A differential refresh scheme for remote end-user\u27s views

The growth of end-user computing and recent developments in information technology, such as client/server architecture and data warehouse, promote the use of remote materialized views (RMVs) to support end-users. This article presents a differential scheme to refresh remote end-user\u27s views. The scheme stores the effects of updates relevant to the RMV in a difference table which is transmitted to the remote site upon receiving the refresh request to update the RMV. The scheme provides a fast response to a user\u27s refresh request. We discuss the data structures and algorithms of the scheme. Performance measures are developed and compared with the regeneration scheme

Adaptive Cost Estimation for Client-Server based Heterogeneous Database Systems

In this paper, we propose a new method for estimating query cost in client-server based heterogeneous database management system. The cost estimation parameters are adjusted by an Adaptive Cost Estimation (ACE) module which uses query execution feedback yielding more and more accurate cost estimates. The most important features of ACE are its detailed cost model which accounts for all costs incurred, its rapid convergence to the actual parameter values, and its low overhead which permits continuous adaptation during the run time of the system. ACE has been implemented and tested with Oracle 6, Oracle 7, Ingres, and ADMS. Extensive experiments performed on these systems show that the ACE's time estimates are within 20% of the real wall-clock time for more than 92% of the queries. This percentage surpasses 98% for queries over 20 seconds. (Also cross-referenced as UMIACS-TR-96-37

The Implementation and Performance Evaluation of the ADMS Query Optimizer: Integrating Query Result Caching and Matching

In this paper, we describe the design and evaluation of the ADMS optimizer. Capitalizing on a structure called Logical Access Path Schema to model the derivation relationship among cached query results, the optimizer is able to perform query matching coincidently with the optimization and generate more efficient query plans using cached results. The optimizer also features data caching and pointer caching, different cache replacement strategies, and different cache update strategies. An extensive set of experiments were conducted, and the results showed that pointer caching and dynamic cache update strategies substantially speedup query computations and, thus, increase query throughput under situations with fair query correlation and update load. The requirement of the cache space is relatively small and the extra computation overhead introduced by the caching and matching mechanism is more than offset by the time saved in query processing. (Also cross-referenced as UMIACS-TR-93-106

Adaptive Database Systems Based On Query Feedback and Cached Results

This dissertation explores the query optimization technique of using cached results and feedback for improving performance of database systems. Cached results and experience obtained by running queries are used to save execution time for follow–up queries, adapt data and system parameters, and improve overall system performance. First, we develop a framework which integrates query optimization and cache management. The optimizer is capable of generating efficient query plans using previous query results cached on the disk. Alternative methods to access and update the caches are considered by the optimizer based on cost estimation. Different cache management strategies are also included in this framework for comparison. Empirical performance study verifies the advantage and practicality of this framework. To help the optimizer in selecting the best plan, we propose a novel approach for providing accurate but cost-effective selectivity estimation. Distribution of attribute values is regressed in real time, using actual query result sizes obtained as feedback, to make accurate selectivity estimation. This method avoids the expensive off-line database access overhead required by the conventional methods and adapts fairly well to updates and query locality. This is verified empirically. To execute a query plan more efficiently, a buffer pool is usually provided for caching data pages in memory to reduce disk accesses. We enhance buffer utilization by devising a buffer allocation scheme for recurring queries using page fault feedback obtained from previous executions. Performance improvement of this scheme is shown by empirical examples and a systematic simulation

Maintenance of Spatial Queries on Continuously Moving Points

Cars, aircraft, mobile cell phones, ships, tanks, and mobile robots all have the common property that they are moving objects. A kinematic representation can be used to describe the location of these objects as a function of time. For example, a moving point can be represented by the linear function p(t) = x_0 + (t - t_0)v, where x_0 is the start location, t_0 is the start time, and v is its velocity vector. Instead of storing the location of the object at a given time in a database, the coefficients of the function are stored. When an object's behavior changes enough that the function describing its location is no longer accurate, the function coefficients for the object are updated.Because the objects are represented as a function of time, spatial query results can change even when no transactions update the database. Our hypothesis is that algorithms for the maintenance of spatial queries on kinematic point data types can be developed to support updates to base relations as time advances that are more efficient than straight forward adaptations of previous work. We present algorithms to maintain k-nearest neighbor, spatial join, and spatial semijoin queries in this domain. We compare by experimentation these new algorithms to more straight forward adaptations of previous work to support updates. Experiments are conducted using synthetic uniformly distributed data, and real aircraft flight data. The primary metric of comparison is the number of I/O disk accesses needed to maintain the query results and supporting data structures. A system to query and visualize results on moving object data, in a client-server environment, is also presented. The work presented here is built upon a culmination of our previously published work, including work on continuously moving point queries [35, 36], and client-server systems [31, 33, 34]