STORM APPLIED by SEAN T. ALLEN, MATTHEW JANKOWSKI, PETER PATHIRANA

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STORM APPLIED

by SEAN T. ALLEN, MATTHEW JANKOWSKI, PETER PATHIRANA

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Storm Applied is an example-driven guide to processing and analyzing real-time data streams. This immediately useful book starts by teaching you how to design Storm solutions the right way. Then, it quickly dives into real-world case studies that show you how to scale a high-throughput stream processor, ensure smooth operation within a production cluster and more. Along the way, you'll learn to use Trident for stateful stream processing, along with other tools from the Storm ecosystem. Book Features - Introducing Storm Core Storm concepts Topology design Creating robust topologies Moving from local to remote topologies Tuning in Storm Resource contention Storm internals Trident Table of Contents - Chapter 1 - Introducing Storm What is big data? How Storm fits into the big data picture Why you�d want to use Storm Chapter 2 - Core Storm concepts Problem definition - GitHub commit count dashboard Basic Storm concepts Implementing a GitHub commit count dashboard in Storm Chapter 3 - Topology design Approaching topology design Problem definition - a social heat map Precepts for mapping the solution to Storm Initial implementation of the design Scaling the topology Topology design paradigms Chapter 4 - Creating robust topologies Requirements for reliability Problem definition - a credit card authorization system Basic implementation of the bolts Guaranteed message processing Replay semantics Chapter 5 - Moving from local to remote topologies The Storm cluster Fail-fast philosophy for fault tolerance within a Storm cluster Installing a Storm cluster Getting your topology to run on a Storm cluster The Storm UI and its role in the Storm cluster Chapter 6 - Tuning in Storm Problem definition - Daily Deals! reborn Initial implementation Tuning - I wanna go fast Latency - when external systems take their time Storm�s metrics-collecting API Chapter 7 - Resource contention Changing the number of worker processes running on a worker node Changing the amount of memory allocated to worker processes (JVMs) Figuring out which worker nodes/processes a topology is executing on Contention for worker processes in a Storm cluster Memory contention within a worker process (JVM) Memory contention on a worker node Worker node CPU contention Worker node I/O contention Chapter 8 - Storm internals The commit count topology revisited Diving into the details of an executor Routing and tasks Knowing when Storm�s internal queues overflow Addressing internal Storm buffers overflowing Tweaking buffer sizes for performance gain Chapter 9 - Trident What is Trident? Kafka and its role with Trident Problem definition - Internet radio Implementing the internet radio design as a Trident topology Accessing the persisted counts through DRPC Mapping Trident operations to Storm primitives Scaling a Trident topology SummaryISBN - 9789351197980

Pages : 280

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