Read atomic transactions with prevention of lost updates: ROLA and its formal analysis

2021 International Symposium on Theoretical Aspects of Software Engineering (TASE)

2021

Self Cite

Developing correct, scalable, and fault-tolerant distributed databases is hard and labor-intensive. The increasing complexity of such systems under modern cloud infrastructures, e.g., geo-replicated multi-partitioned datacenters, further limits the number of design alternatives that can be explored in practice. There is therefore a need for the formal analysis of both their qualitative properties, e.g., data consistency, and their quantitative properties, e.g., latency, at an early design stage.In this paper we use formal modeling and both standard and statistical model checking techniques to explore the design space of replicated RAMP (Read Atomic Multi-Partition) transactions for geo-replicated databases. Specifically, we develop in Maude formal, executable specifications of three replicated RAMP designs, two by the RAMP developers and one by us, and analyze their data consistency properties. We further transform the Maude models into probabilistic rewrite theories for statistical model checking w.r.t. performance properties. Our results: (i) are consistent with the conjectures made by the RAMP developers; (ii) uncover our promising new design that not only provides all crucial data consistency guarantees but also outperforms the other design alternatives. * Corresponding author toolkit for object-based distributed systems [6], [15], [16], [24], [29]. In particular, Maude's LTL model checker and the PVeStA statistical model checker [3] have been used to analyze, often for the first time, both correctness and performance of high-level designs of a wide range of stateof-the-art industrial and academic cloud databases such as Apache Cassandra, Google's Megastore, RAMP, Walter, and ROLA. Model-based performance predictions using PVeStA have shown good correspondence with implementations-based evaluations under realistic deployments for Cassandra, RAMP, Walter, and ROLA [13], [14], [19], [22].

Section: Related Workmentioning

confidence: 99%

Exploring Design Alternatives for Replicated RAMP Transactions Using Maude

2021 International Symposium on Theoretical Aspects of Software Engineering (TASE)

2021

Self Cite

“…These requirements are not very strict. The Maude models of the DTSs RAMP [29], Faster [24], Walter [26], ROLA [25], Jessy [28], and P-Store [32] can all be seen as instantiations of our modeling framework, with very small syntactic changes, such as defining transaction and replica objects as subclasses of Txn and Replica, changing the names of the attributes and sorts, etc. The Apache Cassandra NoSQL key-value store can be seen as a transaction system where each transaction is a single operation; the Maude model of Cassandra in [30] can also be easily modified to fit within our modeling framework.…”

Section: Modeling Dtss In Maudementioning

confidence: 99%

“…Our previous work [8,18,19,[24][25][26]28,29,32] specifies and model checks single DTSs and consistency properties in different ways, as opposed to in a single framework that, furthermore, automates the "monitoring" and analysis process.…”

Section: Related Workmentioning

confidence: 99%

Automatic Analysis of Consistency Properties of Distributed Transaction Systems in Maude

Tools and Algorithms for the Construction and Analysis of Systems

Ölveczky

Zhang

et al. 2019

Self Cite

Many transaction systems distribute, partition, and replicate their data for scalability, availability, and fault tolerance. However, observing and maintaining strong consistency of distributed and partially replicated data leads to high transaction latencies. Since different applications require different consistency guarantees, there is a plethora of consistency properties-from weak ones such as read atomicity through various forms of snapshot isolation to stronger serializability propertiesand distributed transaction systems (DTSs) guaranteeing such properties. This paper presents a general framework for formally specifying a DTS in Maude, and formalizes in Maude nine common consistency properties for DTSs so defined. Furthermore, we provide a fully automated method for analyzing whether the DTS satisfies the desired property for all initial states up to given bounds on system parameters. This is based on automatically recording relevant history during a Maude run and defining the consistency properties on such histories. To the best of our knowledge, this is the first time that model checking of all these properties in a unified, systematic manner is investigated. We have implemented a tool that automates our method, and use it to model check state-ofthe-art DTSs such as P-Store, RAMP, Walter, Jessy, and ROLA.

“…Read atomicity (RA) [10]-either all or none of a transaction's updates are visible to another transaction's readsmagnificently bridges the gap between C and A in a distributed setting by providing the strongest data consistency that is achievable with high availability (the HAT semantics [9]). Many industrial and academic distributed databases have therefore integrated read atomic transactions as important building blocks [4,10,21,48,53,75]. To cite a few examples, RAMP-TAO [21] has recently layered RA on Facebook's TAO data store [18] to provide atomically visible and highly available transactions.…”

Section: Introductionmentioning

confidence: 99%

All in One: Design, Verification, and Implementation of SNOW-optimal Read Atomic Transactions

ACM Trans. Softw. Eng. Methodol.

2022

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Distributed read atomic transactions are important building blocks of modern cloud databases that magnificently bridge the gap between data availability and strong data consistency. The performance of their transactional reads is particularly critical to the overall system performance, as many real-world database workloads are dominated by reads. Following the SNOW design principle for optimal reads, we develop LORA, a novel SNOW-optimal algorithm for distributed read atomic transactions. LORA completes its reads in exactly one round trip, even in the presence of conflicting writes, without imposing additional overhead to the communication, and it outperforms the state-of-the-art read atomic algorithms. To guide LORA’s development, we present a rewriting-logic-based framework and toolkit for design, verification, implementation, and evaluation of distributed databases. Within the framework, we formalize LORA and mathematically prove its data consistency guarantees. We also apply automatic model checking and statistical verification to validate our proofs and to estimate LORA’s performance. We additionally generate from the formal model a correct-by-construction distributed implementation for testing and performance evaluation under realistic deployments. Our design-level and implementation-based experimental results are consistent, which together demonstrate LORA’s promising data consistency and performance achievement.