Stream Data Management
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Stream Data Management
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Author : Nauman Chaudhry
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-04-14
Stream Data Management written by Nauman Chaudhry and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-14 with Computers categories.
Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.
Data Stream Management
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Author : Minos Garofalakis
language : en
Publisher: Springer
Release Date : 2016-07-11
Data Stream Management written by Minos Garofalakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-11 with Computers categories.
This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.
Data Stream Management
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Author : Lukasz Golab
language : en
Publisher: Springer
Release Date : 2010-06-02
Data Stream Management written by Lukasz Golab and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-02 with Computers categories.
Many applications process high volumes of streaming data, among them Internet traffic analysis, financial tickers, and transaction log mining. In general, a data stream is an unbounded data set that is produced incrementally over time, rather than being available in full before its processing begins. In this lecture, we give an overview of recent research in stream processing, ranging from answering simple queries on high-speed streams to loading real-time data feeds into a streaming warehouse for off-line analysis. We will discuss two types of systems for end-to-end stream processing: Data Stream Management Systems (DSMSs) and Streaming Data Warehouses (SDWs). A traditional database management system typically processes a stream of ad-hoc queries over relatively static data. In contrast, a DSMS evaluates static (long-running) queries on streaming data, making a single pass over the data and using limited working memory. In the first part of this lecture, we will discuss research problems in DSMSs, such as continuous query languages, non-blocking query operators that continually react to new data, and continuous query optimization. The second part covers SDWs, which combine the real-time response of a DSMS by loading new data as soon as they arrive with a data warehouse's ability to manage Terabytes of historical data on secondary storage. Table of Contents: Introduction / Data Stream Management Systems / Streaming Data Warehouses / Conclusions
Real Time Stream Data Management
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Author : Wolfram Wingerath
language : en
Publisher: Springer
Release Date : 2019-01-02
Real Time Stream Data Management written by Wolfram Wingerath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-02 with Computers categories.
While traditional databases excel at complex queries over historical data, they are inherently pull-based and therefore ill-equipped to push new information to clients. Systems for data stream management and processing, on the other hand, are natively pushoriented and thus facilitate reactive behavior. However, they do not retain data indefinitely and are therefore not able to answer historical queries. The book provides an overview over the different (push-based) mechanisms for data retrieval in each system class and the semantic differences between them. It also provides a comprehensive overview over the current state of the art in real-time databases. It sfirst includes an in-depth system survey of today's real-time databases: Firebase, Meteor, RethinkDB, Parse, Baqend, and others. Second, the high-level classification scheme illustrated above provides a gentle introduction into the system space of data management: Abstracting from the extreme system diversity in this field, it helps readers build a mental model of the available options.
Stream Data Processing A Quality Of Service Perspective
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Author : Sharma Chakravarthy
language : en
Publisher: Springer
Release Date : 2009-05-08
Stream Data Processing A Quality Of Service Perspective written by Sharma Chakravarthy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-08 with Computers categories.
The systems used to process data streams and provide for the needs of stream-based applications are Data Stream Management Systems (DSMSs). This book presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. Ii includes important aspects of a QoS-driven DSMS (Data Stream Management System) and introduces applications where a DSMS can be used and discusses needs beyond the stream processing model. It also discusses in detail the design and implementation of MavStream. This volume is primarily intended as a reference book for researchers and advanced-level students in computer science. It is also appropriate for practitioners in industry who are interested in developing applications.
Streaming Intelligence Mastering Stream Processing For Real Time Data Analysis
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Author : Dr.K.Sundravadivelu
language : en
Publisher: SK Research Group of Companies
Release Date : 2024-08-10
Streaming Intelligence Mastering Stream Processing For Real Time Data Analysis written by Dr.K.Sundravadivelu and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-10 with Computers categories.
Dr.K.Sundravadivelu, Assistant Professor, Department of Computer Science, School of Information Technology, Madurai Kamaraj University, Madurai, Tamil Nadu, India. Mrs.P.Renuka, Assistant Professor, Department of Computer Applications, Dhanalakshmi Srinivasan College of Arts and Science for Women (Autonomous), Perambalur, Tamil Nadu, India. Mrs.V.Suganthi, Assistant Professor, Department of Computer Science, C.T.T.E College for Women, Affiliated to University of Madras, Chennai, Tamil Nadu, India. Mrs.S.Durgadevi, Assistant Professor, Department of Computer Applications, Dhanalakshmi Srinivasan College of Arts and Science for Women (Autonomous), Perambalur, Tamil Nadu, India. Mr.B.Murali Krishna, Assistant Professor, Department of Computer Science and Engineering, Vignan's LARA Institute of Technology and Science, Vadlamudi, Andhra Pradesh, India.
Data Management And Computation
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Author : National Research Council (U.S.). Space Science Board
language : en
Publisher: National Academies
Release Date : 1982
Data Management And Computation written by National Research Council (U.S.). Space Science Board and has been published by National Academies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Astronautics categories.
Big Data Management And Processing
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Author : Kuan-Ching Li
language : en
Publisher: CRC Press
Release Date : 2017-05-19
Big Data Management And Processing written by Kuan-Ching Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-19 with Business & Economics categories.
From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions. The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.
Vldb 2006
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Author :
language : en
Publisher:
Release Date : 2006
Vldb 2006 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Data structures (Computer science) categories.
Database Management And Analysis Of Fisheries In Illinois Lakes F 69 R 10
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Author :
language : en
Publisher:
Release Date : 1997
Database Management And Analysis Of Fisheries In Illinois Lakes F 69 R 10 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Fishery management categories.