Storm Applied
About the BOOK
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.
Features
` 799 /Authors: Allen, Jankowski,
ISBN: 9789351197980 • Pages: 278 Pathirana, and Montalenti
�
Mapping real problems to Storm
components
�
Performance tuning and scaling
�
Practical troubleshooting and
debugging
�
Exactly-once processing with
Trident
Summary
Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing
and analyzing real-time data streams. This immediately useful book starts by building a solid foundation of
Storm essentials so that you learn how to think about designing Storm solutions the right way from day one.
But it quickly dives into real-world case studies that will bring the novice up to speed with productionizing
Storm.
About the Authors
Sean Allen, Matthew Jankowski, and Peter Pathirana lead the development
team for a high-volume, search-intensive commercial web application at
TheLadders.
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Table of Contents
Chapter 1 Introducing Storm
yy Tuning: I wanna go fast
yy What is big data?
yy Latency: when external systems take their time
yy How Storm fits into the big data picture
yy Storm’s metrics-collecting API
yy Why you’d want to use Storm
Chapter 7 Resource contention
Chapter 2 Core Storm concepts
yy Changing the number of worker processes running on a
yy Problem definition: GitHub commit count dashboard
worker node
yy Changing the amount of memory allocated to worker
yy Basic Storm concepts
yy Implementing a GitHub commit count dashboard in Storm
Chapter 3 Topology design
processes (JVMs)
yy Figuring out which worker nodes/processes a topology is
executing on
yy Approaching topology design
yy Contention for worker processes in a Storm cluster
yy Problem definition: a social heat map
yy Precepts for mapping the solution to Storm
yy Initial implementation of the design
yy Memory contention within a worker process (JVM)
yy Memory contention on a worker node
yy Worker node CPU contention
yy Scaling the topology
yy Worker node I/O contention
yy Topology design paradigms
Chapter 8 Storm internals
Chapter 4 Creating robust topologies
yy The commit count topology revisited
yy Requirements for reliability
yy Problem definition: a credit card authorization system
yy Basic implementation of the bolts
yy Diving into the details of an executor
yy Routing and tasks
yy Knowing when Storm’s internal queues overflow
yy Guaranteed message processing
yy Addressing internal Storm buffers overflowing
yy Replay semantics
Chapter 5 Moving from local to remote topologies
yy Tweaking buffer sizes for performance gain
Chapter 9 Trident
yy The Storm cluster
yy Fail-fast philosophy for fault tolerance within a Storm
cluster
yy What is Trident?
yy Kafka and its role with Trident
yy Installing a Storm cluster
yy Problem definition: Internet radio
yy Getting your topology to run on a Storm cluster
yy Implementing the internet radio design as a Trident
yy The Storm UI and its role in the Storm cluster
topology
yy Accessing the persisted counts through DRPC
Chapter 6 Tuning in Storm
yy Problem definition: Daily Deals! reborn
yy Mapping Trident operations to Storm primitives
yy Initial implementation
yy Scaling a Trident topology
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