Arquitetura de elevada disponibilidade para bases de dados na cloud

Dissertação de mestrado em Computer ScienceCom a constante expansão de sistemas informáticos nas diferentes áreas de aplicação, a quantidade de dados que exigem persistência aumenta exponencialmente. Assim, por forma a tolerar faltas e garantir a disponibilidade de dados, devem ser implementadas técnicas de replicação. Atualmente existem várias abordagens e protocolos, tendo diferentes tipos de aplicações em vista. Existem duas grandes vertentes de protocolos de replicação, protocolos genéricos, para qualquer serviço, e protocolos específicos destinados a bases de dados. No que toca a protocolos de replicação genéricos, as principais técnicas existentes, apesar de completa mente desenvolvidas e em utilização, têm algumas limitações, nomeadamente: problemas de performance relativamente a saturação da réplica primária na replicação passiva e o determinismo necessário associado à replicação ativa. Algumas destas desvantagens são mitigadas pelos protocolos específicos de base de dados (e.g., com recurso a multi-master) mas estes protocolos não permitem efetuar uma separação entre a lógica da replicação e os respetivos dados. Abordagens mais recentes tendem a basear-se em técnicas de repli cação com fundamentos em mecanismos distribuídos de logging. Tais mecanismos propor cionam alta disponibilidade de dados e tolerância a faltas, permitindo abordagens inovado ras baseadas puramente em logs. Por forma a atenuar as limitações encontradas não só no mecanismo de replicação ativa e passiva, mas também nas suas derivações, esta dissertação apresenta uma solução de replicação híbrida baseada em middleware, o SQLware. A grande vantagem desta abor dagem baseia-se na divisão entre a camada de replicação e a camada de dados, utilizando um log distribuído altamente escalável que oferece tolerância a faltas e alta disponibilidade. O protótipo desenvolvido foi validado com recurso à execução de testes de desempenho, sendo avaliado em duas infraestruturas diferentes, nomeadamente, um servidor privado de média gama e um grupo de servidores de computação de alto desempenho. Durante a avaliação do protótipo, o standard da indústria TPC-C, tipicamente utilizado para avaliar sistemas de base de dados transacionais, foi utilizado. Os resultados obtidos demonstram que o SQLware oferece uma aumento de throughput de 150 vezes, comparativamente ao mecanismo de replicação nativo da base de dados considerada, o PostgreSQL.With the constant expansion of computational systems, the amount of data that requires durability increases exponentially. All data persistence must be replicated in order to provide high-availability and fault tolerance according to the surrogate application or use-case. Currently, there are numerous approaches and replication protocols developed supporting different use-cases. There are two prominent variations of replication protocols, generic protocols, and database specific ones. The two main techniques associated with generic replication protocols are the active and passive replication. Although generic replication techniques are fully matured and widely used, there are inherent problems associated with those protocols, namely: performance issues of the primary replica of passive replication and the determinism required by the active replication. Some of those disadvantages are mitigated by specific database replication protocols (e.g., using multi-master) but, those protocols do not allow a separation between logic and data and they can not be decoupled from the database engine. Moreover, recent strategies consider highly-scalable and fault tolerant distributed logging mechanisms, allowing for newer designs based purely on logs to power replication. To mitigate the shortcomings found in both active and passive replication mechanisms, but also in partial variations of these methods, this dissertation presents a hybrid replication middleware, SQLware. The cornerstone of the approach lies in the decoupling between the logical replication layer and the data store, together with the use of a highly scalable distributed log that provides fault-tolerance and high-availability. We validated the prototype by conducting a benchmarking campaign to evaluate the overall system’s performance under two distinct infrastructures, namely a private medium class server, and a private high performance computing cluster. Across the evaluation campaign, we considered the TPCC benchmark, a widely used benchmark in the evaluation of Online transaction processing (OLTP) database systems. Results show that SQLware was able to achieve 150 times more throughput when compared with the native replication mechanism of the underlying data store considered as baseline, PostgreSQL.This work was partially funded by FCT - Fundação para a Ciência e a Tecnologia, I.P., (Portuguese Foundation for Science and Technology) within project UID/EEA/50014/201

