The network is the database

Master'sMASTER OF SCIENC

Transactional concurrency control for resource constrained applications

PhD ThesisTransactions have long been used as a mechanism for ensuring the consistency of databases. Databases, and associated transactional approaches, have always been an active area of research as different application domains and computing architectures have placed ever more elaborate requirements on shared data access. As transactions typically provide consistency at the expense of timeliness (abort/retry) and resource (duplicate shared data and locking), there has been substantial efforts to limit these two aspects of transactions while still satisfying application requirements. In environments where clients are geographically distant from a database the consistency/performance trade-off becomes acute as any retrieval of data over a network is not only expensive, but relatively slow compared to co-located client/database systems. Furthermore, for battery powered clients the increased overhead of transactions can also be viewed as a significant power overhead. However, for all their drawbacks transactions do provide the data consistency that is a requirement for many application types. In this Thesis we explore the solution space related to timely transactional systems for remote clients and centralised databases with a focus on providing a solution, that, when compared to other's work in this domain: (a) maintains consistency; (b) lowers latency; (c) improves throughput. To achieve this we revisit a technique first developed to decrease disk access times via local caching of state (for aborted transactions) to tackle the problems prevalent in real-time databases. We demonstrate that such a technique (rerun) allows a significant change in the typical structure of a transaction (one never before considered, even in rerun systems). Such a change itself brings significant performance success not only in the traditional rerun local database solution space, but also in the distributed solution space. A byproduct of our improvements also, one can argue, brings about a "greener" solution as less time coupled with improved throughput affords improved battery life for mobile devices

Research issues in real-time database systems

Cataloged from PDF version of article.Today's real-time systems are characterized by managing large volumes of data. Efficient database management algorithms for accessing and manipulating data are required to satisfy timing constraints of supported applications. Real-time database systems involve a new research area investigating possible ways of applying database systems technology to real-time systems. Management of real-time information through a database system requires the integration of concepts from both real-time systems and database systems. Some new criteria need to be developed to involve timing constraints of real-time applications in many database systems design issues, such as transaction/query processing, data buffering, CPU, and IO scheduling. In this paper, a basic understanding of the issues in real-time database systems is provided and the research efforts in this area are introduced. Different approaches to various problems of real-time database systems are briefly described, and possible future research directions are discussed

A Survey of Traditional and Practical Concurrency Control in Relational Database Management Systems

Traditionally, database theory has focused on concepts such as atomicity and serializability, asserting that concurrent transaction management must enable correctness above all else. Textbooks and academic journals detail a vision of unbounded rationality, where reduced throughput because of concurrency protocols is not of tremendous concern. This thesis seeks to survey the traditional basis for concurrency in relational database management systems and contrast that with actual practice. SQL-92, the current standard for concurrency in relational database management systems has defined isolation, or allowable concurrency levels, and these are examined. Some ways in which DB2, a popular database, interprets these levels and finesses extra concurrency through performance enhancement are detailed. SQL-92 standardizes de facto relational database management systems features. Given this and a superabundance of articles in professional journals detailing steps for fine-tuning transaction concurrency, the expansion of performance tuning seems bright, even at the expense of serializabilty. Are the practical changes wrought by non-academic professionals killing traditional database concurrency ideals? Not really. Reasoned changes for performance gains advocate compromise, using complex concurrency controls when necessary for the job at hand and relaxing standards otherwise. The idea of relational database management systems is only twenty years old, and standards are still evolving. Is there still an interplay between tradition and practice? Of course. Current practice uses tradition pragmatically, not idealistically. Academic ideas help drive the systems available for use, and perhaps current practice now will help academic ideas define concurrency control concepts for relational database management systems

