Update serializability in locking

Hansdah, R. C.; Patnaik, L. M.

doi:10.1007/3-540-17187-8_36

Cited by 18 publications

(16 citation statements)

References 15 publications

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“…Update serializability was introduced by Garcia-Molina and Wiederhold [4], then later extended for abort transactions by Hansdah and Patnaik [5]. US provides the same guarantees as SER for update transactions, i.e., update transactions are serialized.…”

Section: Related Workmentioning

confidence: 97%

See 1 more Smart Citation

Non-monotonic Snapshot Isolation: Scalable and Strong Consistency for Geo-replicated Transactional Systems

Ardekani

Sutra

Shapiro

2013

2013 IEEE 32nd International Symposium on Reliable Distributed Systems

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Modern cloud systems are geo-replicated to improve application latency and availability. Transactional consistency is essential for application developers; however, the corresponding concurrency control and commitment protocols are costly in a geo-replicated setting. To minimize this cost, we identify the following essential scalability properties: (i) only replicas updated by a transaction T make steps to execute T ; (ii) a read-only transaction never waits for concurrent transactions and always commits; (iii) a transaction may read object versions committed after it started; and (iv) two transactions synchronize with each other only if their writes conflict. We present Non-Monotonic Snapshot Isolation (NMSI), the first strong consistency criterion to allow implementations with all four properties. We also present a practical implementation of NMSI called Jessy, which we compare experimentally against a number of well-known criteria. Our measurements show that the latency and throughput of NMSI are comparable to the weakest criterion, read-committed, and between two to fourteen times faster than well-known strong consistencies.

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Section: Related Workmentioning

confidence: 97%

“…Therefore, several previous works aim at designing consistency criteria that both provide meaningful guarantees to the application, and scale well [4][5][6][7][8][9][10][11]. At one end of the spectrum, strict serializability (SSER) ensures that transactions are atomic, and thus offers the strongest concurrency semantics.…”

Section: Introductionmentioning

confidence: 99%

Non-monotonic Snapshot Isolation: Scalable and Strong Consistency for Geo-replicated Transactional Systems

Ardekani

Sutra

Shapiro

2013

2013 IEEE 32nd International Symposium on Reliable Distributed Systems

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“…Update serializability (US) was introduced by GarciaMolina and Wiederhold [51], then later extended to aborted transactions by Hansdah and Patnaik [52]. US guarantees that update transactions are serialized, and that read-only transactions see consistent but non-monotonic snapshots.…”

Section: Update Serializabilitymentioning

confidence: 99%

G-Dur

Ardekani¹,

Sutra

Shapiro³

2014

Proceedings of the 15th International Middleware Conference on - Middleware '14

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A large family of distributed transactional protocols have a common structure, called Deferred Update Replication (DUR). DUR provides dependability by replicating data, and performance by not re-executing transactions but only applying their updates. Protocols of the DUR family differ only in behaviors of few generic functions. Based on this insight, we offer a generic DUR middleware, called G-DUR, along with a library of finely-optimized plug-in implementations of the required behaviors. This paper presents the middleware, the plugins, and an extensive experimental evaluation in a geo-replicated environment. Our empirical study shows that: (i) G-DUR allows developers to implement various transactional protocols under 600 lines of code; (ii) It provides a fair, apples-to-apples comparison between transactional protocols; (iii) By replacing plugs-ins, developers can use G-DUR to understand bottlenecks in their protocols; (iv) This in turn enables the improvement of existing protocols; and (v) Given a protocol, G-DUR helps evaluate the cost of ensuring various degrees of dependability.

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“…In the following we present their formal specifications. US was originally defined by the work in [11], in terms of view serializability, and later re-formulated by Adya [9] in terms of conflict serializability. We report in the following the latter specification of this consistency criterion.…”

Section: System and Data Modelmentioning

confidence: 99%

“…In terms of formal properties, our protocol (as its name suggests) ensures the so called Extended Update Serializability (EUS) consistency criterion, originally introduced in [11] and further investigated in [9] (in the form of the noupdate-conflict-misses property). EUS provides guarantees analogous to those offered by classic 1-Copy Serializability (1CS) for update transactions, thus ensuring consistent evolution of the system's state.…”

Section: Introductionmentioning

confidence: 99%

When Scalability Meets Consistency: Genuine Multiversion Update-Serializable Partial Data Replication

Peluso

Ruivo

Romano

et al. 2012

2012 IEEE 32nd International Conference on Distributed Computing Systems

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Abstract-In this article we introduce GMU, a genuine partial replication protocol for transactional systems, which exploits an innovative, highly scalable, distributed multiversioning scheme. Unlike existing multiversion-based solutions, GMU does not rely on a global logical clock, which represents a contention point and can limit system scalability. Also, GMU never aborts read-only transactions and spares them from distributed validation schemes. This makes GMU particularly efficient in presence of read-intensive workloads, as typical of a wide range of real-world applications.GMU guarantees the Extended Update Serializability (EUS) isolation level. This consistency criterion is particularly attractive as it is sufficiently strong to ensure correctness even for very demanding applications (such as TPC-C), but is also weak enough to allow efficient and scalable implementations, such as GMU. Further, unlike several relaxed consistency models proposed in literature, EUS has simple and intuitive semantics, thus being an attractive, scalable consistency model for ordinary programmers.We integrated the GMU protocol in a popular open source in-memory transactional data grid, namely Infinispan. On the basis of a large scale experimental study performed on heterogeneous experimental platforms and using industry standard benchmarks (namely TPC-C and YCSB), we show that GMU achieves linear scalability and that it introduces negligible overheads (less than 10%), with respect to solutions ensuring non-serializable semantics, in a wide range of workloads.

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Update serializability in locking

Cited by 18 publications

References 15 publications

Non-monotonic Snapshot Isolation: Scalable and Strong Consistency for Geo-replicated Transactional Systems

Non-monotonic Snapshot Isolation: Scalable and Strong Consistency for Geo-replicated Transactional Systems

G-Dur

When Scalability Meets Consistency: Genuine Multiversion Update-Serializable Partial Data Replication

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