Consistency in 3D

Comparisons of different consistency models often try to place them in a linear strong-to-weak order. However this view is clearly inadequate, since it is well known, for instance, that Snapshot Isolation and Serialisability are incomparable. In the interest of a better understanding, we propose a new classification, along three dimensions, related to: a total order of writes, a causal order of reads, and transactional composition of multiple operations. A model may be stronger than another on one dimension and weaker on another. We believe that this new classification scheme is both scientifically sound and has good explicative value. The current paper presents the three-dimensional design space intuitively.Les comparaisons entre modèles de la cohérence tentent souvent de les classer dans un ordre linéaire, de faible à forte. Cette vue est clairement inadéquate, puisque il est bien connu que, par exemple, les modèles Snapshot Isolation et Serialisability sont incomparables. Dans l'intérêt d'une meilleure compréhension du domaine, nous proposons une nouvelle classification, en trois dimensions~: les garanties liées à un ordre total des écritures~; celles liées à un ordre causal des lectures~; et celles liées à la composition transactionelle d'opérations multiples. Un modèle peut être plus fort qu'un autre dans une dimension, et moins dans une autre. Nous pensons que ce nouveau schéma de classification, à la fois est scientifiquement valide, et a une bonne valeur explicative. Le présent rapport présente l'espace de conception en trois dimensions de façon intuitive

Non-Monotonic Snapshot Isolation: scalable and strong consistency for geo-replicated transactional systems

International audienceModern 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

Non-Monotonic Snapshot Isolation

Many distributed applications require transactions. However, transactional protocols that require strong synchronization are costly in large scale environments. Two properties help with scalability of a transactional system: genuine partial replication (GPR), which leverages the intrinsic parallelism of a workload, and snapshot isolation (SI), which decreases the need for synchronization. We show that, under standard assumptions (data store accesses are not known in advance, and transactions may access arbitrary objects in the data store), it is impossible to have both SI and GPR. To circumvent this impossibility, we propose a weaker consistency criterion, called Non-monotonic Snapshot Isolation (NMSI). NMSI retains the most important properties of SI, i.e., read-only transactions always commit, and two write-conflicting updates do not both commit. We present a GPR protocol that ensures NMSI, and has lower message cost (i.e., it contacts fewer replicas and/or commits faster) than previous approaches.Cet article étudie deux propriétés favorisant le passage à l'échelle des systèmes répartis transactionnels: la réplication partielle authentique GPR), et le critère de cohérence Snapshot Isolation (SI). GPR spécifie que pour valider une transaction T, seules les répliques des données accédées par T effectuent des pas de calcul. SI définit que toute transaction doit lire une vue cohérente du système, et que deux transactions concurrentes ne peuvent écrire la même donnée. Nous montrons que ces deux propriétés sont incompatibles. Nous proposons ensuite un nouveau critère de cohérence nommé Non-Monotonic Snapshot Isolation (NMSI). NMSI est proche de SI et compatible avec GPR. Pour justifier ce propos, nous présentons un protocole authentique implémentant de manière efficace NMSI. Au regard des travaux précédents sur le contrôle de concurrence dans les systèmes répartis transactionnelles, notre protocole est plus performant en latence et/ou en nombre de messages échangés

Ensuring consistency in partially replicated data stores

Dans une première partie, nous étudions la cohérence dans les systèmes transactionnels, en nous concentrant sur le problème de réconcilier la scalabilité avec des garanties transactionnelles fortes. Nous identifions quatre propriétés critiques pour la scalabilité. Nous montrons qu’aucun des critères de cohérence forte existants n’assurent l’ensemble de ces propriétés. Nous définissons un nouveau critère, appelé Non-Monotonic Snapshot Isolation ou NMSI, qui est le premier à être compatible avec les quatre propriétés à la fois. Nous présentons aussi une mise en œuvre de NMSI, appelée Jessy, que nous comparons expérimentalement à plusieurs critères connus. Une autre contribution est un canevas permettant de comparer de façon non biaisée différents protocoles. Elle se base sur la constatation qu’une large classe de protocoles transactionnels distribués est basée sur une même structure, Deferred Update Replication(DUR). Les protocoles de cette classe ne diffèrent que par les comportements spécifiques d’un petit nombre de fonctions génériques. Nous présentons donc un canevas générique pour les protocoles DUR.La seconde partie de la thèse a pour sujet la cohérence dans les systèmes de stockage non transactionnels. C’est ainsi que nous décrivons Tuba, un stockage clef-valeur qui choisit dynamiquement ses répliques selon un objectif de niveau de cohérence fixé par l’application. Ce système reconfigure automatiquement son ensemble de répliques, tout en respectant les objectifs de cohérence fixés par l’application, afin de s’adapter aux changements dans la localisation des clients ou dans le débit des requête.In the first part, we study consistency in a transactional systems, and focus on reconciling scalability with strong transactional guarantees. We identify four scalability properties, and show that none of the strong consistency criteria ensure all four. We define a new scalable consistency criterion called Non-Monotonic Snapshot Isolation (NMSI), while is the first that is compatible 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. We also introduce a framework for performing fair comparison among different transactional protocols. Our insight is that a large family of distributed transactional protocols have a common structure, called Deferred Update Replication (DUR). Protocols of the DUR family differ only in behaviors of few generic functions. We present a generic DUR framework, called G-DUR. We implement and compare several transactional protocols using the G-DUR framework.In the second part, we focus on ensuring consistency in non-transactional data stores. We introduce Tuba, a replicated key-value store that dynamically selects replicas in order to maximize the utility delivered to read operations according to a desired consistency defined by the application. In addition, unlike current systems, it automatically reconfigures its set of replicas while respecting application-defined constraints so that it adapts to changes in clients’ locations or request rates. Compared with a system that is statically configured, our evaluation shows that Tuba increases the reads that return strongly consistent data by 63%