Speculation in Parallel and Distributed Event Processing Systems

Event stream processing (ESP) applications enable the real-time processing of continuous flows of data. Algorithmic trading, network monitoring, and processing data from sensor networks are good examples of applications that traditionally rely upon ESP systems. In addition, technological advances are resulting in an increasing number of devices that are network enabled, producing information that can be automatically collected and processed. This increasing availability of on-line data motivates the development of new and more sophisticated applications that require low-latency processing of large volumes of data. ESP applications are composed of an acyclic graph of operators that is traversed by the data. Inside each operator, the events can be transformed, aggregated, enriched, or filtered out. Some of these operations depend only on the current input events, such operations are called stateless. Other operations, however, depend not only on the current event, but also on a state built during the processing of previous events. Such operations are, therefore, named stateful. As the number of ESP applications grows, there are increasingly strong requirements, which are often difficult to satisfy. In this dissertation, we address two challenges created by the use of stateful operations in a ESP application: (i) stateful operators can be bottlenecks because they are sensitive to the order of events and cannot be trivially parallelized by replication; and (ii), if failures are to be tolerated, the accumulated state of an stateful operator needs to be saved, saving this state traditionally imposes considerable performance costs. Our approach is to evaluate the use of speculation to address these two issues. For handling ordering and parallelization issues in a stateful operator, we propose a speculative approach that both reduces latency when the operator must wait for the correct ordering of the events and improves throughput when the operation in hand is parallelizable. In addition, our approach does not require that user understand concurrent programming or that he or she needs to consider out-of-order execution when writing the operations. For fault-tolerant applications, traditional approaches have imposed prohibitive performance costs due to pessimistic schemes. We extend such approaches, using speculation to mask the cost of fault tolerance.:1 Introduction 1 1.1 Event stream processing systems ......................... 1 1.2 Running example ................................. 3 1.3 Challenges and contributions ........................... 4 1.4 Outline ...................................... 6 2 Background 7 2.1 Event stream processing ............................. 7 2.1.1 State in operators: Windows and synopses ............................ 8 2.1.2 Types of operators ............................ 12 2.1.3 Our prototype system........................... 13 2.2 Software transactional memory.......................... 18 2.2.1 Overview ................................. 18 2.2.2 Memory operations............................ 19 2.3 Fault tolerance in distributed systems ...................................... 23 2.3.1 Failure model and failure detection ...................................... 23 2.3.2 Recovery semantics............................ 24 2.3.3 Active and passive replication ...................... 24 2.4 Summary ..................................... 26 3 Extending event stream processing systems with speculation 27 3.1 Motivation..................................... 27 3.2 Goals ....................................... 28 3.3 Local versus distributed speculation ....................... 29 3.4 Models and assumptions ............................. 29 3.4.1 Operators................................. 30 3.4.2 Events................................... 30 3.4.3 Failures .................................. 31 4 Local speculation 33 4.1 Overview ..................................... 33 4.2 Requirements ................................... 35 4.2.1 Order ................................... 35 4.2.2 Aborts................................... 37 4.2.3 Optimism control ............................. 38 4.2.4 Notifications ............................... 39 4.3 Applications.................................... 40 4.3.1 Out-of-order processing ......................... 40 4.3.2 Optimistic parallelization......................... 42 4.4 Extensions..................................... 44 4.4.1 Avoiding unnecessary aborts ....................... 44 4.4.2 Making aborts unnecessary........................ 45 4.5 Evaluation..................................... 47 4.5.1 Overhead of speculation ......................... 47 4.5.2 Cost of misspeculation .......................... 50 4.5.3 Out-of-order and parallel processing micro benchmarks ........... 53 4.5.4 Behavior with example operators .................... 57 4.6 Summary ..................................... 60 5 Distributed speculation 63 5.1 Overview ..................................... 63 5.2 Requirements ................................... 64 5.2.1 Speculative events ............................ 64 5.2.2 Speculative accesses ........................... 69 5.2.3 Reliable ordered broadcast with optimistic delivery .................. 72 5.3 Applications .................................... 75 5.3.1 Passive replication and rollback recovery ................................ 75 5.3.2 Active replication ............................. 80 5.4 Extensions ..................................... 82 5.4.1 Active replication and software bugs ..................................... 82 5.4.2 Enabling operators to output multiple events ........................ 87 5.5 Evaluation .................................... 87 5.5.1 Passive replication ............................ 88 5.5.2 Active replication ............................. 88 5.6 Summary ..................................... 93 6 Related work 95 6.1 Event stream processing engines ......................... 95 6.2 Parallelization and optimistic computing ................................ 97 6.2.1 Speculation ................................ 97 6.2.2 Optimistic parallelization ......................... 98 6.2.3 Parallelization in event processing .................................... 99 6.2.4 Speculation in event processing ..................... 99 6.3 Fault tolerance .................................. 100 6.3.1 Passive replication and rollback recovery ............................... 100 6.3.2 Active replication ............................ 101 6.3.3 Fault tolerance in event stream processing systems ............. 103 7 Conclusions 105 7.1 Summary of contributions ............................ 105 7.2 Challenges and future work ............................ 106 Appendices Publications 107 Pseudocode for the consensus protocol 10

