作。大多数大型数据库将很快由并行DBMS管理（即，工作站集群上的DBMS，每个工作站管理自己的磁盘集合，通过局域网连接并运行相同的软件），因此并行算法很重要。Salzberg教授和她的学生Chendong Zou和Allyn Dimock在集中式环境中的早期工作包括缩小稀疏填充的B树和移动记录的算法（例如，以改善聚类）。这个项目继续这项工作，并将其扩展到一个平行的设置。该项目研究了当记录从一个站点的磁盘移动到另一个站点的磁盘时，增量和延迟更新分布式字典和索引的问题。这个项目代表了唯一的在线重组在学术环境中，认为恢复和日志记录。Salzberg教授与Telenor Research（挪威电话公司）的Svein-Olaf Hvashovd和Svein-Eric Bratsberg合作，使用并行DBMS ClustRa作为算法工作的测试平台。因为这个项目考虑了恢复，因为工业合作，这项研究的结果很可能能够被用于在线重组实用程序在商业并行数据库管理系统。 ?