Le maintien de la cohérence dans les systèmes de stockage partiellement repliqués

In the first part, we study consistency in a transactional systems, and focus on reconciling scalability with strong transactional guarantees. We identify four scalability properties, and show that none of the strong consistency criteria ensure all four. We define a new scalable consistency criterion called Non-Monotonic Snapshot Isolation (NMSI), while is the first that is compatible 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. We also introduce a framework for performing fair comparison among different transactional protocols. Our insight is that a large family of distributed transactional protocols have a common structure, called Deferred Update Replication (DUR). Protocols of the DUR family differ only in behaviors of few generic functions. We present a generic DUR framework, called G-DUR. We implement and compare several transactional protocols using the G-DUR framework.In the second part, we focus on ensuring consistency in non-transactional data stores. We introduce Tuba, a replicated key-value store that dynamically selects replicas in order to maximize the utility delivered to read operations according to a desired consistency defined by the application. In addition, unlike current systems, it automatically reconfigures its set of replicas while respecting application-defined constraints so that it adapts to changes in clients’ locations or request rates. Compared with a system that is statically configured, our evaluation shows that Tuba increases the reads that return strongly consistent data by 63%.Dans une première partie, nous étudions la cohérence dans les systèmes transactionnels, en nous concentrant sur le problème de réconcilier la scalabilité avec des garanties transactionnelles fortes. Nous identifions quatre propriétés critiques pour la scalabilité. Nous montrons qu’aucun des critères de cohérence forte existants n’assurent l’ensemble de ces propriétés. Nous définissons un nouveau critère, appelé Non-Monotonic Snapshot Isolation ou NMSI, qui est le premier à être compatible avec les quatre propriétés à la fois. Nous présentons aussi une mise en œuvre de NMSI, appelée Jessy, que nous comparons expérimentalement à plusieurs critères connus. Une autre contribution est un canevas permettant de comparer de façon non biaisée différents protocoles. Elle se base sur la constatation qu’une large classe de protocoles transactionnels distribués est basée sur une même structure, Deferred Update Replication(DUR). Les protocoles de cette classe ne diffèrent que par les comportements spécifiques d’un petit nombre de fonctions génériques. Nous présentons donc un canevas générique pour les protocoles DUR.La seconde partie de la thèse a pour sujet la cohérence dans les systèmes de stockage non transactionnels. C’est ainsi que nous décrivons Tuba, un stockage clef-valeur qui choisit dynamiquement ses répliques selon un objectif de niveau de cohérence fixé par l’application. Ce système reconfigure automatiquement son ensemble de répliques, tout en respectant les objectifs de cohérence fixés par l’application, afin de s’adapter aux changements dans la localisation des clients ou dans le débit des requête

A Self-Configurable Geo-Replicated Cloud Storage System

International audienceReconfiguring a cloud storage system can improve its overall service. Tuba is a geo-replicated key-value store that automatically reconfigures its set of replicas while respecting application-defined constraints so that it adapts to changes in clients’ locations or request rates. New replicas may be added, existing replicas moved, replicas upgraded from secondary to primary, and the update propagation between replicas adjusted. Tuba extends a commercial cloudbased service, Microsoft Azure Storage, with broad consistency choices (as in Bayou), consistency-based SLAs (as in Pileus), and a novel replication configuration service. Compared with a system that is statically configured, our evaluation shows that Tuba increases the reads that return strongly consistent data by 63%

The Impossibility of Ensuring Snapshot Isolation in Genuine Replicated STMs

In conjunction with DISC 2011International audienceIn order to scale to large multiprocessors or clusters, transactional memories must reduce reliance on synchronisation. Therefore, we consider two favorable formal properties, namely Snapshot Isolation (SI, by which read-only transactions commit without synchronisation), and Genuine Partial Replication (GPR, by which a processor synchronises for a transaction only if it maintains a copy of some data item accessed by that transaction). We show that, unless the read-set of every transaction is known in advance, the combination of SI+GPR is impossible. To circumvent this impossibility result, we propose to weaken SI such that snapshots are allowed to be non-monotonic

The Impossibility of Ensuring Snapshot Isolation in Genuine Replicated STMs

In conjunction with DISC 2011International audienceIn order to scale to large multiprocessors or clusters, transactional memories must reduce reliance on synchronisation. Therefore, we consider two favorable formal properties, namely Snapshot Isolation (SI, by which read-only transactions commit without synchronisation), and Genuine Partial Replication (GPR, by which a processor synchronises for a transaction only if it maintains a copy of some data item accessed by that transaction). We show that, unless the read-set of every transaction is known in advance, the combination of SI+GPR is impossible. To circumvent this impossibility result, we propose to weaken SI such that snapshots are allowed to be non-monotonic

G-DUR: A Middleware for Assembling, Analyzing, and Improving Transactional Protocols

International audienceA 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 implemen- tations of the required behaviors. This paper presents the middleware, the plugins, and an extensive experimental eval- uation 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 proto- cols; and (v) Given a protocol, G-DUR helps evaluate the cost of ensuring various degrees of dependability