A Comparative Study of Divergence Control Algorithms

This paper evaluates and compares the performance of two-phase locking divergence control (2PLDC) and optimistic divergence control (ODC) algorithms using a comprehensive centralized database simulation model. We examine a system with multiclass workloads in which on-line update transactions and long-duration queries progress based on epsilon serializability (ESR). Our results demonstrate that significant performance enhancements can be achieved with a non-zero tolerable inconsistency (ϵ-spec). With sufficient ϵ-spec and limited system resources, both algorithms achieve comparable performance. However, with low resource contention, ODC performs significantly better than 2PLDC. Moreover, given a small ϵ-spec, ODC returns more accurate results on the committed queries then 2PLDC

Speculation in Parallel and Distributed Event Processing Systems

Event stream processing (ESP) applications enable the real-time processing of continuous flows of data. Algorithmic trading, network monitoring, and processing data from sensor networks are good examples of applications that traditionally rely upon ESP systems. In addition, technological advances are resulting in an increasing number of devices that are network enabled, producing information that can be automatically collected and processed. This increasing availability of on-line data motivates the development of new and more sophisticated applications that require low-latency processing of large volumes of data. ESP applications are composed of an acyclic graph of operators that is traversed by the data. Inside each operator, the events can be transformed, aggregated, enriched, or filtered out. Some of these operations depend only on the current input events, such operations are called stateless. Other operations, however, depend not only on the current event, but also on a state built during the processing of previous events. Such operations are, therefore, named stateful. As the number of ESP applications grows, there are increasingly strong requirements, which are often difficult to satisfy. In this dissertation, we address two challenges created by the use of stateful operations in a ESP application: (i) stateful operators can be bottlenecks because they are sensitive to the order of events and cannot be trivially parallelized by replication; and (ii), if failures are to be tolerated, the accumulated state of an stateful operator needs to be saved, saving this state traditionally imposes considerable performance costs. Our approach is to evaluate the use of speculation to address these two issues. For handling ordering and parallelization issues in a stateful operator, we propose a speculative approach that both reduces latency when the operator must wait for the correct ordering of the events and improves throughput when the operation in hand is parallelizable. In addition, our approach does not require that user understand concurrent programming or that he or she needs to consider out-of-order execution when writing the operations. For fault-tolerant applications, traditional approaches have imposed prohibitive performance costs due to pessimistic schemes. We extend such approaches, using speculation to mask the cost of fault tolerance.:1 Introduction 1 1.1 Event stream processing systems ......................... 1 1.2 Running example ................................. 3 1.3 Challenges and contributions ........................... 4 1.4 Outline ...................................... 6 2 Background 7 2.1 Event stream processing ............................. 7 2.1.1 State in operators: Windows and synopses ............................ 8 2.1.2 Types of operators ............................ 12 2.1.3 Our prototype system........................... 13 2.2 Software transactional memory.......................... 18 2.2.1 Overview ................................. 18 2.2.2 Memory operations............................ 19 2.3 Fault tolerance in distributed systems ...................................... 23 2.3.1 Failure model and failure detection ...................................... 23 2.3.2 Recovery semantics............................ 24 2.3.3 Active and passive replication ...................... 24 2.4 Summary ..................................... 26 3 Extending event stream processing systems with speculation 27 3.1 Motivation..................................... 27 3.2 Goals ....................................... 28 3.3 Local versus distributed speculation ....................... 29 3.4 Models and assumptions ............................. 29 3.4.1 Operators................................. 30 3.4.2 Events................................... 30 3.4.3 Failures .................................. 31 4 Local speculation 33 4.1 Overview ..................................... 33 4.2 Requirements ................................... 35 4.2.1 Order ................................... 35 4.2.2 Aborts................................... 37 4.2.3 Optimism control ............................. 38 4.2.4 Notifications ............................... 39 4.3 Applications.................................... 40 4.3.1 Out-of-order processing ......................... 40 4.3.2 Optimistic parallelization......................... 42 4.4 Extensions..................................... 44 4.4.1 Avoiding unnecessary aborts ....................... 44 4.4.2 Making aborts unnecessary........................ 45 4.5 Evaluation..................................... 47 4.5.1 Overhead of speculation ......................... 47 4.5.2 Cost of misspeculation .......................... 50 4.5.3 Out-of-order and parallel processing micro benchmarks ........... 53 4.5.4 Behavior with example operators .................... 57 4.6 Summary ..................................... 60 5 Distributed speculation 63 5.1 Overview ..................................... 63 5.2 Requirements ................................... 64 5.2.1 Speculative events ............................ 64 5.2.2 Speculative accesses ........................... 69 5.2.3 Reliable ordered broadcast with optimistic delivery .................. 72 5.3 Applications .................................... 75 5.3.1 Passive replication and rollback recovery ................................ 75 5.3.2 Active replication ............................. 80 5.4 Extensions ..................................... 82 5.4.1 Active replication and software bugs ..................................... 82 5.4.2 Enabling operators to output multiple events ........................ 87 5.5 Evaluation .................................... 87 5.5.1 Passive replication ............................ 88 5.5.2 Active replication ............................. 88 5.6 Summary ..................................... 93 6 Related work 95 6.1 Event stream processing engines ......................... 95 6.2 Parallelization and optimistic computing ................................ 97 6.2.1 Speculation ................................ 97 6.2.2 Optimistic parallelization ......................... 98 6.2.3 Parallelization in event processing .................................... 99 6.2.4 Speculation in event processing ..................... 99 6.3 Fault tolerance .................................. 100 6.3.1 Passive replication and rollback recovery ............................... 100 6.3.2 Active replication ............................ 101 6.3.3 Fault tolerance in event stream processing systems ............. 103 7 Conclusions 105 7.1 Summary of contributions ............................ 105 7.2 Challenges and future work ............................ 106 Appendices Publications 107 Pseudocode for the consensus protocol 10

