Download or read book An Introduction to Distributed Data Processing written by Harry Katzan and published by . This book was released on 1979 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two functions that are fundamental to organized society are communication and dispersion. Communication provides a means for information to be accumulated, and dispersion permits effective and efficient use of resources. Communication and dispersion also provide the basis for a major technological advance in the computer field known as Distributed Data Processing. The move to distributed data processing offers five general benefits: reliability, responsiveness, incremental growth, correspondence to organizational patterns, and resource sharing. The objective of this book is to summarize the key concepts of distributed data processing from an introductory point of view.
Download or read book Design and Strategy for Distributed Data Processing written by James Martin and published by Prentice Hall. This book was released on 1981 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revolutionary change in data processing; The impact of distributed processing on organization; Forms of distributed processing; Strategy; Design of distributed data; Software and network strategy; Security and auditability.
Download or read book Principles of Distributed Database Systems written by M. Tamer Özsu and published by Springer Science & Business Media. This book was released on 2011-02-24 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Distributed Data Processing written by Michael P. Mariani and published by North Holland. This book was released on 1984 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Management of Distributed Data Processing written by Jacob Akoka and published by North-Holland. This book was released on 1982 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Design and Management of Distributed Data Processing written by Muhammad Idrees and published by Blackwell Publishers. This book was released on 1990 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Distributed Database Management Systems written by Saeed K. Rahimi and published by John Wiley & Sons. This book was released on 2015-02-13 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses issues related to managing data across a distributed database system. It is unique because it covers traditional database theory and current research, explaining the difficulties in providing a unified user interface and global data dictionary. The book gives implementers guidance on hiding discrepancies across systems and creating the illusion of a single repository for users. It also includes three sample frameworks—implemented using J2SE with JMS, J2EE, and Microsoft .Net—that readers can use to learn how to implement a distributed database management system. IT and development groups and computer sciences/software engineering graduates will find this guide invaluable.
Download or read book What is a distributed Data Processing System written by Philip Harrison Enslow and published by . This book was released on 1978 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Processing Vocabulary written by and published by . This book was released on 1991 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Distribution written by Richard Wiliiams and published by Routledge. This book was released on 2018-12-17 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Published in 1992. Business information has evolved from typewriter/card index (decentralized) through the era of DP Department and mainframe (centralized) to present mix with PCs and networks (distributed). This book demonstrates how data distribution can function in the best interests of organizations, through a managed environment. It looks at what is needed from the systems professionals to support current methods; reporting actual experience, defining techniques, and examining the opportunities and challenges.
Download or read book Pathways Through Data Processing written by and published by . This book was released on 1980 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Distributed Data Processing for BMD written by Michael J. Flynn and published by . This book was released on 1979 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past year, the emphasis of this group in support of Distributed Data Processing for BMD was on the development of tools for more accurately predicting the performance of distributed data processing systems and investigation alternatives for novel DDP architectures. Specifically three study areas were covered: (1) Directly Executed Languages and 'Ideal' BMD Architecture Development; (2) Parallel Nodal Architectures; and (3) Communication Networks.
Download or read book Distributed Processing Systems written by Robert J. Thierauf and published by Prentice Hall. This book was released on 1978 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prior developments to distributed processing systems; Systems prior to distributed processing; Current developments in distributed processing systems; Essentials of distributed processing systems; Feasibility study of distributed processing systems; Implementation and applications of distributed processing systems (First and second levels); Networks and applications of distributed processing systems (Third level); Case study of current distributed processing systems; Selected distributed processing subsystems-american products corporation; Distributed processing marketing subsystem-american products corporation; Distributed processing manufacturing subsystem-american products corporation; Distributed processing physical distribution subsystem-american products corporation; Distributed processing accounting subsystem-american products corporation; Future developments in distributed processing systems; Developments for future distributed processing systems; Future distributed processing systems.
Download or read book Practical Real time Data Processing and Analytics written by Shilpi Saxena and published by Packt Publishing Ltd. This book was released on 2017-09-28 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.
Download or read book Data Processing written by Susan Wooldridge and published by Elsevier. This book was released on 2013-10-22 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Processing: Made Simple, Second Edition presents discussions of a number of trends and developments in the world of commercial data processing. The book covers the rapid growth of micro- and mini-computers for both home and office use; word processing and the 'automated office'; the advent of distributed data processing; and the continued growth of database-oriented systems. The text also discusses modern digital computers; fundamental computer concepts; information and data processing requirements of commercial organizations; and the historical perspective of the computer industry. The computer hardware and software and the development and implementation of a computer system are considered. The book tackles careers in data processing; the tasks carried out by the data processing department; and the way in which the data processing department fits in with the rest of the organization. The text concludes by examining some of the problems of running a data processing department, and by suggesting some possible solutions. Computer science students will find the book invaluable.
Download or read book Database Internals written by Alex Petrov and published by O'Reilly Media. This book was released on 2019-09-13 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency
Download or read book Distributed Computing in Big Data Analytics written by Sourav Mazumder and published by Springer. This book was released on 2017-08-29 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use. This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.
