Affiliation:
1. Carnegie Mellon University
Abstract
The design of the logging and recovery components of database management systems (DBMSs) has always been influenced by the difference in the performance characteristics of volatile (DRAM) and non-volatile storage devices (HDD/SSDs). The key assumption has been that non-volatile storage is much slower than DRAM and only supports block-oriented read/writes. But the arrival of new non-volatile memory (NVM) storage that is almost as fast as DRAM with fine-grained read/writes invalidates these previous design choices.
This paper explores the changes that are required in a DBMS to leverage the unique properties of NVM in systems that still include volatile DRAM. We make the case for a new logging and recovery protocol, called write-behind logging, that enables a DBMS to recover nearly instantaneously from system failures. The key idea is that the DBMS logs what parts of the database have changed rather than how it was changed. Using this method, the DBMS flushes the changes to the database <u>before</u> recording them in the log. Our evaluation shows that this protocol improves a DBMS's transactional throughput by 1.3×, reduces the recovery time by more than two orders of magnitude, and shrinks the storage footprint of the DBMS on NVM by 1.5×. We also demonstrate that our logging protocol is compatible with standard replication schemes.
Subject
General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development
Cited by
54 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Falcon: Fast OLTP Engine for Persistent Cache and Non-Volatile Memory;Proceedings of the 29th Symposium on Operating Systems Principles;2023-10-23
2. Transactional Python for Durable Machine Learning: Vision, Challenges, and Feasibility;Proceedings of the Seventh Workshop on Data Management for End-to-End Machine Learning;2023-06-18
3. LUNAR: A Native Table Engine for Embedded Devices;Proceedings of the 24th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems;2023-06-13
4. When Tree Meets Hash: Reducing Random Reads for Index Structures on Persistent Memories;Proceedings of the ACM on Management of Data;2023-05-26
5. Integrating Non-Volatile Main Memory in a Deterministic Database;Proceedings of the Eighteenth European Conference on Computer Systems;2023-05-08