Using Actors to Build a Parallel DBMS

In this paper, we present the design and the architecture of a parallel main memory database management system. We focus on concurrency control scheme and recovery. Our prototype is based on the concept of “database actors”, an object-oriented data model well suited for parallelmanipulations. The storage sub system is built upon distributed Ram-files using SDDS (Scalable Distributed Data Structures) techniques. A nested transaction model is proposed and used to handle concurrency access and recovery. We have also proposed novel approach, based on wait-die, to implement a distributed deadlock prevention technique for our model of nested transactions

Optimizing recovery protocols for replicated database systems

En la actualidad, el uso de tecnologías de informacíon y sistemas de cómputo tienen una gran influencia en la vida diaria. Dentro de los sistemas informáticos actualmente en uso, son de gran relevancia los sistemas distribuidos por la capacidad que pueden tener para escalar, proporcionar soporte para la tolerancia a fallos y mejorar el desempeño de aplicaciones y proporcionar alta disponibilidad. Los sistemas replicados son un caso especial de los sistemas distribuidos. Esta tesis está centrada en el área de las bases de datos replicadas debido al uso extendido que en el presente se hace de ellas, requiriendo características como: bajos tiempos de respuesta, alto rendimiento en los procesos, balanceo de carga entre las replicas, consistencia e integridad de datos y tolerancia a fallos. En este contexto, el desarrollo de aplicaciones utilizando bases de datos replicadas presenta dificultades que pueden verse atenuadas mediante el uso de servicios de soporte a mas bajo nivel tales como servicios de comunicacion y pertenencia. El uso de los servicios proporcionados por los sistemas de comunicación de grupos permiten ocultar los detalles de las comunicaciones y facilitan el diseño de protocolos de replicación y recuperación. En esta tesis, se presenta un estudio de las alternativas y estrategias empleadas en los protocolos de replicación y recuperación en las bases de datos replicadas. También se revisan diferentes conceptos sobre los sistemas de comunicación de grupos y sincronia virtual. Se caracterizan y clasifican diferentes tipos de protocolos de replicación con respecto a la interacción o soporte que pudieran dar a la recuperación, sin embargo el enfoque se dirige a los protocolos basados en sistemas de comunicación de grupos. Debido a que los sistemas comerciales actuales permiten a los programadores y administradores de sistemas de bases de datos renunciar en alguna medida a la consistencia con la finalidad de aumentar el rendimiento, es importante determinar el nivel de consistencia necesario. En el caso de las bases de datos replicadas la consistencia está muy relacionada con el nivel de aislamiento establecido entre las transacciones. Una de las propuestas centrales de esta tesis es un protocolo de recuperación para un protocolo de replicación basado en certificación. Los protocolos de replicación de base de datos basados en certificación proveen buenas bases para el desarrollo de sus respectivos protocolos de recuperación cuando se utiliza el nivel de aislamiento snapshot. Para tal nivel de aislamiento no se requiere que los readsets sean transferidos entre las réplicas ni revisados en la fase de cetificación y ya que estos protocolos mantienen un histórico de la lista de writesets que es utilizada para certificar las transacciones, este histórico provee la información necesaria para transferir el estado perdido por la réplica en recuperación. Se hace un estudio del rendimiento del protocolo de recuperación básico y de la versión optimizada en la que se compacta la información a transferir. Se presentan los resultados obtenidos en las pruebas de la implementación del protocolo de recuperación en el middleware de soporte. La segunda propuesta esta basada en aplicar el principio de compactación de