EAGER: Rapid Updates and Snapshot-Based Queries Using Multicore Processors

EAGER：使用多核处理器进行快速更新和基于快照的查询

• 批准号: 1049898
• 负责人: Kenneth Ross
• 金额: $ 15万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1049898&HistoricalAwards=false
• 关键词: EAGER; Rapid; Updates; Snapshot; Based

Applications such as traffic monitoring, mobile user management, and sensor networks need to process large volumes of updates while supporting on-line analytic queries. With large amounts of RAM, single machines are potentially able to manage hundreds of millions of items. With multiple hardware threads, as many as 64 on modern commodity multicore chips, many operations can be processed concurrently.Processing queries and updates concurrently can cause interference. Queries need to see a consistent database state, meaning that at least some of the time, updates will need to wait for queries to complete. To address this problem, a variety of solutions are explored in which a RAM-resident snapshot of the database is taken at various points in time. Analytic queries operate over the snapshot, eliminating interference, but allowing answers to be slightly out of date. Several different snapshot creation methods are being developed and studied, with the goal of being able to create snapshots rapidl(e.g., in fractions of a second) while minimizing the overhead on update processing.These problems are studied both for traditional server machines, as well as for multicore mobile devices. By keeping personalized, up to date data on a user's mobile device, a wide range of potential new applications could be supported while avoiding the privacy concerns of widely distributing one's location. The research focus is on how to efficiently utilize the many processing cores available on modern machines, both traditional and mobile devices. A primary goal is to allow performance to scale as additional cores become available in newer generations of hardware.The website for this project can be found at http://www.cs.columbia.edu/~kar/snapshot.html

流量监视，移动用户管理和传感器网络等应用程序需要处理大量更新，同时支持在线分析查询。 有了大量的RAM，单机器可能能够管理数亿个物品。 有了多个硬件线程，在现代商品多芯片芯片上多达64个，可以同时处理许多操作。处理查询和更新同时可能引起干扰。查询需要查看一致的数据库状态，这意味着至少在某些时间，更新将需要等待查询完成。为了解决这个问题，探索了各种解决方案，其中在各个时间点拍摄了数据库的沿公羊居民快照。 分析查询在快照上运行，消除了干扰，但允许答案略有过时。正在开发和研究几种不同的快照创建方法，目的是能够创建快照Rapidl（例如，在一秒钟的分数中），同时最大程度地减少了更新处理的开销。这些问题都是针对传统服务器机器的研究，以及用于多项移动设备的问题。 通过保持个性化，最新数据的最新数据，可以支持各种潜在的新应用程序，同时避免广泛分发自己的位置的隐私问题。 研究重点是如何有效利用传统和移动设备的现代机器上可用的许多处理核心。 一个主要目标是使性能扩展，随着额外的核心在新一代的硬件中可用。该项目的网站可以在http://www.cs.columbia.edu/~kar/~kar/snapshot.html上找到。