Parallel Database Systems

Best practices for Esri's GeoAnalytics Desktop and Postgres/PostGIS

The SELECT statement, functions and more. Oracle Database 11g, 12c, 19c, 21c using Oracle SQL Developer. 1Z0-071 exam.

In the last few years a number of object-oriented database systems have appeared in the literature, most of which addresses specific areas such as office information systems (OIS), computer aided design (CAD), computer aided manufacturing (CAM), software engineering (SE), and artificial intelligence (AI). Unfortunately, hardly any one of them addresses the problem of concurrency control from the general-purpose database point of view.

For a long time the design of data processing systems has been mainly based on experience and practical considerations more than on formal quantitative approaches. This was true both in the design of computer architecture and in the design of software systems such as operating systems and database systems. Two relevant exceptions were the early studies in switching theory, concerned with such problems as minimization and reliability, on the one hand, and on the other hand, the general mathematical approach to computer system modeling and performance evaluation. More recently, the evaluation of distributed computing related to technological advances in microelectronics, has increased the need for quantitative studies for optimizing the design of computer systems.

With the unprecedented growth-rate at which data is being collected and stored electronically today in almost all fields of human endeavor, the efficient extraction of useful information from the data available is becoming an increasing scientific challenge and a massive economic need. This book presents thoroughly reviewed and revised full versions of papers presented at a workshop on the topic held during KDD'99 in San Diego, California, USA in August 1999 complemented by several invited chapters and a detailed introductory survey in order to provide complete coverage of the relevant issues. The contributions presented cover all major tasks in data mining including parallel and distributed mining frameworks, associations, sequences, clustering, and classification. All in all, the volume presents the state of the art in the young and dynamic field of parallel and distributed data mining methods. It will be a valuable source of reference for researchers and professionals.