Apostolos N. Papadopoulos

This book is a gentle introduction to dominance-based query processing techniques and their applications. The book aims to present fundamental as well as some advanced issues in the area in a precise, but easy-to-follow, manner. Dominance is an intuitive concept that can be used in many different ways in diverse application domains. The concept of dominance is based on the values of the attributes of each object. An object ???? dominates another object ???? if ???? is better than ????. This goodness criterion may differ from one user to another. However, all decisions boil down to the minimization or maximization of attribute values. In this book, we will explore algorithms and applications related to dominance-based query processing. The concept of dominance has a long history in finance and multi-criteria optimization. However, the introduction of the concept to the database community in 2001 inspired many researchers to contribute to the area. Therefore, many algorithmic techniqueshave been proposed for the efficient processing of dominance-based queries, such as skyline queries, ????-dominant queries, and top-???? dominating queries, just to name a few.

Space support in databases poses new challenges in every part of a database management system & the capability of spatial support in the physical layer is considered very important. This has led to the design of spatial access methods to enable the effective & efficient management of spatial objects. R-trees have a simplicity of structure & together with their resemblance to the B-tree, allow developers to incorporate them easily into existing database management systems for the support of spatial query processing. This book provides an extensive survey of the R-tree evolution, studying the applicability of the structure & its variations to efficient query processing, accurate proposed cost models, & implementation issues like concurrency control and parallelism. Written for database researchers, designers & programmers as well as graduate students, this comprehensive monograph will be a welcome addition to the field.

Modern applications are both data and computationally intensive and require the storage and manipulation of voluminous traditional (alphanumeric) and nontraditional data sets (images, text, geometric objects, time-series). Examples of such emerging application domains are: Geographical Information Systems (GIS), Multimedia Information Systems, CAD/CAM, Time-Series Analysis, Medical Information Sstems, On-Line Analytical Processing (OLAP), and Data Mining. These applications pose diverse requirements with respect to the information and the operations that need to be supported. From the database perspective, new techniques and tools therefore need to be developed towards increased processing efficiency. This monograph explores the way spatial database management systems aim at supporting queries that involve the space characteristics of the underlying data, and discusses query processing techniques for nearest neighbor queries. It provides both basic concepts and state-of-the-art results in spatial databases and parallel processing research, and studies numerous applications of nearest neighbor queries.

Space support in databases poses new challenges in every part of a database management system & the capability of spatial support in the physical layer is considered very important. This has led to the design of spatial access methods to enable the effective & efficient management of spatial objects. R-trees have a simplicity of structure & together with their resemblance to the B-tree, allow developers to incorporate them easily into existing database management systems for the support of spatial query processing. This book provides an extensive survey of the R-tree evolution, studying the applicability of the structure & its variations to efficient query processing, accurate proposed cost models, & implementation issues like concurrency control and parallelism. Written for database researchers, designers & programmers as well as graduate students, this comprehensive monograph will be a welcome addition to the field.

Modern applications are both data and computationally intensive and require the storage and manipulation of voluminous traditional (alphanumeric) and nontraditional data sets (images, text, geometric objects, time-series). Examples of such emerging application domains are: Geographical Information Systems (GIS), Multimedia Information Systems, CAD/CAM, Time-Series Analysis, Medical Information Sstems, On-Line Analytical Processing (OLAP), and Data Mining. These applications pose diverse requirements with respect to the information and the operations that need to be supported. From the database perspective, new techniques and tools therefore need to be developed towards increased processing efficiency. This monograph explores the way spatial database management systems aim at supporting queries that involve the space characteristics of the underlying data, and discusses query processing techniques for nearest neighbor queries. It provides both basic concepts and state-of-the-art results in spatial databases and parallel processing research, and studies numerous applications of nearest neighbor queries.