Distributed Computing Big Data (35 results)

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paperback. Condition: New. Paperback. Pub Date: 2023-07 Pages: 216 Language: Chinese Publisher: Chemical Industry Press This book explains big data analysis from a technical perspective in a simple and easy-to-understand form through a large number of drawings and detailed explanations. This is a textbook that gradually advances from system structure construction to actual development. The knowledge points in the book include distributed processing and machine learning required for big data analysis. as well as distrib.

paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2024-07 Pages: 448 Publisher: China Machine Press This book has been revised from the first edition. keeping up with new technologies in the fields of distributed computing. cloud computing and big data. and explaining the relevant technical principles and application methods based on application needs. The main contents include: the basic principles and programming development technologies of distributed computing. the principles and key technologies of .

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Hardcover. Condition: Very Good. 1. Auflage. Unread, some shelfwear. Immediately dispatched from Germany.

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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

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Taschenbuch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.

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Paperback. Condition: Brand New. reprint edition. 162 pages. 9.25x6.10x0.39 inches. In Stock.

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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Buch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.

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Softcover. Condition: New. Dust Jacket Condition: no dj. First. Distributed Systems for Cloud Computing and Big Data presents a comprehensive examination of the complex challenges and opportunities presented by distributed systems in cloud computing and big data environments. By scrutinizing the intricate interplay between data distribution, concurrency control, and scalability, this book offers a nuanced understanding of the delicate balance required to sustain high-performance data processing. From the nuances of distributed query optimization to the importance of fault-tolerant design, this book provides a thorough exploration of the multifaceted challenges faced by cloud computing and big data professionals. By adopting a distributed system architecture, organizations can optimize their data processing capabilities, ensuring real-time insights and decision-making in high-stakes environments. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condition: New. Dust Jacket Condition: no dj. First. Distributed Systems for Cloud Computing and Big Data Analytics for Environmental Sustainability is a cutting-edge guide that explores the potential of distributed systems in the context of cloud computing and big data analytics for environmental sustainability. By examining the complex relationships between data transmission, system performance, and environmental impact, this book offers a comprehensive understanding of how to design and optimize distributed systems for maximum efficiency, scalability, and sustainability. Through a series of theoretical frameworks and practical case studies, the book demonstrates how distributed systems can be applied to cloud computing and big data analytics, resulting in reduced energy consumption, improved resource efficiency, and enhanced overall sustainability. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condition: New. Dust Jacket Condition: no dj. First. Distributed systems and cloud computing are rapidly evolving fields that require a deep understanding of programming languages, data analysis techniques, and big data analytics. Java for Distributed Systems and Cloud Computing and Big Data provides readers with a comprehensive introduction to the key concepts and techniques necessary to develop distributed systems and cloud computing applications using Java. By examining real-world case studies and drawing on the latest research in distributed systems and cloud computing, this book explores the role of Java in distributed systems and cloud computing, including the use of Java libraries and frameworks, the integration of data analysis techniques, and the development of big data analytics applications. Readers will learn how to design and develop efficient and scalable distributed systems and cloud computing applications using Java. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2022-08-01 Pages: 232 Publisher: China Water Conservancy and Hydropower Press Distributed Intelligent Algorithm and Its Application in Big Data mainly includes an overview of intelligent algorithm technology and big data; distributed hybrid rice based on Hadoop Algorithm; Random singular value decomposition algorithm based on Hadoop; Distributed water wave optimization algorithm based on Hadoop; Distributed association rule mining algorithm based on Spark.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 172 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 mech.

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