Getting Started with Storm Continuous Streaming Computation with Twitter's Cluster Technology
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Sprache:Englisch
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Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
16.10.2012
Abbildungen
w. Illustrationen
Verlag
O'Reilly MediaSeitenzahl
104
Maße (L/B/H)
24/17,9/1 cm
Gewicht
192 g
Sprache
Englisch
ISBN
978-1-4493-2401-8
Even as big data is turning the world upside down, the next phase of the revolution is already taking shape: real-time data analysis. This hands-on guide introduces you to Storm, a distributed, JVM-based system for processing streaming data. Through simple tutorials, sample Java code, and a complete real-world scenario, you’ll learn how to build fast, fault-tolerant solutions that process results as soon as the data arrives.
Discover how easy it is to set up Storm clusters for solving various problems, including continuous data computation, distributed remote procedure calls, and data stream processing.
* Learn how to program Storm components: spouts for data input and bolts for data transformation
* Discover how data is exchanged between spouts and bolts in a Storm topology
* Make spouts fault-tolerant with several commonly used design strategies
* Explore bolts—their life cycle, strategies for design, and ways to implement them
* Scale your solution by defining each component’s level of parallelism
* Study a real-time web analytics system built with Node.js, a Redis server, and a Storm topology
* Write spouts and bolts with non-JVM languages such as Python, Ruby, and Javascript
Discover how easy it is to set up Storm clusters for solving various problems, including continuous data computation, distributed remote procedure calls, and data stream processing.
* Learn how to program Storm components: spouts for data input and bolts for data transformation
* Discover how data is exchanged between spouts and bolts in a Storm topology
* Make spouts fault-tolerant with several commonly used design strategies
* Explore bolts—their life cycle, strategies for design, and ways to implement them
* Scale your solution by defining each component’s level of parallelism
* Study a real-time web analytics system built with Node.js, a Redis server, and a Storm topology
* Write spouts and bolts with non-JVM languages such as Python, Ruby, and Javascript
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