Scalable and Highly Available Database Systems in the Cloud

Cloud computing allows users to tap into a massive pool of shared computing resources such as servers, storage, and network. These resources are provided as a service to the users allowing them to “plug into the cloud” similar to a utility grid. The promise of the cloud is to free users from the tedious and often complex task of managing and provisioning computing resources to run applications. At the same time, the cloud brings several additional benefits including: a pay-as-you-go cost model, easier deployment of applications, elastic scalability, high availability, and a more robust and secure infrastructure. One important class of applications that users are increasingly deploying in the cloud is database management systems. Database management systems differ from other types of applications in that they manage large amounts of state that is frequently updated, and that must be kept consistent at all scales and in the presence of failure. This makes it difficult to provide scalability and high availability for database systems in the cloud. In this thesis, we show how we can exploit cloud technologies and relational database systems to provide a highly available and scalable database service in the cloud. The first part of the thesis presents RemusDB, a reliable, cost-effective high availability solution that is implemented as a service provided by the virtualization platform. RemusDB can make any database system highly available with little or no code modifications by exploiting the capabilities of virtualization. In the second part of the thesis, we present two systems that aim to provide elastic scalability for database systems in the cloud using two very different approaches. The three systems presented in this thesis bring us closer to the goal of building a scalable and reliable transactional database service in the cloud

