The End of Slow Networks: It's Time for a Redesign

Next generation high-performance RDMA-capable networks will require a fundamental rethinking of the design and architecture of modern distributed DBMSs. These systems are commonly designed and optimized under the assumption that the network is the bottleneck: the network is slow and "thin", and thus needs to be avoided as much as possible. Yet this assumption no longer holds true. With InfiniBand FDR 4x, the bandwidth available to transfer data across network is in the same ballpark as the bandwidth of one memory channel, and it increases even further with the most recent EDR standard. Moreover, with the increasing advances of RDMA, the latency improves similarly fast. In this paper, we first argue that the "old" distributed database design is not capable of taking full advantage of the network. Second, we propose architectural redesigns for OLTP, OLAP and advanced analytical frameworks to take better advantage of the improved bandwidth, latency and RDMA capabilities. Finally, for each of the workload categories, we show that remarkable performance improvements can be achieved

A shared-disk parallel cluster file system

Dissertação apresentada para obtenção do Grau de Doutor em Informática Pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaToday, clusters are the de facto cost effective platform both for high performance computing (HPC) as well as IT environments. HPC and IT are quite different environments and differences include, among others, their choices on file systems and storage: HPC favours parallel file systems geared towards maximum I/O bandwidth, but which are not fully POSIX-compliant and were devised to run on top of (fault prone) partitioned storage; conversely, IT data centres favour both external disk arrays (to provide highly available storage) and POSIX compliant file systems, (either general purpose or shared-disk cluster file systems, CFSs). These specialised file systems do perform very well in their target environments provided that applications do not require some lateral features, e.g., no file locking on parallel file systems, and no high performance writes over cluster-wide shared files on CFSs. In brief, we can say that none of the above approaches solves the problem of providing high levels of reliability and performance to both worlds. Our pCFS proposal makes a contribution to change this situation: the rationale is to take advantage on the best of both – the reliability of cluster file systems and the high performance of parallel file systems. We don’t claim to provide the absolute best of each, but we aim at full POSIX compliance, a rich feature set, and levels of reliability and performance good enough for broad usage – e.g., traditional as well as HPC applications, support of clustered DBMS engines that may run over regular files, and video streaming. pCFS’ main ideas include: · Cooperative caching, a technique that has been used in file systems for distributed disks but, as far as we know, was never used either in SAN based cluster file systems or in parallel file systems. As a result, pCFS may use all infrastructures (LAN and SAN) to move data. · Fine-grain locking, whereby processes running across distinct nodes may define nonoverlapping byte-range regions in a file (instead of the whole file) and access them in parallel, reading and writing over those regions at the infrastructure’s full speed (provided that no major metadata changes are required). A prototype was built on top of GFS (a Red Hat shared disk CFS): GFS’ kernel code was slightly modified, and two kernel modules and a user-level daemon were added. In the prototype, fine grain locking is fully implemented and a cluster-wide coherent cache is maintained through data (page fragments) movement over the LAN. Our benchmarks for non-overlapping writers over a single file shared among processes running on different nodes show that pCFS’ bandwidth is 2 times greater than NFS’ while being comparable to that of the Parallel Virtual File System (PVFS), both requiring about 10 times more CPU. And pCFS’ bandwidth also surpasses GFS’ (600 times for small record sizes, e.g., 4 KB, decreasing down to 2 times for large record sizes, e.g., 4 MB), at about the same CPU usage.Lusitania, Companhia de Seguros S.A, Programa IBM Shared University Research (SUR

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

Analytical considerations for transactional cache protocols

Since the early nineties transactional cache protocols have been intensively studied in the context of client-server database systems. Research has developed a variety of protocols and compared different aspects of their quality using simulation systems and applying semi-standardized benchmarks. Unfortunately none of the related publications substantiated their experimental findings by thorough analytical considerations. We try to close this gap at least partially by presenting comprensive and highly accurate analytical formulas for quality aspects of two important transactional cache protocols. We consider the non-adaptive variants of the "Callback Read Protocol" (CBR) and the "Optimistic Concurrency Control Protocol" (OCC). The paper studies their cache filling size and the number of messages they produce for the so-called UNIFORM workload. In many cases the cache filling size may considerably differ from a given maximum cache size - a phenomenon which has been overlooked by former publications. Moreover for OCC, we also give a highly accurate formula which forecasts the transaction abortion rate. All formulas are compared against corresponding simulation results in order to validate their correctness

Theory and Practice of Transactional Method Caching

Nowadays, tiered architectures are widely accepted for constructing large scale information systems. In this context application servers often form the bottleneck for a system's efficiency. An application server exposes an object oriented interface consisting of set of methods which are accessed by potentially remote clients. The idea of method caching is to store results of read-only method invocations with respect to the application server's interface on the client side. If the client invokes the same method with the same arguments again, the corresponding result can be taken from the cache without contacting the server. It has been shown that this approach can considerably improve a real world system's efficiency. This paper extends the concept of method caching by addressing the case where clients wrap related method invocations in ACID transactions. Demarcating sequences of method calls in this way is supported by many important application server standards. In this context the paper presents an architecture, a theory and an efficient protocol for maintaining full transactional consistency and in particular serializability when using a method cache on the client side. In order to create a protocol for scheduling cached method results, the paper extends a classical transaction formalism. Based on this extension, a recovery protocol and an optimistic serializability protocol are derived. The latter one differs from traditional transactional cache protocols in many essential ways. An efficiency experiment validates the approach: Using the cache a system's performance and scalability are considerably improved

