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Streaming systems : the what, where, when, and how of large-scale data processing /
Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scienti...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media, Inc.,
[2018]
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Akidau, Tyler, |e author. | |
| 245 | 1 | 0 | |a Streaming systems : |b the what, where, when, and how of large-scale data processing / |c Tyler Akidau, Slava Chernyak, Reuven Lax. |
| 264 | 1 | |a Sebastopol, CA : |b O'Reilly Media, Inc., |c [2018] | |
| 264 | 4 | |c ©2018 | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Includes index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed July 23, 2018). | |
| 505 | 0 | |a The beam model. Streaming 101 -- The what, where, when, and how of data processing -- Watermarks -- Advanced windowing -- Exactly-once and side effects -- Streams and tables. The practicalities of persistent state -- Streaming SQL -- Streaming joins -- The evolution of large-scale data processing. | |
| 505 | 0 | |a Intro; Copyright; Table of Contents; Preface Or: What Are You Getting Yourself Into Here?; Navigating This Book; Takeaways; Conventions Used in This Book; Online Resources; Figures; Code Snippets; O'Reilly Safari; How to Contact Us; Acknowledgments; Part I. The Beam Model; Chapter 1. Streaming 101; Terminology: What Is Streaming?; On the Greatly Exaggerated Limitations of Streaming; Event Time Versus Processing Time; Data Processing Patterns; Bounded Data; Unbounded Data: Batch; Unbounded Data: Streaming; Summary; Chapter 2. The What, Where, When, and How of Data Processing; Roadmap | |
| 505 | 8 | |a Batch Foundations: What and WhereWhat: Transformations; Where: Windowing; Going Streaming: When and How; When: The Wonderful Thing About Triggers Is Triggers Are Wonderful Things!; When: Watermarks; When: Early/On-Time/Late Triggers FTW!; When: Allowed Lateness (i.e., Garbage Collection); How: Accumulation; Summary; Chapter 3. Watermarks; Definition; Source Watermark Creation; Perfect Watermark Creation; Heuristic Watermark Creation; Watermark Propagation; Understanding Watermark Propagation; Watermark Propagation and Output Timestamps; The Tricky Case of Overlapping Windows | |
| 505 | 8 | |a Percentile WatermarksProcessing-Time Watermarks; Case Studies; Case Study: Watermarks in Google Cloud Dataflow; Case Study: Watermarks in Apache Flink; Case Study: Source Watermarks for Google Cloud Pub/Sub; Summary; Chapter 4. Advanced Windowing; When/Where: Processing-Time Windows; Event-Time Windowing; Processing-Time Windowing via Triggers; Processing-Time Windowing via Ingress Time; Where: Session Windows; Where: Custom Windowing; Variations on Fixed Windows; Variations on Session Windows; One Size Does Not Fit All; Summary; Chapter 5. Exactly-Once and Side Effects | |
| 505 | 8 | |a Why Exactly Once MattersAccuracy Versus Completeness; Side Effects; Problem Definition; Ensuring Exactly Once in Shuffle; Addressing Determinism; Performance; Graph Optimization; Bloom Filters; Garbage Collection; Exactly Once in Sources; Exactly Once in Sinks; Use Cases; Example Source: Cloud Pub/Sub; Example Sink: Files; Example Sink: Google BigQuery; Other Systems; Apache Spark Streaming; Apache Flink; Summary; Part II. Streams and Tables; Chapter 6. Streams and Tables; Stream-and-Table Basics Or: a Special Theory of Stream and Table Relativity | |
| 505 | 8 | |a Toward a General Theory of Stream and Table RelativityBatch Processing Versus Streams and Tables; A Streams and Tables Analysis of MapReduce; Reconciling with Batch Processing; What, Where, When, and How in a Streams and Tables World; What: Transformations; Where: Windowing; When: Triggers; How: Accumulation; A Holistic View of Streams and Tables in the Beam Model; A General Theory of Stream and Table Relativity; Summary; Chapter 7. The Practicalities of Persistent State; Motivation; The Inevitability of Failure; Correctness and Efficiency; Implicit State; Raw Grouping; Incremental Combining | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau's popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You'll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Streaming technology (Telecommunications) | |
| 650 | 0 | |a Electronic data processing |x Distributed processing. | |
| 650 | 0 | |a Big data. | |
| 650 | 2 | |a Webcasts as Topic | |
| 650 | 6 | |a En continu (Télécommunications) | |
| 650 | 6 | |a Traitement réparti. | |
| 650 | 6 | |a Données volumineuses. | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 650 | 7 | |a Big data. |2 fast |0 (OCoLC)fst01892965 | |
| 650 | 7 | |a Electronic data processing |x Distributed processing. |2 fast |0 (OCoLC)fst00906987 | |
| 650 | 7 | |a Streaming technology (Telecommunications) |2 fast |0 (OCoLC)fst01134637 | |
| 654 | |a COMPUTERS |b General. |2 bisacsh | ||
| 700 | 1 | |a Chernyak, Slava, |e author. | |
| 700 | 1 | |a Lax, Reuven, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Akidau, Tyler. |t Streaming systems. |d Sebastopol, CA : O'Reilly Media, Inc., [2018] |z 9781491983874 |z 1491983876 |w (OCoLC)975362965 |
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