On the Semantics of Snapshot Isolation

Snapshot isolation (SI) is a standard transactional consistency model used in databases, distributed systems and software transactional memory (STM). Its semantics is formally defined both declaratively as an acyclicity axiom, and operationally as a concurrent algorithm with memory bearing timestamps. We develop two simpler equivalent operational definitions of SI as lock-based reference implementations that do not use timestamps. Our first locking implementation is prescient in that requires a priori knowledge of the data accessed by a transaction and carries out transactional writes eagerly (in-place). Our second implementation is non-prescient and performs transactional writes lazily by recording them in a local log and propagating them to memory at commit time. Whilst our first implementation is simpler and may be better suited for developing a program logic for SI transactions, our second implementation is more practical due to its non-prescience. We show that both implementations are sound and complete against the declarative SI specification and thus yield equivalent operational definitions for SI. We further consider, for the first time formally, the use of SI in a context with racy non-transactional accesses, as can arise in STM implementations of SI. We introduce robust snapshot isolation (RSI), an adaptation of SI with similar semantics and guarantees in this mixed setting. We present a declarative specification of RSI as an acyclicity axiom and analogously develop two operational models as lock-based reference implementations (one eager, one lazy). We show that these operational models are both sound and complete against the declarative RSI model

Una implementación rápida de Parallel Snapshot Isolation

Grado en Ingeniería Informática, Facultad de Informática UCM, Departamento de Arquitectura de Computadores y Automática, Curso 2019/2020.Most distributed database systems offer weak consistency models in order to avoid the performance penalty of coordinating replicas. Ideally, distributed databases would offer strong consistency models, like serialisability, since they make it easy to verify application invariants, and free programmers from worrying about concurrency. However, implementing and scaling systems with strong consistency is difficult, since it usually requires global communication. Weak models, while easier to scale, impose on the programmers the need to reason about possible anomalies, and the need to implement conflict resolution mechanisms in application code. Recently proposed consistency models, like Parallel Snapshot Isolation (PSI) and NonMonotonic Snapshot Isolation (NMSI), represent the strongest models that still allow to build scalable systems without global communication. They allow comparable performance to previous, weaker models, as well as similar abort rates. However, both models still provide weaker guarantees than serialisability, and may prove difficult to use in applications. This work shows an approach to bridge the gap between PSI, NMSI and strong consistency models like serialisability. It introduces and implements fastPSI, a consistency protocol that allows the user to selectively enforce serialisability for certain executions, while retaining the scalability properties of weaker consistency models like PSI and NMSI. In addition, it features a comprehensive evaluation of fastPSI in comparison with other consistency protocols, both weak and strong, showing that fastPSI offers better performance than serialisability, while retaining the scalability of weaker protocols.La mayoría de las bases de datos distribuidas ofrecen modelos de consistencia débil, con la finalidad de evitar la penalización de rendimiento que supone la coordinación de las distintas réplicas. Idealmente, las bases de datos distribuidas ofrecerían modelos de consistencia fuerte, como serialisability, ya que facilitan la verificación de los invariantes de las aplicaciones, y permiten que los programadores no deban preocuparse sobre posibles problemas de concurrencia. Sin embargo, implementar sistemas escalables que con modelos de consistencia fuerte no es fácil, pues requieren el uso de comunicación global. Sin embargo, aunque los modelos de consistencia más débiles permiten sistemas más escalables, imponen en los programadores la necesidad de razonar sobre posibles anomalías, así como implementar mecanismos de resolución de conflictos en el código de las aplicaciones. Dos modelos de consistencia propuestos recientemente, Parallel Snapshot Isolation (PSI) y Non-Monotonic Snapshot Isolation (NMSI), representan los modelos más fuertes que permiten implementaciones escalables sin necesidad de comunicación global. Permiten, a su vez, implementar sistemas con rendimientos similares a aquellos con modelos más débiles, a la vez que mantienen tasas de cancelación de transacciones similares. Aun así, ambos modelos no logran ofrecer las mismas garantías que serialisability, por lo que pueden ser difíciles de usar desde el punto de vista de las aplicaciones. Este trabajo presenta una propuesta que busca acortar la distancia entre modelos como PSI y NMSI y modelos fuertes como serialisability. Con esa finalidad, este trabajo presenta fastPSI, un protocolo de consistencia que permite al usuario ejecutar de manera selectiva transacciones serializables, reteniendo a su vez las propiedades de escalabilidad propias de modelos de consistencia débiles como PSI o NMSI. Además, este trabajo cuenta con una evaluación exhaustiva de fastPSI, comparándolo con otros protocolos de consistencia, tanto fuertes como débiles. Se muestra así que fastPSI logra un rendimiento mayor que serialisability sin por ello renunciar a la escalabilidad de protocolos más débiles.Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu

LogBase: A Scalable Log-structured Database System in the Cloud

Numerous applications such as financial transactions (e.g., stock trading) are write-heavy in nature. The shift from reads to writes in web applications has also been accelerating in recent years. Write-ahead-logging is a common approach for providing recovery capability while improving performance in most storage systems. However, the separation of log and application data incurs write overheads observed in write-heavy environments and hence adversely affects the write throughput and recovery time in the system. In this paper, we introduce LogBase - a scalable log-structured database system that adopts log-only storage for removing the write bottleneck and supporting fast system recovery. LogBase is designed to be dynamically deployed on commodity clusters to take advantage of elastic scaling property of cloud environments. LogBase provides in-memory multiversion indexes for supporting efficient access to data maintained in the log. LogBase also supports transactions that bundle read and write operations spanning across multiple records. We implemented the proposed system and compared it with HBase and a disk-based log-structured record-oriented system modeled after RAMCloud. The experimental results show that LogBase is able to provide sustained write throughput, efficient data access out of the cache, and effective system recovery.Comment: VLDB201