Franky Lam

Querying and maintaining a compact XML storage

As XML database sizes grow, the amount of space used for storing the data and auxiliary data structures becomes a major factor in query and update performance. This paper presents a new storage scheme for XML data that supports all navigational operations in near constant time. In addition to supporting efficient queries, the space requirement of the proposed scheme is within a constant factor of the information theoretic minimum, while insertions and deletions can be performed in near constant time as well. As a result, the proposed structure features a small memory footprint that increases cache locality, whilst still supporting standard APIs, such as DOM, and necessary database operations, such as queries and updates, efficiently. Analysis and experiments show that the proposed structure is space and time efficient.

Efficient synchronization for mobile XML data

Many handheld applications receive data from a primary database server and operate in an intermittently connected environment these days. They maintain data consistency with data sources through sychronization. In certain applications such as sales force automation, it is highly desirable if updates on the data source can be reflected at the handheld applications immediately. This paper proposes an efficient method to synchronize XML data on multiple mobile devices. Each device retrieves and caches a local copy of data from the database source based on a regular path expression. These local copies may be overlapping or disjoint with each other. An efficient mechanism is proposed to find all the disjoint copies to avoid unnecessary synchronizations. Each update to the data source will then be checked to identify all handheld applications which are affected by the update. Communication costs can be further reduced by eliminating the forwarding of unnecessary operations to groups of mobile clients.

Modelling and manipulating multidimensional data in semistructured databases

Multidimensional information is pervasive in many computer applications including time series, spatial information, data warehousing, and visual data. While semistructured data or XML is becoming more and more popular for information integration and exchange, not much research work has been done in the design and implementation of semistructured database system to manage multidimensional information efficiently. In this paper, dimension operators have been defined based on a multidimensional logic which we call ML(ω). It can be used in applications such as multidimensional spreadsheets and multidimensional databases usually found in decision suport systems and data warehouses. Finally, a multidimensional XML database system has been prototyped and described in detail. Technologies such as XSL are used to transform or visualise data from different dimensions.

Algebraic Transformation and Optimization for XQuery

XQuery has been recently proposed by W3C as a standardized query language for XML. Because of its complexity, optimizing XQuery is difficult and requires more complicated optimization schemes than those for traditional query languages. This paper first proposes an XML data model and query algebra to provide a semantics and a means of optimization for the XQuery language. Following the language algebra, algebraic transformation (with optimization rules) is presented. Finally, physical algebraic operators are also defined to specify queries in this algebra into physical query plans.

Efficient ordering for XML data

With the increasing popularity of XML, there arises the need for managing and querying information in this form. Several query languages, such as XQuery, have been proposed which return their results in document order. However, most recent efforts focused on query optimization have disregarded order. This paper presents a simple yet elegant method to maintain document ordering for XML data. Analysis of our method shows that it is indeed efficient and scalable, even for changing data.

An XML repository for molecular sequence data

The emergence of the Extensible Markup Language (XML) as a new standard for data representation and exchange on the World Wide Web has created a new information revolution. Several proposals have been made to formulate molecular sequences in XML, however none of them mentioned the efficient storage and management of the resultant XML sequence data. This paper addresses some implementation issues of an XML repository for molecular sequence data.

Skipping Strategies for Efficient Structural Joins

The structural join is considered a core operation in processing and optimizing XML queries. Recently, various techniques have been proposed for efficiently finding structural relationships between sets of nodes. This paper presents an adaptive algorithm for efficiently processing structural joins. In contrast to previous work, which usually relies on external index structures such as B-trees, our proposal paper does not require any such data structures. Hence, our strategy has lower overheads than previous techniques, and can be easily implemented and incorporated into any existing system. Experiments show that our method significantly outperforms previous algorithms.

Performance evaluation of XSync: an efficient synchronizer for mobile XML data

Many handheld applications maintain data consistency with data sources through synchronization. In certain applications such as sales force automation, it is highly desirable if updates on the data source can be reflected at the handheld applications immediately. This paper proposes an efficient method to synchronize XML data on multiple mobile devices by identifying all the disjoint copies of updated data to avoid unnecessary synchronizations. Each update to the data source will then be checked to identify all handheld applications which are affected by the update. Communication costs can be further reduced by eliminating the forwarding of unnecessary operations to groups of mobile clients. Finally, this paper focuses on the performance aspects of the proposed approach.

Effective clustering schemes for XML databases

Although clustering problems are in general NP-hard, much research effort on this problem has been invested in the areas of object-oriented databases (OODB) and relational databases systems (RDBMS). With the increasing popularity of XML, researchers have been focusing on various XML data management including query processing and optimization. However, the clustering issues for XML data storage have been disregarded in their work. This paper provides a preliminary study on data clustering for optimizing XML databases. Different clustering schemes are compared through a set of extensive experiments.

An efficient path index for querying semi-structured data

The richness of semi-structured data allows data of varied and inconsistent structures to be stored in a single database. Such data can be represented as a graph, and queries can be constructed using path expressions, which describe traversals through the graph. Instead of providing optimal performance for a limited range of path expressions, we propose a mechanism which is shown to have consistent and high performance for path expressions of any complexity, including those with descendant operators (path wildcards). We further detail mechanisms which employ our index to perform more complex processing, such as evaluating both path expressions containing links and entire (sub) queries containing path based predicates. Performance is shown to be independent of the number of terms in the path expression(s), even where these expressions contain wildcards. Experiments show that our index is faster than conventional methods by up to two orders of magnitude for certain query types, is compact, and scales well.