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| Autore: |
Ellis Byron
|
| Titolo: |
Real-time analytics : techniques to analyze and visualize streaming data / / Byron Ellis
|
| Pubblicazione: | Indianapolis, Indiana : , : Wiley, , 2014 |
| ©2014 | |
| Edizione: | 1st edition |
| Descrizione fisica: | 1 online resource (841 p.) |
| Disciplina: | 025.04 |
| Soggetto topico: | Real-time data processing |
| Data flow computing | |
| Data mining | |
| Note generali: | Includes index. |
| Nota di contenuto: | Cover; Chapter 1: Introduction to Streaming Data; Sources of Streaming Data; Why Streaming Data Is Different; Infrastructures and Algorithms; Conclusion; Part I: Streaming A Analytics Architecture; Chapter 2: Designing Real-Time Streaming Architectures; Real-Time Architecture Components; Features of a Real-Time Architecture; Languages for Real-Time Programming; A Real-Time Architecture Checklist; Conclusion; Chapter 3: Service Configuration and Coordination; Motivation for Configuration and Coordination Systems; Maintaining Distributed State; Apache ZooKeeper; Conclusion |
| Chapter 4: Data-Flow Management in Streaming Analysis Distributed Data Flows; Apache Kafka: High-Throughput Distributed Messaging; Apache Flume: Distributed Log Collection; Conclusion; Chapter 5: Processing Streaming Data; Distributed Streaming Data Processing; Processing Data with Storm; Processing Data with Samza; Conclusion; Chapter 6: Storing Streaming Data; Consistent Hashing; "NoSQL" Storage Systems; Other Storage Technologies; Choosing a Technology; Warehousing; Conclusion; Part II: Analysis and Visualization; Chapter 7: Delivering Streaming Metrics; Streaming Web Applications | |
| Visualizing Data Mobile Streaming Applications; Conclusion; Chapter 8: Exact Aggregation and Delivery; Timed Counting and Summation; Multi-Resolution Time-Series Aggregation; Stochastic Optimization; Delivering Time-Series Data; Conclusion; Chapter 9: Statistical Approximation of Streaming Data; Numerical Libraries; Probabilities and Distributions; Working with Distributions; Random Number Generation; Sampling Procedures; Conclusion; Chapter 10: Approximating Streaming Data with Sketching; Registers and Hash Functions; Working with Sets; The Bloom Filter; Distinct Value Sketches | |
| The Count-Min Sketch Other Applications; Conclusion; Chapter 11: Beyond Aggregation; Models for Real-Time Data; Forecasting with Models; Monitoring; Real-Time Optimization; Conclusion; Introduction; Overview and Organization of This Book; Who Should Read This Book; Tools You Will Need; What''s on the Website; Time to Dive In; End User License Agreement | |
| Sommario/riassunto: | Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, |
| Titolo autorizzato: | Real-time analytics ![]() |
| ISBN: | 1-118-83802-5 |
| 1-118-83793-2 | |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910814081903321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |