Napa

作者：Ankur Agiwal, Kevin Lai, Gokul Nath Babu Manoharan, Indrajit Roy, Jagan Sankaranarayanan, Hao Zhang, Tao Zou, Min Chen, Zongchang Chen, Ming Dai, Thanh Do, Haoyu Gao, Haoyan Geng, Raman Grover, Bo Huang, Yanlai Huang, Zhi Li, Jianyi Liang, Tao Lin, Li Liu, Yao Liu, Xi Mao, Yalan Meng, Prashant Mishra, Jay M. Patel, S. Rajesh, Vijayshankar Raman, Sourashis Roy, Mayank Singh Shishodia, Tianhang Sun, Ye Tang, Junichi Tatemura, Sagar Trehan, Ramkumar Vadali, Prasanna Venkatasubramanian, Gensheng Zhang, Kefei Zhang, Yupu Zhang, Zeleng Zhuang, Goetz Graefe, Divyakant Agrawal, Jeff Naughton, Sujata Kosalge, Hakan Hacígümüş · 发表于：Proceedings of the VLDB Endowment · 年份：2021 · DOI：10.14778/3476311.3476377 · 被引用次数：18 · 研究领域：Advanced Database Systems and Queries、Data Management and Algorithms、Cloud Computing and Resource Management

Google services continuously generate vast amounts of application data. This data provides valuable insights to business users. We need to store and serve these planet-scale data sets under the extremely demanding requirements of scalability, sub-second query response times, availability, and strong consistency; all this while ingesting a massive stream of updates from applications used around the globe. We have developed and deployed in production an analytical data management system, Napa, to meet these requirements. Napa is the backend for numerous clients in Google. These clients have a strong expectation of variance-free, robust query performance. At its core, Napa's principal technologies for robust query performance include the aggressive use of materialized views, which are maintained consistently as new data is ingested across multiple data centers. Our clients also demand flexibility in being able to adjust their query performance, data freshness, and costs to suit their unique needs. Robust query processing and flexible configuration of client databases are the hallmark of Napa design. Most of the related work in this area takes advantage of full flexibility to design the whole system without the need to support a diverse set of preexisting use cases. In comparison, a particular challenge we faced is that Napa needs to deal with hard constraints from existing applications and infrastructure, so we could not do a "green field" system, but rather had to satisfy exist...