Posterior Snapshot Isolation

Zhou, Xuan; Zhou, Xin; Yu, Zhengtai; Tan, Kian-Lee

doi:10.1109/icde.2017.130

Cited by 7 publications

(3 citation statements)

References 25 publications

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“…Concurrent Control algorithms. There are many concurrent control algorithms, include two-phase locking (2PL) [21], timestamp ordering (T/O) [8], OCC [5,12,13,33,37,48], MVCC [9]. Locking-based approaches make a particular design on the lock types (e.g., read/write/predicate locks) as well as locking mechanism to disallow single-variable data anomalies [11,19,22,27,28].…”

Section: Related Workmentioning

confidence: 99%

Coo: Rethink Data Anomalies In Databases

Li¹,

Li²,

Chen³

et al. 2021

Preprint

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Transaction processing technology has three important contents: data anomalies, isolation levels and concurrent control algorithms. Concurrent control algorithms is used to eliminate some or all data anomalies at different isolation levels to ensure data consistency. Isolation levels in the current ANSI standard are defined by disallowing certain kinds of data anomalies. Yet, the definitions of data anomalies in the ANSI standard are controversial. On one hand, the definitions lack a mathematical formalization, and cause ambiguous interpretations. On the other hand, the definitions are made in a case-by-case manner, and lead to a situation that even a senior DBA could not have infallible knowledge of data anomalies, due to a lack of a full understanding of its nature. While revised definitions in exiting literature propose various mathematical formalizations to correct the former argument, how to address the latter argument still remains an open problem. In this paper, we present a general framework called Coo with the capability to systematically define data anomalies. Under this framework, we show that existing reported data anomalies is only a small portion. While we theoretically prove that Coo is complete to mathematically formalize data anomalies, we employ a novel method to classify infinite data anomalies. In addition, we use this framework to define a new isolation levels and quantitatively describe the concurrency and rollback rate of mainstream concurrency control algorithms. These works show that the C and I of ACID can be quantitatively analyzed based on all data anomalies.

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Section: Related Workmentioning

confidence: 99%

Coo: Rethink Data Anomalies In Databases

Li¹,

Li²,

Chen³

et al. 2021

Preprint

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show abstract

“…Snapshot isolation is proposed to avoid read lock [17]. Snapshot isolation reads the entity value from the log, but it still relies on the locking protocol to prevent write skew [18].The latest discussion on the concurrency control is trying to make the snapshot isolation is able to prevent write skew concurrency anomaly and makes the interleaved transactions become serializable [19][20][21]. The discussion on making the interleaved transactions in the read committed isolation become serializable is started in [22].…”

Section: Isolation Levelmentioning

confidence: 99%

Basic principles of blind write protocol

Anshar¹,

Suryana²,

Noraswaliza³

2020

Bulletin EEI

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The current approach to handle interleaved write operation and preserve consistency in relational database system still relies on the locking protocol. If any entity is locked by any transaction, then it becomes temporary unavailable to other transaction until the lock is released. The temporary unavailability can be more often if the number of write operation increases as happens in the application systems that utilize IoT technology or smartphone devices to collect the data. To solve this problem, this research is proposed blind write protocol which does not lock the entity while the transaction is performing a write operation. This paper presents the basic principles of blind write protocol implementation in a relational database system

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“…In a preliminary version of this paper [12], we introduced CV and PostSI. In this extended version, we show that serializability can also be enforced efficiently by utilizing visibility.…”

Section: Introductionmentioning

confidence: 99%