la informacion de recuperación en un protocolo de recuperación para los protocolos de replicación basados en votación débil. El objetivo es minimizar el tiempo necesario para transfeir y aplicar la información perdida por la réplica en recuperación obteniendo con esto un protocolo de recuperación mas eficiente. Se ha verificado el buen desempeño de este algoritmo a través de una simulación. Para efectuar la simulación se ha hecho uso del entorno de simulación Omnet++. En los resultados de los experimentos puede apreciarse que este protocolo de recuperación tiene buenos resultados en múltiples escenarios. Finalmente, se presenta la verificación de la corrección de ambos algoritmos de recuperación en el Capítulo 5.Nowadays, information technology and computing systems have a great relevance on our lives. Among current computer systems, distributed systems are one of the most important because of their scalability, fault tolerance, performance improvements and high availability. Replicated systems are a specific case of distributed system. This Ph.D. thesis is centered in the replicated database field due to their extended usage, requiring among other properties: low response times, high throughput, load balancing among replicas, data consistency, data integrity and fault tolerance. In this scope, the development of applications that use replicated databases raises some problems that can be reduced using other fault-tolerant building blocks, as group communication and membership services. Thus, the usage of the services provided by group communication systems (GCS) hides several communication details, simplifying the design of replication and recovery protocols. This Ph.D. thesis surveys the alternatives and strategies being used in the replication and recovery protocols for database replication systems. It also summarizes different concepts about group communication systems and virtual synchrony. As a result, the thesis provides a classification of database replication protocols according to their support to (and interaction with) recovery protocols, always assuming that both kinds of protocol rely on a GCS. Since current commercial DBMSs allow that programmers and database administrators sacrifice consistency with the aim of improving performance, it is important to select the appropriate level of consistency. Regarding (replicated) databases, consistency is strongly related to the isolation levels being assigned to transactions. One of the main proposals of this thesis is a recovery protocol for a replication protocol based on certification. Certification-based database replication protocols provide a good basis for the development of their recovery strategies when a snapshot isolation level is assumed. In that level readsets are not needed in the validation step. As a result, they do not need to be transmitted to other replicas. Additionally, these protocols hold a writeset list that is used in the certification/validation step. That list maintains the set of writesets needed by the recovery protocol. This thesis evaluates the performance of a recovery protocol based on the writeset list tranfer (basic protocol) and of an optimized version that compacts the information to be transferred. The second proposal applies the compaction principle to a recovery protocol designed for weak-voting replication protocols. Its aim is to minimize the time needed for transferring and applying the writesets lost by the recovering replica, obtaining in this way an efficient recovery. The performance of this recovery algorithm has been checked implementing a simulator. To this end, the Omnet++ simulating framework has been used. The simulation results confirm that this recovery protocol provides good results in multiple scenarios. Finally, the correction of both recovery protocols is also justified and presented in Chapter 5.García Muñoz, LH. (2013). Optimizing recovery protocols for replicated database systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/31632TESI