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Fundamentals of stream processing : application design, systems, and analytics / Henrique C.M. Andrade, JP Morgan, New York, Bugra Gedik, Bilkent University, Turkey, Deepak S. Turaga, IBM Thomas J. Watson Research Center, New York.
Author:
Andrade, Henrique C. M. author.
Imprint:Cambridge, United Kingdom ; New York : Cambridge University Press, [2014]
Descriptionxxvii, 529 pages : illlustrations ; 26 cm
Note:Part I Fundamentals: 1. What brought us here? Overview -- Toward continuous data processing: the requirements -- Stream processing foundations -- Stream processing -- tying it all together -- 2. Introduction to stream processing. Overview -- Stream Processing Applications -- Information flow processing technologies -- Stream Processing Systems -- Part II Application development: 3. Application development -- the basics. Overview -- Characteristics of SPAs -- Introduction to SPL -- Common stream processing operators -- 4. Application development -- data flow programming. Overview -- Flow composition -- Flow manipulation -- 5. Large-scale development -- modularity, extensibility, and distribution. Overview -- Modularity and extensibility -- Distributed programming -- 6. Visualization and debugging. Overview -- Visualization -- Debugging -- Part III System Architecture: 7. Architecture of a stream processing system. Overview -- Architectural building blocks -- Architectural overview -- 8. InfoSphere Streams architecture. Overview -- Background and history -- A user's perspective -- Components -- Services -- Part IV Application and design and analytics: 9. Design principles and patterns for stream processing applications. Overview -- Functional design patterns and principles -- Non-functional principles and design patterns -- 10. Stream analytics: data pre-processing and transformation. Overview -- The mining process -- Notation -- Descriptive statistics -- Sampling -- Sketches -- Quantization -- Dimensionality reduction -- Transforms -- 11. Stream analytics: modeling and evaluation. Overview -- Offline modeling and online evaluation -- Data stream classification -- Data stream clustering -- Data stream regression -- Data stream frequent pattern mining -- Anomaly detection -- Part V Case Studies: 12. Applications. Overview -- The Operations Monitoring application -- The Patient Monitoring application -- The Semiconductor Process Control application -- Part VI Closing notes: 13. Conclusion. Book summary -- Challenges and open problems -- Where do we go from here? -- References.
Bibliography Note:Includes bibliographical references and index.
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