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	Storm Applied by Sean T. Allen, Matthew Jankowski, Peter Pathirana
	Price : Rs 799.00
	Your Price : Rs 679.15

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