Modelling parallel database management systems for performance prediction

Abstract unavailable please refer to PD

Data Processing in a Database Management System Using Parallel Processing

This research project will be focused on parallel processing as it is used with database management systems to process data. Specifically, the goal is to see if creating a database management system with parallel processing at the forefront of its data processing can offer enough of an efficiency increase to warrant using it against a sequential database management system and is it possible to make that system just as reliable as those databases without parallel processing. A parallel processed database will be created with a focus on monitoring its data reliability and consistency. It will then be compared to two sequential databases to compare their performance and determine the effectiveness of the parallel processed database. This project has resulted in both the creation of a sequential database and a parallel processed database. Numerous tests have been run on both, and while it may be very beneficial to allow for a database to have parallel capabilities, the efficiency and speed up that a parallel database may have over a sequential do not warrant the use and creation of it with the technologies used at this time

Some Considerations about Modern Database Machines

Optimizing the two computing resources of any computing system - time and space - has al-ways been one of the priority objectives of any database. A current and effective solution in this respect is the computer database. Optimizing computer applications by means of database machines has been a steady preoccupation of researchers since the late seventies. Several information technologies have revolutionized the present information framework. Out of these, those which have brought a major contribution to the optimization of the databases are: efficient handling of large volumes of data (Data Warehouse, Data Mining, OLAP – On Line Analytical Processing), the improvement of DBMS – Database Management Systems facilities through the integration of the new technologies, the dramatic increase in computing power and the efficient use of it (computer networks, massive parallel computing, Grid Computing and so on). All these information technologies, and others, have favored the resumption of the research on database machines and the obtaining in the last few years of some very good practical results, as far as the optimization of the computing resources is concerned.Database Optimization, Database Machines, Data Warehouse, OLAP – On Line Analytical Processing, OLTP – On Line Transaction Processing, Parallel Processing

UTILISING NETWORKED WORKSTATIONS TO ACCELERATE DATABASE QUERIES

The rapid growth in the size of databases and the advances made in Query Languages has resulted in increased SQL query complexity submitted by users, which in turn slows down the speed of information retrieval from the database. The future of high performance database systems lies in parallelism. Commercial vendors´ database systems have introduced solutions but these have proved to be extremely expensive. This paper investagetes how networked resources such as workstations can be utilised by using Parallel Virtual Machine (PVM) to Optimise Database Query Execution. An investigation and experiments of the scalability of the PVM are conducted. PVM is used to implement palallelism in two separate ways: (i) Removes the work load for deriving and maintaining rules from the data server for Semantic Query Optimisation, therefore clears the way for more widespread use of SQO in databases [16], [5]. (ii) Answers users queries by a proposed Parallel Query Algorithm PQA which works over a network of workstations, coupled with a sequential Database Management System DBMS called PostgreSql on the prototype called Expandable Server Architecture ESA [11], [12], [21], [13]. Experiments have been conducted to tackle the problems of Parallel and Distributed systems such as task scheduling, load balance and fault tolerance

Exploring parallelism with object oriented database management system

The object oriented approach to database management systems aims to remove the limitations of the current systems by providing enhanced semantic capabilities and more flexible facilities, including the encapsulation of operations as well as data in the specification of an object. Such systems are certainly more complex than existing database management systems. Although, they are complex, the current object oriented database management systems are built for Von-Neumann (purely sequential) machines. Such implementation inevitably leads to major problems involving efficiency and performance. So, new techniques for implementation need to be investigated. One possible solution for the efficiency, and performance problems is to use parallel processing techniques. Thus, the aim of this research is to propose aspects in which parallel processing can be introduced within the scope of object oriented database management systems and identify ways in which the performance can be improved. A prototype of the main components of an object oriented database system called KBZ has been implemented to test out some of the parallel processing aspects. The thesis starts with an introduction and background to the research. It then describes major parallel system architectures for an object oriented database management system. Techniques such as distributing a large volume of data among various processors (transputers), performing processing in the background of the system to reduce response time, and performing input/output parallel processing are presented. The initial prototype, PKBZ version-1, is then described; in particular, the logical and physical representation of object classes, how they communicate through message sending, and the different types of message supported. Two prototype versions exist. The initial prototype was designed to investigate the parallel implementation and general functionality of the system. The second version provides greater flexibility and incorporates enhanced functionality to allow experimentation. The enhancements in the second version are also discussed in the thesis, and the experimental results using different transputer configurations are illustrated and analyzed