Scalable transactions in the cloud: partitioning revisited

Lecture Notes in Computer Science, 6427Cloud computing is becoming one of the most used paradigms to deploy highly available and scalable systems. These systems usually demand the management of huge amounts of data, which cannot be solved with traditional nor replicated database systems as we know them. Recent solutions store data in special key-value structures, in an approach that commonly lacks the consistency provided by transactional guarantees, as it is traded for high scalability and availability. In order to ensure consistent access to the information, the use of transactions is required. However, it is well-known that traditional replication protocols do not scale well for a cloud environment. Here we take a look at current proposals to deploy transactional systems in the cloud and we propose a new system aiming at being a step forward in achieving this goal. We proceed to focus on data partitioning and describe the key role it plays in achieving high scalability.This work has been partially supported by the Spanish Government under grant TIN2009-14460-C03-02 and by the Spanish MEC under grant BES-2007-17362 and by project ReD Resilient Database Clusters (PDTC/EIA-EIA/109044/2008)

Parallel Deferred Update Replication

Deferred update replication (DUR) is an established approach to implementing highly efficient and available storage. While the throughput of read-only transactions scales linearly with the number of deployed replicas in DUR, the throughput of update transactions experiences limited improvements as replicas are added. This paper presents Parallel Deferred Update Replication (P-DUR), a variation of classical DUR that scales both read-only and update transactions with the number of cores available in a replica. In addition to introducing the new approach, we describe its full implementation and compare its performance to classical DUR and to Berkeley DB, a well-known standalone database

Ensuring Serializable Executions with Snapshot Isolation DBMS

Snapshot Isolation (SI) is a multiversion concurrency control that has been implemented by open source and commercial database systems such as PostgreSQL and Oracle. The main feature of SI is that a read operation does not block a write operation and vice versa, which allows higher degree of concurrency than traditional two-phase locking. SI prevents many anomalies that appear in other isolation levels, but it still can result in non-serializable execution, in which database integrity constraints can be violated. Several techniques have been proposed to ensure serializable execution with engines running SI; these techniques are based on modifying the applications by introducing conflicting SQL statements. However, with each of these techniques the DBA has to make a difficult choice among possible transactions to modify. This thesis helps the DBA’s to choose between these different techniques and choices by understanding how the choices affect system performance. It also proposes a novel technique called ’External Lock Manager’ (ELM) which introduces conflicts in a separate lock-manager object so that every execution will be serializable. We build a prototype system for ELM and we run experiments to demonstrate the robustness of the new technique compare to the previous techniques. Experiments show that modifying the application code for some transactions has a high impact on performance for some choices, which makes it very hard for DBA’s to choose wisely. However, ELM has peak performance which is similar to SI, no matter which transactions are chosen for modification. Thus we say that ELM is a robust technique for ensure serializable execution

Ensuring Serializable Executions with Snapshot Isolation DBMS

Snapshot Isolation (SI) is a multiversion concurrency control that has been implemented by open source and commercial database systems such as PostgreSQL and Oracle. The main feature of SI is that a read operation does not block a write operation and vice versa, which allows higher degree of concurrency than traditional two-phase locking. SI prevents many anomalies that appear in other isolation levels, but it still can result in non-serializable execution, in which database integrity constraints can be violated. Several techniques have been proposed to ensure serializable execution with engines running SI; these techniques are based on modifying the applications by introducing conflicting SQL statements. However, with each of these techniques the DBA has to make a difficult choice among possible transactions to modify. This thesis helps the DBA’s to choose between these different techniques and choices by understanding how the choices affect system performance. It also proposes a novel technique called ’External Lock Manager’ (ELM) which introduces conflicts in a separate lock-manager object so that every execution will be serializable. We build a prototype system for ELM and we run experiments to demonstrate the robustness of the new technique compare to the previous techniques. Experiments show that modifying the application code for some transactions has a high impact on performance for some choices, which makes it very hard for DBA’s to choose wisely. However, ELM has peak performance which is similar to SI, no matter which transactions are chosen for modification. Thus we say that ELM is a robust technique for ensure serializable execution