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

Clouder : a flexible large scale decentralized object store

Programa Doutoral em Informática MAP-iLarge scale data stores have been initially introduced to support a few concrete extreme scale applications such as social networks. Their scalability and availability requirements often outweigh sacrificing richer data and processing models, and even elementary data consistency. In strong contrast with traditional relational databases (RDBMS), large scale data stores present very simple data models and APIs, lacking most of the established relational data management operations; and relax consistency guarantees, providing eventual consistency. With a number of alternatives now available and mature, there is an increasing willingness to use them in a wider and more diverse spectrum of applications, by skewing the current trade-off towards the needs of common business users, and easing the migration from current RDBMS. This is particularly so when used in the context of a Cloud solution such as in a Platform as a Service (PaaS). This thesis aims at reducing the gap between traditional RDBMS and large scale data stores, by seeking mechanisms to provide additional consistency guarantees and higher level data processing primitives in large scale data stores. The devised mechanisms should not hinder the scalability and dependability of large scale data stores. Regarding, higher level data processing primitives this thesis explores two complementary approaches: by extending data stores with additional operations such as general multi-item operations; and by coupling data stores with other existent processing facilities without hindering scalability. We address this challenges with a new architecture for large scale data stores, efficient multi item access for large scale data stores, and SQL processing atop large scale data stores. The novel architecture allows to find the right trade-offs among flexible usage, efficiency, and fault-tolerance. To efficient support multi item access we extend first generation large scale data store’s data models with tags and a multi-tuple data placement strategy, that allow to efficiently store and retrieve large sets of related data at once. For efficient SQL support atop scalable data stores we devise design modifications to existing relational SQL query engines, allowing them to be distributed. We demonstrate our approaches with running prototypes and extensive experimental evaluation using proper workloads.Os sistemas de armazenamento de dados de grande escala foram inicialmente desenvolvidos para suportar um leque restrito de aplicacões de escala extrema, como as redes sociais. Os requisitos de escalabilidade e elevada disponibilidade levaram a sacrificar modelos de dados e processamento enriquecidos e até a coerência dos dados. Em oposição aos tradicionais sistemas relacionais de gestão de bases de dados (SRGBD), os sistemas de armazenamento de dados de grande escala apresentam modelos de dados e APIs muito simples. Em particular, evidenciasse a ausência de muitas das conhecidas operacões de gestão de dados relacionais e o relaxamento das garantias de coerência, fornecendo coerência futura. Atualmente, com o número de alternativas disponíveis e maduras, existe o crescente interesse em usá-los num maior e diverso leque de aplicacões, orientando o atual compromisso para as necessidades dos típicos clientes empresariais e facilitando a migração a partir das atuais SRGBD. Isto é particularmente importante no contexto de soluções cloud como plataformas como um servic¸o (PaaS). Esta tese tem como objetivo reduzir a diferencça entre os tradicionais SRGDBs e os sistemas de armazenamento de dados de grande escala, procurando mecanismos que providenciem garantias de coerência mais fortes e primitivas com maior capacidade de processamento. Os mecanismos desenvolvidos não devem comprometer a escalabilidade e fiabilidade dos sistemas de armazenamento de dados de grande escala. No que diz respeito às primitivas com maior capacidade de processamento esta tese explora duas abordagens complementares : a extensão de sistemas de armazenamento de dados de grande escala com operacões genéricas de multi objeto e a junção dos sistemas de armazenamento de dados de grande escala com mecanismos existentes de processamento e interrogac¸ ˜ao de dados, sem colocar em causa a escalabilidade dos mesmos. Para isso apresent´amos uma nova arquitetura para os sistemas de armazenamento de dados de grande escala, acesso eficiente a m´ultiplos objetos, e processamento de SQL sobre sistemas de armazenamento de dados de grande escala. A nova arquitetura permite encontrar os compromissos adequados entre flexibilidade, eficiˆencia e tolerˆancia a faltas. De forma a suportar de forma eficiente o acesso a m´ultiplos objetos estendemos o modelo de dados de sistemas de armazenamento de dados de grande escala da primeira gerac¸ ˜ao com palavras-chave e definimos uma estrat´egia de colocac¸ ˜ao de dados para m´ultiplos objetos que permite de forma eficiente armazenar e obter grandes quantidades de dados de uma s´o vez. Para o suporte eficiente de SQL sobre sistemas de armazenamento de dados de grande escala, analisámos a arquitetura dos motores de interrogação de SRGBDs e fizemos alterações que permitem que sejam distribuídos. As abordagens propostas são demonstradas através de protótipos e uma avaliacão experimental exaustiva recorrendo a cargas adequadas baseadas em aplicações reais

Partial replication in distributed software transactional memory

Dissertação para obtenção do Grau de Mestre em Engenharia InformáticaDistributed software transactional memory (DSTM) is emerging as an interesting alternative for distributed concurrency control. Usually, DSTM systems resort to data distribution and full replication techniques in order to provide scalability and fault tolerance. Nevertheless, distribution does not provide support for fault tolerance and full replication limits the system’s total storage capacity. In this context, partial data replication rises as an intermediate solution that combines the best of the previous two trying to mitigate their disadvantages. This strategy has been explored by the distributed databases research field, but has been little addressed in the context of transactional memory and, to the best of our knowledge, it has never before been incorporated into a DSTM system for a general-purpose programming language. Thus, we defend the claim that it is possible to combine both full and partial data replication in such systems. Accordingly, we developed a prototype of a DSTM system combining full and partial data replication for Java programs. We built from an existent DSTM framework and extended it with support for partial data replication. With the proposed framework, we implemented a partially replicated DSTM. We evaluated the proposed system using known benchmarks, and the evaluation showcases the existence of scenarios where partial data replication can be advantageous, e.g., in scenarios with small amounts of transactions modifying fully replicated data. The results of this thesis show that we were able to sustain our claim by implementing a prototype that effectively combines full and partial data replication in a DSTM system. The modularity of the presented framework allows the easy implementation of its various components, and it provides a non-intrusive interface to applications.Fundação para a Ciência e Tecnologia - (FCT/MCTES) in the scope of the research project PTDC/EIA-EIA/113613/2009 (Synergy-VM