The authors investigate a direct storage scheme for complex objects called FIHSM (Fully Inverted Hierarchical Storage Model) and propose a novel parallel-query-processing strategy (QPS) for it. The QPS has four phases (select, pivot, value materialize and compose). With a declustered placement strategy, each of these phases provides for both inter and intra-operation parallelism. Furthermore, partial results of one phase could be pipelined to the subsequent phase. The proposed four-phase structured algorithm is based on heuristics and thus avoids the prohibitive exhaustive searches which are needed for optimizing query executions in parallel environments.>

Handling parallelism in database systems involves the specification of a storage model, a placement strategy, and a query processing strategy. An important goal is to determine the appropriate combination of these three strategies in order to obtain the best performance advantages. In this paper we present a novel and promising query processing strategy for a decomposed storage model. We discuss some of the qualitative advantages of the scheme. We also compare the performance of the proposed “pivot” strategy with conventional query processing for the n-ary storage model. The comparison is performed using the Wisconsin Benchmarks.

We investigate two schemes for placing data on multiple disks. We show that declustering (spreading each file across several disks) is inherently better than clustering (placing each file on a single disk) due to a number of reasons including parallelism and uniform load on all disks.

The availability of larger RAM spaces for DBMSs provides interesting opportunities for performance enhancements, especially in buffer management. In this paper we propose and compare two alternative strategies for the buffer management of permanent data (i.e., the data committed by transactions) called block buffering and attribute buffering. These strategies use statistics to capture the changing locality of a reference string. We model and demonstrate the impact of locality on the performance of buffering. We also analyze and compare the effect of both the attribute and predicate dimensions of locality on buffering, varying a number of parameters including the degree of locality, RAM size, and RAM utilization.

Identity is that property of an object which distinguishes each object from all others. Identity has been investigated almost independently in general-purpose programming languages and database languages. Its importance is growing as these two environments evolve and merge.

Article Free Access Share on A calculus for complex objects Authors: Francois Bancilhon View Profile , Setrag Khoshafian Microelectronics and Computer Technology Corporation Microelectronics and Computer Technology CorporationView Profile Authors Info & Claims PODS '86: Proceedings of the fifth ACM SIGACT-SIGMOD symposium on Principles of database systemsJune 1985 Pages 53–60https://doi.org/10.1145/6012.15404Online:01 June 1985Publication History 109citation355DownloadsMetricsTotal Citations109Total Downloads355Last 12 Months11Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

This report examines the relative advantages of a storage model based on decomposition (of community view relations into binary relations containing a surrogate and one attribute) over conventional n-ary storage models

Most research in statistical databases has concentrated on retrieval, sampling, and aggregation type statistical queries. Data management issues associated with computational statistical operations have been ignored. As a first step towards integrating database management support of statistical operations, we have analyzed the performance of X'X, the QR decomposition, and the Singular Value Factorization. Alternative implementation strategies with respect to the relational and transposed storage organizations are developed. Implementation strategies corresponding to vector building block, vector-matrix, and direct algorithms with explicit buffer management are compared in terms of efficiency in performance.