Scalable hosting of web applications

Modern Web sites have evolved from simple monolithic systems to complex multitiered systems. In contrast to traditional Web sites, these sites do not simply deliver pre-written content but dynamically generate content using (one or more) multi-tiered Web applications. In this thesis, we addressed the question: How to host multi-tiered Web applications in a scalable manner? Scaling up a Web application requires scaling its individual tiers. To this end, various research works have proposed techniques that employ replication or caching solutions at different tiers. However, most of these techniques aim to optimize the performance of individual tiers and not the entire application. A key observation made in our research is that there exists no elixir technique that performs the best for allWeb applications. Effective hosting of a Web application requires careful selection and deployment of several techniques at different tiers. To this end, we present several caching and replication strategies, such as GlobeCBC, GlobeDB and GlobeTP, to improve the scalability of different tiers of a Web application. While these techniques and systems improve the performance of the individual tiers (and eventually the application), an application's administrator is not only interested in the performance of its individual tiers but also in its endto- end performance. To this end, we propose a resource provisioning approach that allows us to choose the best resource configuration for hosting a Web application such that its end-to-end response time can be optimized with minimum usage of resources. The proposed approach is based on an analytical model for multi-tier systems, which allows us to derive expressions for estimating the mean end-to-end response time and its variance.Steen, M.R. van [Promotor]Pierre, G.E.O. [Copromotor

