Database recovery

Recovery techniques are an important aspect of database systems. They are essential to ensure that data integrity is maintained after any type of failure occurs. The recovery mechanism must be designed so that the availability and performance of the system are not unacceptably impacted by the recovery algorithms running during normal execution. On the other hand, enough information must be stored so that the database can be restored or transactions backed out in a reasonable amount of time. Concepts, techniques, and problems associated with database recovery will be presented in this thesis. The recovery issues for both centralized and distributed systems will be discussed, along with the tradeoffs of different recovery tools. The database recovery schemes in IMS/VS, DB2 and SDD-1 will be described to show approaches in existing systems

FastPay: High-Performance Byzantine Fault Tolerant Settlement

FastPay allows a set of distributed authorities, some of which are Byzantine, to maintain a high-integrity and availability settlement system for pre-funded payments. It can be used to settle payments in a native unit of value (crypto-currency), or as a financial side-infrastructure to support retail payments in fiat currencies. FastPay is based on Byzantine Consistent Broadcast as its core primitive, foregoing the expenses of full atomic commit channels (consensus). The resulting system has low-latency for both confirmation and payment finality. Remarkably, each authority can be sharded across many machines to allow unbounded horizontal scalability. Our experiments demonstrate intra-continental confirmation latency of less than 100ms, making FastPay applicable to point of sale payments. In laboratory environments, we achieve over 80,000 transactions per second with 20 authorities---surpassing the requirements of current retail card payment networks, while significantly increasing their robustness

Middleware-based Database Replication: The Gaps between Theory and Practice

The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in isolation, overlooking the need for completeness in their solutions, while commercial teams take a holistic approach that often misses opportunities for fundamental innovation. This has created over time a gap between academic research and industrial practice. This paper aims to characterize the gap along three axes: performance, availability, and administration. We build on our own experience developing and deploying replication systems in commercial and academic settings, as well as on a large body of prior related work. We sift through representative examples from the last decade of open-source, academic, and commercial database replication systems and combine this material with case studies from real systems deployed at Fortune 500 customers. We propose two agendas, one for academic research and one for industrial R&D, which we believe can bridge the gap within 5-10 years. This way, we hope to both motivate and help researchers in making the theory and practice of middleware-based database replication more relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on Management of Data, Vancouver, Canada, June 200

Recovery algorithms for in-memory OLTP databases

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 63-66).Fine-grained, record-oriented write-ahead logging, as exemplified by systems like ARIES, has been the gold standard for relational database recovery. In this thesis, we show that in modern high-throughput transaction processing systems, this is no longer the optimal way to recover a database system. In particular, as transaction throughputs get higher, ARIES-style logging starts to represent a non-trivial fraction of the overall transaction execution time. We propose a lighter weight, coarse-grained command logging technique which only records the transactions that were executed on the database. It then does recovery by starting from a transactionally consistent checkpoint and replaying the commands in the log as if they were new transactions. By avoiding the overhead of fine-grained, page-level logging of before and after images (and substantial associated I/O), command logging can yield significantly higher throughput at run-time. Recovery times for command logging are higher compared to ARIES, but especially with the advent of high-availability techniques that can mask the outage of a recovering node, recovery speeds have become secondary in importance to run-time performance for most applications. We evaluated our approach on an implementation of TPC-C in a main memory database system (VoltDB), and found that command logging can offer 1.5x higher throughput than a main-memory optimized implementation of ARIES.by Nirmesh Malviya.S.M

Toward Message Passing Failure Management

As machine sizes have increased and application runtimes have lengthened, research into fault tolerance has evolved alongside. Moving from result checking, to rollback recovery, and to algorithm based fault tolerance, the type of recovery being performed has changed, but the programming model in which it executes has remained virtually static since the publication of the original Message Passing Interface (MPI) Standard in 1992. Since that time, applications have used a message passing paradigm to communicate between processes, but they could not perform process recovery within an MPI implementation due to limitations of the MPI Standard. This dissertation describes a new protocol using the exiting MPI Standard called Checkpoint-on-Failure to perform limited fault tolerance within the current framework of MPI, and proposes a new platform titled User Level Failure Mitigation (ULFM) to build more complete and complex fault tolerance solutions with a true fault tolerant MPI implementation. We will demonstrate the overhead involved in using these fault tolerant solutions and give examples of applications and libraries which construct other fault tolerance mechanisms based on the constructs provided in ULFM

Improving Scalability of Application-Level Checkpoint-Recovery by Reducing Checkpoint Sizes

This is a post-peer-review, pre-copyedit version of an article published in New Generation Computing. The final authenticated version is available online at: https://doi.org/10.1007/s00354-013-0302-4[Abstract] The execution times of large-scale parallel applications on nowadays multi/many-core systems are usually longer than the mean time between failures. Therefore, parallel applications must tolerate hardware failures to ensure that not all computation done is lost on machine failures. Checkpointing and rollback recovery is one of the most popular techniques to implement fault-tolerant applications. However, checkpointing parallel applications is expensive in terms of computing time, network utilization and storage resources. Thus, current checkpoint-recovery techniques should minimize these costs in order to be useful for large scale systems. In this paper three different and complementary techniques to reduce the size of the checkpoints generated by application-level checkpointing are proposed and implemented. Detailed experimental results obtained on a multicore cluster show the effectiveness of the proposed methods to reduce checkpointing cost.Ministerio de Ciencia e Innovación; TIN2010-16735Galicia. Consellería de Economía e Industria; 10PXIB105180P

Mathematics in Software Reliability and Quality Assurance

This monograph concerns the mathematical aspects of software reliability and quality assurance and consists of 11 technical papers in this emerging area. Included are the latest research results related to formal methods and design, automatic software testing, software verification and validation, coalgebra theory, automata theory, hybrid system and software reliability modeling and assessment