On Parallel Join Processing in Object-Relational Database Systems

So far only few performance studies on parallel object-relational database systems are available. In particular, the relative performance of relational vs. reference-based join processing in a parallel environment has not been investigated sufficiently. We present a performance study based on the BUCKY benchmark to compare parallel join processing using reference attributes with relational hash- and merge-join algorithms. In addition, we propose a data allocation scheme especially suited for object hierarchies and set-valued attributes

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

Query Processing in a Parallel Object-Relational Database System

Object-relational database systems are now being deployed for real use by customers. Researchers and industry users have begun to explore the performance issues that these systems raise. In this paper, we examine some of those performance issues, and evaluate them for object-relational systems in general and for INFORMIX-Universal Server in particular. We describe objectrelational query processing techniques and make some predictions about how they will evolve over the next several years. 1 Introduction Since the middle 1970s, with the advent of the relational model and the appearance of working systems with which to experiment, academic and industry researchers have spent considerable time and energy inventing ways to make queries in relational databases run faster. Most relational database systems were sold to businesses, so most researchers concentrated on speeding up business query processing. The creation and use of indices, access path selection, cache structure and management, ..

M.: Query Processing in a Parallel Object-Relational Database System, Data Engineering Bulletin

Object-relational database systems are now being deployed for real use by customers. Researchers and industry users have begun to explore the performance issues that these systems raise. In this paper, we examine some of those performance issues, and evaluate them for object-relational systems in general and for INFORMIX-Universal Server in particular. We describe objectrelational query processing techniques and make some predictions about how they will evolve over the next several years.