计算与存储分离

这部分内容有帮助吗？

参考文献

BigQuery: A Serverless Data Warehouse at Scale, James Shute, Radek Vingralek, David C. Smith, Eric Schrock, Justin Levandoski, Jonathan Rosenfeld, Matthew A. S. Franklin, Stephen O'Kane, Jeremy C. Chen, Shailesh G. Lele, Ryan P. Johnson, Michael Carey, David S. C. Hsiao, Andrew C. Pavlo, 2021 Proceedings of the 2021 International Conference on Management of Data (SIGMOD '21) (ACM) DOI: 10.1145/3448016.3457155 - 介绍了Google BigQuery的架构，侧重于其用于大规模数据分析的无服务器、解耦设计及其对云对象存储的利用。
Cloud-Native Data Warehousing, Thomas Neumann, Alfons Kemper, Eike Schiewer, Tobias Müller, Andreas Heindl, Viktor Leis, 2019 Proceedings of the VLDB Endowment, Volume 12, Issue 12, Vol. 12 (VLDB Endowment) DOI: 10.14778/3352063.3352077 - 讨论了构建云原生数据仓库的架构原则和挑战，包括向计算和存储分离的根本转变。
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, Martin Kleppmann, 2017 (O'Reilly Media) - 全面解释了分布式系统概念，包括架构模式、MVCC等一致性模型、缓存策略以及与解耦数据仓库相关的数据存储原则。