@inproceedings{4d980432f82e41588f043a7117bf75bd,
title = "Poplar: Partially-Ordered Parallel Logging for Lower Isolation Levels",
abstract = "Existing parallel logging schemes are unsuitable for lower isolation levels due to tracking all dependencies of transactions. To overcome this problem, we present a high-performance parallel logging scheme (Poplar) in database management systems (DBMSs), which is compatible with multiple concurrency control techniques. Poplar uses a partially-ordered log sequence number (PSN) to encode write/read-dependencies of transactions. These dependencies are sufficient to ensure the correctness of logging and recovery. Our experimental evaluation shows that Poplar outperforms the state-of-the-art parallel logging schemes by up to ∼67\% at Read Committed and ∼23\% at Repeatable Read in the YCSB workload, and achieves up to ∼97\% better performance at Read Committed in the TPC-C workload. It also enables the DBMS to recover up to ∼22\% faster than these baselines.",
keywords = "Lower Isolation level, Parallel Logging, Recovery",
author = "Lei Yang and Huan Zhou and Weining Qian and Jian Hu and Tao Liu and Jianhua Zhang",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 8th Asia-Pacific Web and Web-Age Information Management Joint International Conference on Web and Big Data, APWeb-WAIM 2024 ; Conference date: 30-08-2024 Through 01-09-2024",
year = "2024",
doi = "10.1007/978-981-97-7238-4\_30",
language = "英语",
isbn = "9789819772377",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "477--493",
editor = "Wenjie Zhang and Zhengyi Yang and Xiaoyang Wang and Anthony Tung and Zhonglong Zheng and Hongjie Guo",
booktitle = "Web and Big Data - 8th International Joint Conference, APWeb-WAIM 2024, Proceedings",
address = "德国",
}