III: Small: Multi-Version Concurrency Control on Modern Hardware

III：小：现代硬件上的多版本并发控制

• 批准号: 1718581
• 负责人: Daniel Abadi
• 金额: $ 50万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1718581&HistoricalAwards=false
• 关键词: III; Small; Multi; Version; Concurrency

Database systems generally fall into two categories with respect to how they update data: either they overwrite the old value with the new value, or they store (and make accessible) both the old version and new version of the data. Most early database systems fall in the first category (overwriting data) because storage was expensive and limited. However, as compliance, auditing, reporting, back-up, and disaster recovery use-cases increasingly rely on reading database snapshots and data that may have been later updated, the ability of a database system to maintain recent versions of record values in near-line access modes has become increasingly important. Furthermore, maintaining multiple versions of record values potentially enables the database to improve its throughput of handling transaction requests - reads and writes of the same record can potentially occur concurrently instead of delaying transactions to avoid inconsistent reads. Therefore, the trend in database system architecture is towards the second category: keeping around multiple versions of data values. Existing multi-versioned database systems have done an adequate job in handling the compliance, auditing, reporting, back-up, and disaster recovery use-cases that exist today. However, in many cases they provide no protection against snapshot isolation anomalies that violates the correctness of the data in the database and can result in bugs in application code written on top of the database system. The few existing systems that avoid these anomalies only do so at significant costs to throughput and database performance. Furthermore, most existing multi-versioned database systemsare designed for disk-storage, and struggle to perform well under main-memory workloads.We are building a completely redesigned multi-versioned database system, designed for main-memory deployments. It is architected to achieve extremely high throughput, while avoiding the fundamental write skew anomalies that have existed in previous systems affecting both application developers and database users. We are integrating novel techniques for database recoverability and transaction chopping into the multi-versioned database system architecture in order to improve transaction throughput by at least an order of magnitude. We are also investigating techniques for continuous snapshot replication and serving consistent read queries from geo-distributed replicas with bounded staleness. Furthermore, we are performing extensive experimental studies that both motivate the design of our system, and also motivate the use of multi-versioned database systems in general vs. single-versioned systems.

根据更新数据的方式，数据库系统通常分为两类：要么用新值覆盖旧值，要么存储（并使其可访问）旧版本和新版本的数据。大多数早期的数据库系统属于第一类（覆盖数据），因为存储昂贵且有限。然而，由于遵从性、审计、报告、备份和灾难恢复用例越来越依赖于读取数据库快照和可能稍后更新的数据，数据库系统在近线访问模式下维护记录值的最新版本的能力变得越来越重要。此外，维护多个版本的记录值可能会提高数据库处理事务请求的吞吐量——对同一记录的读和写可能会并发发生，而不是延迟事务以避免不一致的读。因此，数据库系统体系结构的趋势是第二类：保持数据值的多个版本。现有的多版本数据库系统在处理当前存在的遵从性、审计、报告、备份和灾难恢复用例方面已经完成了足够的工作。但是，在许多情况下，它们不提供针对快照隔离异常的保护，这些异常会破坏数据库中数据的正确性，并可能导致在数据库系统之上编写的应用程序代码出现错误。少数能够避免这些异常的现有系统只是在吞吐量和数据库性能方面付出了巨大的代价。此外，大多数现有的多版本数据库系统都是为磁盘存储而设计的，在主内存工作负载下很难表现良好。我们正在构建一个完全重新设计的多版本数据库系统，专为主内存部署而设计。它的架构是为了实现极高的吞吐量，同时避免了在以前的系统中存在的影响应用程序开发人员和数据库用户的基本写倾斜异常。我们正在将数据库可恢复性和事务截断的新技术集成到多版本数据库系统架构中，以便将事务吞吐量至少提高一个数量级。我们还在研究持续快照复制的技术，以及从具有有限过期性的地理分布式副本中提供一致读查询的技术。此外，我们正在进行广泛的实验研究，这既激励了我们系统的设计，也激励了在一般情况下使用多版本数据库系统而不是单版本系统。

项目成果

BullFrog: Online Schema Evolution via Lazy Evaluation

• DOI: 10.1145/3448016.3452842
• 发表时间: 2021-06
• 期刊: Proceedings of the 2021 International Conference on Management of Data
• 作者: Souvik Bhattacherjee;Gang Liao;M. Hicks;D. Abadi

Integration of Large-Scale Data Processing Systems and Traditional Parallel Database Technology

• DOI: 10.14778/3352063.3352145
• 发表时间: 2019-08
• 期刊: Proc. VLDB Endow.
• 作者: A. Abouzeid;D. Abadi;Kamil Bajda-Pawlikowski;A. Silberschatz

SLOG: Serializable, Low-latency, Geo-replicated Transactions

• DOI: 10.14778/3342263.3342647
• 发表时间: 2019-07
• 期刊: Proc. VLDB Endow.
• 作者: Kun Ren;Dennis Li;Daniel J. Abadi

The FuzzyLog: A Partially Ordered Shared Log

• 发表时间: 2018-10
• 作者: Joshua Lockerman;Jose M. Faleiro;Juno Kim;Soham Sankaran;D. Abadi;J. Aspnes;S. Sen;M. Balakrishnan

An overview of deterministic database systems

• DOI: 10.1145/3181853
• 发表时间: 2018-08
• 期刊: Communications of the ACM
• 影响因子: 22.7
• 作者: D. Abadi;Jose M. Faleiro