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  • Book Overview & Buying Storm Blueprints: Patterns for Distributed Real-time Computation
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Storm Blueprints: Patterns for Distributed Real-time Computation

Storm Blueprints: Patterns for Distributed Real-time Computation

By : Brian O'Neill
4.1 (8)
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Storm Blueprints: Patterns for Distributed Real-time Computation

Storm Blueprints: Patterns for Distributed Real-time Computation

4.1 (8)
By: Brian O'Neill
Buy this Book

Overview of this book

A blueprints book with 10 different projects built in 10 different chapters which demonstrate the various use cases of storm for both beginner and intermediate users, grounded in real-world example applications. Although the book focuses primarily on Java development with Storm, the patterns are more broadly applicable and the tips, techniques, and approaches described in the book apply to architects, developers, and operations. Additionally, the book should provoke and inspire applications of distributed computing to other industries and domains. Hadoop enthusiasts will also find this book a good introduction to Storm, providing a potential migration path from batch processing to the world of real-time analytics.
Table of Contents (17 chapters)
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Storm Blueprints: Patterns for Distributed Real-time Computation
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Storm Blueprints: Patterns for Distributed Real-time Computation
Credits
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Credits
About the Authors
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About the Authors
About the Reviewers
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About the Reviewers
www.PacktPub.com
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www.PacktPub.com
Preface
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Preface
Lock Free Chapter
1
Distributed Word Count
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Distributed Word Count
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Introducing elements of a Storm topology – streams, spouts, and bolts
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Introducing the word count topology data flow
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Implementing the word count topology
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Introducing parallelism in Storm
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Understanding stream groupings
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Guaranteed processing
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Summary
2
Configuring Storm Clusters
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Configuring Storm Clusters
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Introducing the anatomy of a Storm cluster
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Introducing the Storm technology stack
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Installing Storm on Linux
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Submitting topologies to a Storm cluster
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Automating the cluster configuration
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A rapid introduction to Puppet
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Summary
3
Trident Topologies and Sensor Data
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Trident Topologies and Sensor Data
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Examining our use case
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Introducing Trident topologies
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Introducing Trident spouts
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Introducing Trident operations – filters and functions
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Introducing Trident aggregators – Combiners and Reducers
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Introducing the Trident state
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Executing the topology
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Summary
4
Real-time Trend Analysis
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Real-time Trend Analysis
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Use case
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Architecture
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Installing the required software
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Introducing the sample application
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Introducing the log analysis topology
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The final topology
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Running the log analysis topology
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Summary
5
Real-time Graph Analysis
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Real-time Graph Analysis
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Use case
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Architecture
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A brief introduction to graph databases
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Software installation
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Setting up Titan to use the Cassandra storage backend
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Graph data model
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Connecting to the Twitter stream
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Twitter graph topology
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Implementing GraphState
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Implementing GraphFactory
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Implementing GraphTupleProcessor
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Putting it all together – the TwitterGraphTopology class
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Querying the graph with Gremlin
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Summary
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Artificial Intelligence
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Artificial Intelligence
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Designing for our use case
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Establishing the architecture
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Implementing the architecture
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Summary
7
Integrating Druid for Financial Analytics
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Integrating Druid for Financial Analytics
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Use case
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Integrating a non-transactional system
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The topology
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Implementing the architecture
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Executing the implementation
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Examining the analytics
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Summary
8
Natural Language Processing
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Natural Language Processing
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Motivating a Lambda architecture
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Examining our use case
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Realizing a Lambda architecture
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Designing the topology for our use case
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Implementing the design
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Examining the analytics
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Batch processing / historical analysis
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Hadoop
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Summary
9
Deploying Storm on Hadoop for Advertising Analysis
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Deploying Storm on Hadoop for Advertising Analysis
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Examining the use case
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Establishing the architecture
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Configuring the infrastructure
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Deploying the analytics
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Performing the analytics
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Deploying the topology
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Executing the topology
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Summary
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Storm in the Cloud
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Storm in the Cloud
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Introducing Amazon Elastic Compute Cloud (EC2)
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Introducing Apache Whirr
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Configuring a Storm cluster with Whirr
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Introducing Whirr Storm
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Introducing Vagrant
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Creating Storm-provisioning scripts
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Summary
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Index
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Index

Use case

In our use case, we have an application or set of applications (websites, enterprise applications, and so on) that use the popular logback framework (http://logback.qos.ch) for logging structured messages to disk (access logs, errors, and so on). Currently, the only way to perform analytics on that data is to process the files in batches using something like Hadoop. The latency introduced by that process dramatically slows down our reaction time; patterns gleaned from the log data only emerge hours, sometimes days, after a particular event occurred and the opportunity to take responsive action has passed. It is much more desirable to be actively notified of patterns as they emerge, rather than after the fact.

This use case represents a common theme and has a broad range of applications across many business scenarios, including the following applications:

  • Application Monitoring: For example, to notify system administrators when certain network errors reach a certain frequency

  • Intrusion...

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Tech Concepts
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Programming languages
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