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Exploring Transaction Anomalies under Weak Isolation Levels for General Database Applications

Gan, Yifan
http://orcid.org/0000-0002-0732-058X
http://rave.ohiolink.edu/etdc/view?acc_num=osu1638473583256795

Abstract Details

2021, Doctor of Philosophy, Ohio State University, Computer Science and Engineering.
Weak isolation levels, such as Read Committed and Snapshot Isolation, are widely used by databases for their higher concurrency and better performance, but may introduce subtle correctness errors in applications that only experts can identify. To help developers debug the anomalies caused by weak isolation, we proposed IsoDiff, a tool to analyze transactions in database applications and identify possible anomalous executions under given weak isolation levels. To address the challenge that the number of anomalies can be non-polynomial with respect to the number of types of transactions, IsoDiff finds a representative subset of anomalies involving different transactions, operations, and problematic patterns. To reduce false positives, IsoDiff proposes two novel methods: 1) correlation detection; 2) timing relationship check, to eliminate as many false positives as possible. We further extend the work of IsoDiff on several respects. First, we design a random yet deterministic mechanism to provide stable performance and consistent result with control of single random seed. Second, we incorporate domain knowledge from developer via a generalized feedback framework to allow developers express their requirements and eliminate false positives with their specific usage scenarios. Third, we make augmentation on IsoDiff in consideration of practical database management system settings. To show the effectiveness, we evaluate IsoDiff against TPC-C and other real applications under Snapshot Isolation and Read Committed, showing that IsoDiff can balance computation time and the coverage of anomalies; it can automatically eliminate a significant portion of false positives; and its feedback mechanism allows a developer to express the root cause of false positives, which can eliminate many false positives with only a small number of developer hints. The extensive evaluation on IsoDiff shows its generalizability and flexibility of handling various requirements from database management system and database application developers.
Yang Wang (Advisor)
Xiaodong Zhang (Committee Member)
Feng Qin (Committee Member)
Spyros Blanas (Committee Member)
111 p.
Computer Engineering; Computer Science
Database; Transaction Isolation; Concurrency Control; Distributed System

Recommended Citations

Citations

  • Gan, Y. (2021). Exploring Transaction Anomalies under Weak Isolation Levels for General Database Applications [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1638473583256795

    APA Style (7th edition)

  • Gan, Yifan. Exploring Transaction Anomalies under Weak Isolation Levels for General Database Applications. 2021. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1638473583256795.

    MLA Style (8th edition)

  • Gan, Yifan. "Exploring Transaction Anomalies under Weak Isolation Levels for General Database Applications." Doctoral dissertation, Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1638473583256795

    Chicago Manual of Style (17th edition)

osu1638473583256795
357
© 2021, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.