Consistency anomalies in multi-tier architectures: automatic detection and prevention

Zellag, Kamal; Kemme, Bettina

doi:10.1007/s00778-013-0318-x

Cited by 26 publications

(12 citation statements)

References 21 publications

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“…[31] developed a set of tools and methods to automatically detect data anomalies from applications under snapshot isolation technology. [44][45][46][47], use a middleware layer that is embedded between the application and the database, according to the serializable theory and dependency graph technology [2,3,6,10,19,24], the method quantifies and classifies the data anomalies. However, this method detects data anomalies based on applications such as TPC-C [18], and finds no new data anomalies.…”

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

View full text Add to dashboard Cite

show abstract

“…This form of atomicity is offered by most commercial database systems, and is easily realized through the judicious use of locks. Enforcing stronger multi-record atomicity guarantees is more challenging, especially in distributed environments with replicated database state [6,9,19,32,50]. In this paper, we consider behaviors induced when the database guarantees only a very weak form of consistency and isolation that allows transactions to see an arbitrary subset of committed updates by other transactions.…”

Section: Data Store Semanticsmentioning

confidence: 99%

Repairing serializability bugs in distributed database programs via automated schema refactoring

Rahmani

Nagar

Delaware

et al. 2021

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation

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Serializability is a well-understood concurrency control mechanism that eases reasoning about highly-concurrent database programs. Unfortunately, enforcing serializability has a high performance cost, especially on geographically distributed database clusters. Consequently, many databases allow programmers to choose when a transaction must be executed under serializability, with the expectation that transactions would only be so marked when necessary to avoid serious concurrency bugs. However, this is a significant burden to impose on developers, requiring them to (a) reason about subtle concurrent interactions among potentially interfering transactions, (b) determine when such interactions would violate desired invariants, and (c) then identify the minimum number of transactions whose executions should be serialized to prevent these violations. To mitigate this burden, this paper presents a sound and fully automated schema refactoring procedure that transforms a program's data layout -rather than its concurrency control logic -to eliminate statically identified concurrency bugs, allowing more transactions to be safely executed under weaker and more performant database guarantees. Experimental results over a range of realistic database benchmarks indicate that our approach is highly effective in eliminating concurrency bugs, with safe refactored programs showing an average of 120% higher throughput and 45% lower latency compared to a serialized baseline.

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“…There are also dynamic anomaly detection techniques [28,11,7] which either build the dependency graphs at run-time and check for cycles, or analyze the trace of events after execution. These approaches do not provide any guarantee that all anomalies will be detected, even for bounded executions.…”

Section: Related Work and Conclusionmentioning

confidence: 99%

Automated Detection of Serializability Violations under Weak Consistency

Nagar,

Jagannathan

2018

Preprint

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While a number of weak consistency mechanisms have been developed in recent years to improve performance and ensure availability in distributed, replicated systems, ensuring correctness of transactional applications running on top of such systems remains a difficult and important problem. Serializability is a well-understood correctness criterion for transactional programs; understanding whether applications are serializable when executed in a weakly-consistent environment, however remains a challenging exercise. In this work, we combine the dependency graph-based characterization of serializability and the framework of abstract executions to develop a fully automated approach for statically finding bounded serializability violations under any weak consistency model. We reduce the problem of serializability to satisfiability of a formula in First-Order Logic, which allows us to harness the power of existing SMT solvers. We provide rules to automatically construct the FOL encoding from programs written in SQL (allowing loops and conditionals) and the consistency specification written as a formula in FOL. In addition to detecting bounded serializability violations, we also provide two orthogonal schemes to reason about unbounded executions by providing sufficient conditions (in the form of FOL formulae) whose satisfiability would imply the absence of anomalies in any arbitrary execution. We have applied the proposed technique on TPC-C, a real world database program with complex application logic, and were able to discover anomalies under Parallel Snapshot Isolation, and verify serializability for unbounded executions under Snapshot Isolation, two consistency mechanisms substantially weaker than serializability.

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Consistency anomalies in multi-tier architectures: automatic detection and prevention

Cited by 26 publications

References 21 publications

Coo: Rethink Data Anomalies In Databases

Coo: Rethink Data Anomalies In Databases

Repairing serializability bugs in distributed database programs via automated schema refactoring

Automated Detection of Serializability Violations under Weak Consistency

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