This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced a renewal of interest in distributed and parallel data management, while, at the same time, requiring a rethinking of some of the traditional techniques. This book covers the breadth and depth of this re-emerging field. The coverage consists of two parts. The first part discusses the fundamental principles of distributed data management and includes distribution design, data integration, distributed query processing and optimization, distributed transaction management, and replication. The second part focuses on more advanced topics and includes discussion of parallel database systems, distributed object management, peer-to-peer data management, web data management, data stream systems, and cloud computing. New in this Edition: New chapters, covering database replication, database integration, multidatabase query processing, peer-to-peer data management, and web data management. Coverage of emerging topics such as data streams and cloud computing Extensive revisions and updates based on years of class testing and feedback Ancillary teaching materials are available.

Principles of Distributed Database Systems

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

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Query evaluation techniques for large databases

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation that may be efficiently processed to determine correspondence. Applications of the interface and system include a video cassette recorder (VCR), medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

Adaptive pattern recognition based control system and method

Enterprise management information in a first format (500) for use by a first computerized system is transformed into an intermediate format (514) to readily make the stored enterprise management information available for use in a second computerized system that utilizes a second format (520). The transformation includes a plurality of common data type elements (502, 504, 506, 508, 510, 512) that are adapted to be shared across a plurality of data objects in the intermediate format.

Common common object

Stored product management information in a first format for use by a first computerized system is transformed to readily make the stored product management information available for use in a second computerized system that utilizes a second format in a cost-efficient and time-efficient manner.

Product common object

Research Direction in Query Optimization at the University of Maryland.

Site autonomy issues in R*: a distributed database management system

Rising costs, decreasing quality of care, diminishing productivity, and increasing complexity have all contributed to the present state of the healthcare industry. The interactions between payers (e.g., insurance companies and health plans) and providers (e.g., hospitals and laboratories) are growing and are becoming more complicated. The constant upsurge in and enhanced complexity of diagnostic and treatment information has made the clinical decision-making process more difficult. Medical transaction charges are greater than ever. Population-specific financial requirements are increasing the economic burden on the entire system. Medical insurance and identity theft frauds are on the rise. The current lack of comparative cost analytics hampers systematic efficiency. Redundant and unnecessary interventions add to medical expenditures that add no value. Contemporary payment models are antithetic to outcome-driven medicine. The rate of medical errors and mistakes is high. Slow inefficient processes and the lack of best practice support for care delivery do not create productive settings. Information technology has an important role to play in approaching these problems. This paper describes IBM Research's approach to helping address these issues, i.e., the evidence-based healthcare platform.

http://gotzfamily.org/david/pubs/bigus_ibm_jrd_2011.pdf

Information technology for healthcare transformation

The design and implementation of R*, an experimental prototype of a distributed system for the management of interrelated, voluntarily cooperating, but also autonomous databases is based on several major objectives: site autonomy, transparency, ease of use and performance. This paper discusses the way data definition and control statements are executed in a distributed environment and shows how the general objectives are fulfilled. Specialized distributed execution facilities have been developed to facilitate the implementation of complex multi-site functions. This paper describes the facilities and methodology used to implement the distributed processing needed to perform multi-site data definition operations in R*.

"I wish I were over there": distributed execution protocols for data definition in R

Location of grocery stores, available modes of transportation, economic and social demographics, urban planning, medicine, agriculture, advertising and marketing practices, and regulations are diverse components of a complex system that affect health. Decision makers need to predict the health effects of changes in these factors. Typically, experts in different organizations drawing on knowledge and techniques from different disciplines create independent models for understanding various components of such complex systems. It is a significant challenge to pull these sorts of models together into an integrated picture. This paper describes our progress toward designing the Smarter Planet Platform for Analysis and Simulation of Health (Splash), a platform for composing multiple heterogeneous models, simulations, and datasets. This platform comprises mechanisms for cataloging, describing, connecting, and executing a set of models together. We focused initially on a five-model composition related to obesity. This paper describes some challenges we encountered and some lessons we learned.

/pdf/splash-a-progress-report-on-building-a-platform-for-a-360-mncz9rbsnu.pdf

Patricia G. Selinger

Papers

Research Direction in Query Optimization at the University of Maryland.

Site autonomy issues in R*: a distributed database management system

Information technology for healthcare transformation

"I wish I were over there": distributed execution protocols for data definition in R

Splash: a progress report on building a platform for a 360 degree view of health