Practical database replication

Tese de doutoramento em InformáticaSoftware-based replication is a cost-effective approach for fault-tolerance when combined with commodity hardware. In particular, shared-nothing database clusters built upon commodity machines and synchronized through eager software-based replication protocols have been driven by the distributed systems community in the last decade. The efforts on eager database replication, however, stem from the late 1970s with initial proposals designed by the database community. From that time, we have the distributed locking and atomic commitment protocols. Briefly speaking, before updating a data item, all copies are locked through a distributed lock, and upon commit, an atomic commitment protocol is responsible for guaranteeing that the transaction’s changes are written to a non-volatile storage at all replicas before committing it. Both these processes contributed to a poor performance. The distributed systems community improved these processes by reducing the number of interactions among replicas through the use of group communication and by relaxing the durability requirements imposed by the atomic commitment protocol. The approach requires at most two interactions among replicas and disseminates updates without necessarily applying them before committing a transaction. This relies on a high number of machines to reduce the likelihood of failures and ensure data resilience. Clearly, the availability of commodity machines and their increasing processing power makes this feasible. Proving the feasibility of this approach requires us to build several prototypes and evaluate them with different workloads and scenarios. Although simulation environments are a good starting point, mainly those that allow us to combine real (e.g., replication protocols, group communication) and simulated-code (e.g., database, network), full-fledged implementations should be developed and tested. Unfortunately, database vendors usually do not provide native support for the development of third-party replication protocols, thus forcing protocol developers to either change the database engines, when the source code is available, or construct in the middleware server wrappers that intercept client requests otherwise. The former solution is hard to maintain as new database releases are constantly being produced, whereas the latter represents a strenuous development effort as it requires us to rebuild several database features at the middleware. Unfortunately, the group-based replication protocols, optimistic or conservative, that had been proposed so far have drawbacks that present a major hurdle to their practicability. The optimistic protocols make it difficult to commit transactions in the presence of hot-spots, whereas the conservative protocols have a poor performance due to concurrency issues. In this thesis, we propose using a generic architecture and programming interface, titled GAPI, to facilitate the development of different replication strategies. The idea consists of providing key extensions to multiple DBMSs (Database Management Systems), thus enabling a replication strategy to be developed once and tested on several databases that have such extensions, i.e., those that are replication-friendly. To tackle the aforementioned problems in groupbased replication protocols, we propose using a novel protocol, titled AKARA. AKARA guarantees fairness, and thus all transactions have a chance to commit, and ensures great performance while exploiting parallelism as provided by local database engines. Finally, we outline a simple but comprehensive set of components to build group-based replication protocols and discuss key points in its design and implementation.A replicação baseada em software é uma abordagem que fornece um bom custo benefício para tolerância a falhas quando combinada com hardware commodity. Em particular, os clusters de base de dados “shared-nothing” construídos com hardware commodity e sincronizados através de protocolos “eager” têm sido impulsionados pela comunidade de sistemas distribuídos na última década. Os primeiros esforços na utilização dos protocolos “eager”, decorrem da década de 70 do século XX com as propostas da comunidade de base de dados. Dessa época, temos os protocolos de bloqueio distribuído e de terminação atómica (i.e. “two-phase commit”). De forma sucinta, antes de actualizar um item de dados, todas as cópias são bloqueadas através de um protocolo de bloqueio distribuído e, no momento de efetivar uma transacção, um protocolo de terminação atómica é responsável por garantir que as alterações da transacção são gravadas em todas as réplicas num sistema de armazenamento não-volátil. No entanto, ambos os processos contribuem para um mau desempenho do sistema. A comunidade de sistemas distribuídos melhorou esses processos, reduzindo o número de interacções entre réplicas, através do uso da comunicação em grupo e minimizando a rigidez os requisitos de durabilidade impostos pelo protocolo de terminação atómica. Essa abordagem requer no máximo duas interacções entre as réplicas e dissemina actualizações sem necessariamente aplicá-las antes de efectivar uma transacção. Para funcionar, a solução depende de um elevado número de máquinas para reduzirem a probabilidade de falhas e garantir a resiliência de dados. Claramente, a disponibilidade de hardware commodity e o seu poder de processamento crescente tornam essa abordagem possível. Comprovar a viabilidade desta abordagem obriga-nos a construir vários protótipos e a avaliálos com diferentes cargas de trabalho e cenários. Embora os ambientes de simulação sejam um bom ponto de partida, principalmente aqueles que nos permitem combinar o código real (por exemplo, protocolos de replicação, a comunicação em grupo) e o simulado (por exemplo, base de dados, rede), implementações reais devem ser desenvolvidas e testadas. Infelizmente, os fornecedores de base de dados, geralmente, não possuem suporte nativo para o desenvolvimento de protocolos de replicação de terceiros, forçando os desenvolvedores de protocolo a mudar o motor de base de dados, quando o código fonte está disponível, ou a construir no middleware abordagens que interceptam as solicitações do cliente. A primeira solução é difícil de manter já que novas “releases” das bases de dados estão constantemente a serem produzidas, enquanto a segunda representa um desenvolvimento árduo, pois obriga-nos a reconstruir vários recursos de uma base de dados no middleware. Infelizmente, os protocolos de replicação baseados em comunicação em grupo, optimistas ou conservadores, que foram propostos até agora apresentam inconvenientes que são um grande obstáculo à sua utilização. Com os protocolos optimistas é difícil efectivar transacções na presença de “hot-spots”, enquanto que os protocolos conservadores têm um fraco desempenho devido a problemas de concorrência. Nesta tese, propomos utilizar uma arquitetura genérica e uma interface de programação, intitulada GAPI, para facilitar o desenvolvimento de diferentes estratégias de replicação. A ideia consiste em fornecer extensões chaves para múltiplos SGBDs (Database Management Systems), permitindo assim que uma estratégia de replicação possa ser desenvolvida uma única vez e testada em várias bases de dados que possuam tais extensões, ou seja, aquelas que são “replicationfriendly”. Para resolver os problemas acima referidos nos protocolos de replicação baseados em comunicação em grupo, propomos utilizar um novo protocolo, intitulado AKARA. AKARA garante a equidade, portanto, todas as operações têm uma oportunidade de serem efectivadas, e garante um excelente desempenho ao tirar partido do paralelismo fornecido pelos motores de base de dados. Finalmente, propomos um conjunto simples, mas abrangente de componentes para construir protocolos de replicação baseados em comunicação em grupo e discutimos pontoschave na sua concepção e implementação

Hyperscale Data Processing With Network-Centric Designs

Today’s largest data processing workloads are hosted in cloud data centers. Due to unprecedented data growth and the end of Moore’s Law, these workloads have ballooned to the hyperscale level, encompassing billions to trillions of data items and hundreds to thousands of machines per query. Enabling and expanding with these workloads are highly scalable data center networks that connect up to hundreds of thousands of networked servers. These massive scales fundamentally challenge the designs of both data processing systems and data center networks, and the classic layered designs are no longer sustainable. Rather than optimize these massive layers in silos, we build systems across them with principled network-centric designs. In current networks, we redesign data processing systems with network-awareness to minimize the cost of moving data in the network. In future networks, we propose new interfaces and services that the cloud infrastructure offers to applications and codesign data processing systems to achieve optimal query processing performance. To transform the network to future designs, we facilitate network innovation at scale. This dissertation presents a line of systems work that covers all three directions. It first discusses GraphRex, a network-aware system that combines classic database and systems techniques to push the performance of massive graph queries in current data centers. It then introduces data processing in disaggregated data centers, a promising new cloud proposal. It details TELEPORT, a compute pushdown feature that eliminates data processing performance bottlenecks in disaggregated data centers, and Redy, which provides high-performance caches using remote disaggregated memory. Finally, it presents MimicNet, a fine-grained simulation framework that evaluates network proposals at datacenter scale with machine learning approximation. These systems demonstrate that our ideas in network-centric designs achieve orders of magnitude higher efficiency compared to the state of the art at hyperscale