Analytical response time estimation in parallel relational database systems

Techniques for performance estimation in parallel database systems are well established for parameters such as throughput, bottlenecks and resource utilisation. However, response time estimation is a complex activity which is difficult to predict and has attracted research for a number of years. Simulation is one option for predicting response time but this is a costly process. Analytical modelling is a less expensive option but requires approximations and assumptions about the queueing networks built up in real parallel database machines which are often questionable and few of the papers on analytical approaches are backed by results from validation against real machines. This paper describes a new analytical approach for response time estimation that is based on a detailed study of different approaches and assumptions. The approach has been validated against two commercial parallel DBMSs running on actual parallel machines and is shown to produce acceptable accuracy

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

Performance models of concurrency control protocols for transaction processing systems

Transaction processing plays a key role in a lot of IT infrastructures. It is widely used in a variety of contexts, spanning from database management systems to concurrent programming tools. Transaction processing systems leverage on concurrency control protocols, which allow them to concurrently process transactions preserving essential properties, as isolation and atomicity. Performance is a critical aspect of transaction processing systems, and it is unavoidably affected by the concurrency control. For this reason, methods and techniques to assess and predict the performance of concurrency control protocols are of interest for many IT players, including application designers, developers and system administrators. The analysis and the proper understanding of the impact on the system performance of these protocols require quantitative approaches. Analytical modeling is a practical approach for building cost-effective computer system performance models, enabling us to quantitatively describe the complex dynamics characterizing these systems. In this dissertation we present analytical performance models of concurrency control protocols. We deal with both traditional transaction processing systems, such as database management systems, and emerging ones, as transactional memories. The analysis focuses on widely used protocols, providing detailed performance models and validation studies. In addition, we propose new modeling approaches, which also broaden the scope of our study towards a more realistic, application-oriented, performance analysis

Modelling parallel database management systems for performance prediction

Abstract unavailable please refer to PD

Transaction management on collaborative application services

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2000.Includes bibliographical references (leaves 86-87).by Koon-Po Paul Wong.M.Eng

Performance analysis of data sharing environments

A data sharing environment consists of multiple loosely coupled transaction processing nodes sharing a common database at the disk level. Apart from the private buffers in each node, the environment may contain an additional global shared buffer in the form of disk cache, file server cache or intermediate shared memory. In this dissertation, we develop a comprehensive analytical model for such a complex environment using a hierarchical approach, where the concurrency control, the CPU queueing discipline and the buffer hit probabilities of the private and shared buffers are first modeled separately, and then integrated through an iterative procedure. To this end, we develop two new submodels: (1) the private buffer model that captures the effects of multi-system buffer invalidation, skewed database access, LRU buffer replacement policy and the rerun transactions, and (2) the shared buffer modeling framework that captures the effects of dependence between the contents of private and the shared buffers, and is used to analyze various shared buffer management policies (SBMPs) proposed in this dissertation. The various policies propagate a granule into the shared buffer after one or more of the following events: database update, shared buffer miss and private buffer replacement. The analytical model is then used to investigate various issues in the design of data sharing environment. Scalability. The model predicts degradation in transaction response time as new nodes are added to the system. Buffer utilization. The model predicts the effectiveness of additional buffer allocation for both the private and shared buffers. Skewed access. The skewed access increases both data contention and buffer hit probability in the system. The resultant effect on the transaction response time is investigated. The response time is found to be more sensitive to skewed data access under two-phase locking (2PL) than under optimistic concurrency control (OCC) protocol. The skewed access also magnifies the effect of invalidation and reduces the utilization of private buffers. Policy selection. The modeling framework is used to select the best SBMP for a given parameter range (private and shared buffer sizes, shared buffer access overhead and delay, number of nodes, database access pattern, update probabilities, etc.). The updates should always be propagated to the shared buffer to alleviate the invalidation problem. For a smaller number of nodes, the effect of dependence between the contents of the private and the shared buffers influences policy selection. Optimal configuration. The model can be used to optimally allocate the buffer between the private and the shared buffers in various system architectures depending on the overhead and delay in accessing the shared buffer. For a larger number of nodes and under skewed database access, the shared buffer can improve the transaction response time significantly