Johanna Wenny Rahayu

New SQL standard for object-relational database applications

We examine the impact of the newest generation of structured query language (SQL), which is the standard language for relational model. The new standard of SQL4 adds powerful object-oriented data structures to object-relational database (ORDB), which is designed and implemented on relational model, to be used in diverse applications. We offer some opportunities of ORDB usage in many emerging database technologies such as statistical and scientific database, Web database, multimedia database, etc. We aim to show how standardizations impact on the model that can be useful for many real world applications.

Performance evaluation of the object-relational transformation methodology

Abstract The emergence of the object-oriented (OO) methodology has shown its capabilities in modelling the real world better than the earlier relational methodology. However, object-oriented databases (OODBs) are still considered immature in comparison with relational databases (RDBs) which have existed for many years. RDBs still continue to dominate the implementation of databases constituting more than 90% of all database implementations [28] . It was felt worthwhile to exploit the great modelling power of OO methodology, while still facilitating relational implementations. These reasons have led us to develop an object-relational transformation methodology [20] , [21] , [22] , [23] , [24] , [25] which allows us to use the OO methodology for data modelling and to transform it into a relational logical model for implementation in relational database management systems (RDBMSs). The main purpose of this paper is to present a performance evaluation of the transformation methodology. The evaluation covers I/O cost models of different types of queries. The type of evaluation is basically comparison-based, in which the performance of SQL operations upon a set of tables derived from the relational data model is compared with the tables derived from the OO data model using the transformation methodology. The results of the evaluation show that the performance of the RDB implementation transferred from an OO conceptual model using our object-relational transformation methodology is better than the relational implementation using a conventional relational modelling. Moreover, in many cases, the relational modelling is not applicable since it cannot capture the design semantics particularly relating to collection types. Our object-relational methodology solves this problem.

A methodology for transforming inheritance relationships in an object-oriented conceptual model to relational tables

Abstract With the increasing popularity of Object-Relational technology, it becomes necessary to have a methodology that allows database designers to exploit the great modeling power of object-oriented conceptual model, and still facilitate implementation on relational database systems. This paper presents a transformation methodology from inheritance relationships to relational tables. This includes transformation of different types of inheritance, such as union inheritance, mutual exclusion inheritance, partition inheritance and multiple inheritance. Performance comparison between the proposed transformation methodology and existing methods is also carried out. From the evaluation, we conclude that the proposed transformation methodology is more efficient than the others.

Sorting in parallel database systems

Sorting in database processing is frequently required through the use of Order By and Distinct clauses in SQL. Sorting is also widely known in the computer science community at large. Sorting in general covers internal and external sorting. Past published work has extensively focused on external sorting on uni-processors (serial external sorting), and internal sorting on multiprocessors (parallel internal sorting). External sorting on multiprocessors (parallel external sorting) has received surprisingly little attention; furthermore, the way current parallel database systems do sorting is far from optimal in many scenarios. The authors present a taxonomy for parallel sorting in parallel database systems, which covers five sorting methods: namely parallel merge-all sort, parallel binary-merge sort, parallel redistribution binary-merge sort, parallel redistribution merge-all sort, and parallel partitioned sort. The first two methods are previously proposed approaches to parallel external sorting which have been adopted as status quo of parallel database sorting, whereas the latter three methods which are based on redistribution and repartitioning are new, in that the have not been discussed in the literature of parallel external sorting.

Parallel selection query processing involving index in parallel database systems

Index is an important element in databases, and the existence of index is unavoidable. When an index has been built on a particular attribute, database operations (e.g. selection, join) on this attribute will become more efficient by utilizing the index. We focus on parallel algorithms for selection queries involving index that is data searching on indexed attributes. We propose two categories of parallel selection queries using index: parallel exact match and range selections; depending on the type of selection conditions. As parallel algorithms for these selection queries are very much influenced by indexing schemes, we also describe various index partitioning methods for parallel databases, and discuss their efficiency in supporting parallel selection query processing.

n-Dependency: dependency diversity in anatomised microdata tables

k-Anonymity and l-Diversity have laid the fundamental techniques for preserving privacy in microdata, and many research works have been inspired by them, proposing better and stronger levels of privacy. A common technique for achieving higher privacy in microdata tables is to diversify the records in such a way that sensitive information stored in the data is less likely to be disclosed. While most of the approaches succeed in protecting the original sensitive information to a high degree, issues arise when sensitive values are generalised along a hierarchical taxonomy, causing an increase in probability of privacy disclosure already after the first level of generalisation. This paper introduces n-Dependency, a novel technique that considers the hierarchical nature of sensitive information and their generalisations when diversifying the microdata. We propose a formal model and algorithms, and verify our technique by conducting extensive experiments.

XML-Enabled Relational Database for XML Document Update

With increasing demands for a proper and efficient XML data storage, XML-enabled database (XEnDB) has emerged as one of the popular answers. It claims to combine the strengths and limit the shortcomings of the traditional database management systems and native XML database. The implication is more research need to be done for this database family. This paper focuses on the XML update management in XEnDB. Our aim is to preserve the conceptual semantic constraints in XML data during update operations. The constraints are classified and represented in SQL/XML schema. Then, we propose the update methodology that utilizes the proposed schema and implement the method in one of the current XEnDB products