Databases Reference
In-Depth Information
1
Introduction
Traditional relational database systems are not adequate for storing, retrieving,
and processing the data found for non-traditional database applications. Such
data includes data for visualization, spatial data, and multimedia data, which is
often used in World Wide Web pages. A number of applications requiring such
structurally complex data are not only data-intensive but also cpu-intensive. Object
Database Management Systems (ODBMS) are efficient to handle such data due to
an abundance of data structures, rich functionality for data processing, and the
ability to integrate programming languages and databases.
In this chapter, we focus on issues involved in distributed and parallel processing
of object queries and parallel object programming languages. An implementation
of ODBMS based on ODMG3.0 standard is also introduced. This chapter consists
of four sections including this one.
In section 2, parallel processing of path expressions is discussed. Path expressions
are often used in ODB applications. Fast processing of path expressions are crucial
in fast retrieval of objects. Parallel execution of a path expression utilizing index
in an asynchronous parallel computing environment is addressed. This section is
written by Tatsuo Tsuji.
In section 3, a parallel object programming language is introduced. The
abovementioned non-traditional applications are data-intensive and cpu-intensive.
The object programming language is useful in integrating the database retrieval
and the data processing uniformly. Since such applications are cpu-intensive,
improvement of the performance of these applications can be expected by parallel
processing. Parallel processing using the proposed language is discussed, and
methods of performance evaluation are presented. This section is written by
Hirofumi Amano.
Finally, in section 4, an ODBMS based on the ODMG3.0 standard with
distributed and parallel processing ability is introduced. The system, named
ShusseUo, consists of three components: WAKASHI, for distributed data storage,
INADA, for ODMG2.0-compliant object handling, and WARASA, for distributed
and parallel OQL compiler. This section focuses on the system architecture and
functionality. In addiction, a performance evaluation using a large spatial database
is presented. This section is written by Kunihiko Kaneko.
2
Termination detection of parallel index retrieval for complex
objects
A fast retrieval method for handling complex objects and corresponding effective
implementation schemes are essential in order to keep up with the rapid growth of
database applications in which large and complicated objects are handled.
Employing parallelism is one promising approach for the fast retrieval of complex
objects
3)4)5)
. Another effective approach is providing fast indexing techniques for a