Enabling distributed key-value stores with low latency-impact snapshot support

Current distributed key-value stores generally provide greater scalability at the expense of weaker consistency and isolation. However, additional isolation support is becoming increasingly important in the environments in which these stores are deployed, where different kinds of applications with different needs are executed, from transactional workloads to data analytics. While fully-fledged ACID support may not be feasible, it is still possible to take advantage of the design of these data stores, which often include the notion of multiversion concurrency control, to enable them with additional features at a much lower performance cost and maintaining its scalability and availability. In this paper we explore the effects that additional consistency guarantees and isolation capabilities may have on a state of the art key-value store: Apache Cassandra. We propose and implement a new multiversioned isolation level that provides stronger guarantees without compromising Cassandra's scalability and availability. As shown in our experiments, our version of Cassandra allows Snapshot Isolation-like transactions, preserving the overall performance and scalability of the system.This work is partially supported by the Ministry of Science and Technology of Spain and the European Union’s FEDER funds (TIN2007-60625, TIN2012-34557), by the Generalitat de Catalunya (2009-SGR-980), by the BSC-CNS Severo Ochoa program (SEV-2011-00067), by the HiPEAC European Network of Excellence (IST- 004408, FP7-ICT-217068, FP7-ICT-287759), and by IBM through the 2008 and 2010 IBM Faculty Award program.Peer ReviewedPostprint (author’s final draft

Cost- and workload-driven data management in the cloud

This thesis deals with the challenge of finding the right balance between consistency, availability, latency and costs, captured by the CAP/PACELC trade-offs, in the context of distributed data management in the Cloud. At the core of this work, cost and workload-driven data management protocols, called CCQ protocols, are developed. First, this includes the development of C3, which is an adaptive consistency protocol that is able to adjust consistency at runtime by considering consistency and inconsistency costs. Second, the development of Cumulus, an adaptive data partitioning protocol, that can adapt partitions by considering the application workload so that expensive distributed transactions are minimized or avoided. And third, the development of QuAD, a quorum-based replication protocol, that constructs the quorums in such a way so that, given a set of constraints, the best possible performance is achieved. The behavior of each CCQ protocol is steered by a cost model, which aims at reducing the costs and overhead for providing the desired data management guarantees. The CCQ protocols are able to continuously assess their behavior, and if necessary to adapt the behavior at runtime based on application workload and the cost model. This property is crucial for applications deployed in the Cloud, as they are characterized by a highly dynamic workload, and high scalability and availability demands. The dynamic adaptation of the behavior at runtime does not come for free, and may generate considerable overhead that might outweigh the gain of adaptation. The CCQ cost models incorporate a control mechanism, which aims at avoiding expensive and unnecessary adaptations, which do not provide any benefits to applications. The adaptation is a distributed activity that requires coordination between the sites in a distributed database system. The CCQ protocols implement safe online adaptation approaches, which exploit the properties of 2PC and 2PL to ensure that all sites behave in accordance with the cost model, even in the presence of arbitrary failures. It is crucial to guarantee a globally consistent view of the behavior, as in contrary the effects of the cost models are nullified. The presented protocols are implemented as part of a prototypical database system. Their modular architecture allows for a seamless extension of the optimization capabilities at any level of their implementation. Finally, the protocols are quantitatively evaluated in a series of experiments executed in a real Cloud environment. The results show their feasibility and ability to reduce application costs, and to dynamically adjust the behavior at runtime without violating their correctness

Application-level caching with transactional consistency

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from PDF version of thesis.Includes bibliographical references (p. 147-159).Distributed in-memory application data caches like memcached are a popular solution for scaling database-driven web sites. These systems increase performance significantly by reducing load on both the database and application servers. Unfortunately, such caches present two challenges for application developers. First, they cannot ensure that the application sees a consistent view of the data within a transaction, violating the isolation properties of the underlying database. Second, they leave the application responsible for locating data in the cache and keeping it up to date, a frequent source of application complexity and programming errors. This thesis addresses both of these problems in a new cache called TxCache. TxCache is a transactional cache: it ensures that any data seen within a transaction, whether from the cache or the database, reflects a slightly stale but consistent snapshot of the database. TxCache also offers a simple programming model. Application developers simply designate certain functions as cacheable, and the system automatically caches their results and invalidates the cached data as the underlying database changes. Our experiments found that TxCache can substantially increase the performance of a web application: on the RUBiS benchmark, it increases throughput by up to 5.2x relative to a system without caching. More importantly, on this application, TxCache achieves performance comparable (within 5%) to that of a non-transactional cache, showing that consistency does not have to come at the price of performance.by Dan R. K. Ports.Ph.D