Pro Spark Streaming
Apress (Verlag)
978-1-4842-1480-0 (ISBN)
In the last few years, Spark has become synonymous with big data processing. DStreams enhance the underlying Spark processing engine to support streaming analysis with a novel micro-batch processing model. Pro Spark Streaming by Zubair Nabi will enable you to become a specialist of latency sensitive applications by leveraging the key features of DStreams, micro-batch processing, and functional programming. To this end, the book includes ready-to-deploy examples and actual code. Pro Spark Streamingwill act as the bible of Spark Streaming.
What You'll Learn
Discover Spark Streaming application development and best practices
Work with the low-level details of discretized streams
Optimize production-grade deployments of Spark Streaming via configuration recipes and instrumentation using Graphite, collectd, and Nagios
Ingest data from disparate sources including MQTT, Flume, Kafka, Twitter, and a custom HTTP receiver
Integrate and couple with HBase, Cassandra, and Redis
Take advantage of design patterns for side-effects and maintaining state across the Spark Streaming micro-batch model
Implement real-time and scalable ETL using data frames, SparkSQL, Hive, and SparkR
Use streaming machine learning, predictive analytics, and recommendations
Mesh batch processing with stream processing via the Lambda architecture
Who This Book Is For
Data scientists, big data experts, BI analysts, and data architects.
Zubair Nabi is one of the very few computer scientists who have solved Big Data problems in all three domains: academia, research, and industry. He currently works at Qubit, a London-based start up backed by Goldman Sachs, Accel Partners, Salesforce Ventures, and Balderton Capital. Qubit helps retailers understand their customers and provide personalized customer experience, and which has a rapidly growing client base that includes Staples, Emirates, Thomas Cook, and Topshop. Prior to Qubit, he was a researcher at IBM Research, where he worked at the intersection of Big Data systems and analytics to solve real-world problems in the telecommunication, electricity, and urban dynamics space. Zubair’s work has been featured in MIT Technology Review, SciDev, CNET, and Asian Scientist, and on Swedish National Radio, among others. He has authored more than 20 research papers, published by some of the top publication venues in computer science including USENIX Middleware, ECML PKDD, and IEEE BigData; and he also has a number of patents to his credit. Zubair has an MPhil in computer science with distinction from Cambridge.
Chapter 1: The Hitchhiker's Guide to Big Data.- Chapter 2: Introduction to Spark.- Chapter 3: DStreams: Realtime RDDs.- Chapter 4: High Velocity Streams: Parallelism and Other Stories.- Chapter 5: Real-time Route 66: Linking External Data Sources.- Chapter 6: The Art of Side Effects.- Chapter 7: Getting Ready for Prime Time.- Chapter 8: Real-time ETL and Analytics Magic.- Chapter 9: Machine Learning at Scale.- Chapter 10: Of Clouds, Lambdas, and Pythons.
| Zusatzinfo | 61 Illustrations, color; 7 Illustrations, black and white; XIX, 230 p. 68 illus., 61 illus. in color. |
|---|---|
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Informatik ► Netzwerke | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Sozialwissenschaften | |
| ISBN-10 | 1-4842-1480-3 / 1484214803 |
| ISBN-13 | 978-1-4842-1480-0 / 9781484214800 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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