Distributed Word Count | Storm Blueprints: Patterns for Distributed Real-time Computation

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Storm Blueprints: Patterns for Distributed Real-time Computation

4.1 (8)

Storm Blueprints: Patterns for Distributed Real-time Computation

4.1 (8)

Overview of this book

Storm Blueprints: Patterns for Distributed Real-time Computation

Storm Blueprints: Patterns for Distributed Real-time Computation

Credits

Credits

About the Authors

About the Authors

About the Reviewers

About the Reviewers

www.PacktPub.com

www.PacktPub.com

Preface

Preface

Free Chapter

Distributed Word Count

Distributed Word Count

Introducing elements of a Storm topology – streams, spouts, and bolts

Introducing the word count topology data flow

Implementing the word count topology

Introducing parallelism in Storm

Understanding stream groupings

Guaranteed processing

Summary

Configuring Storm Clusters

Configuring Storm Clusters

Introducing the anatomy of a Storm cluster

Introducing the Storm technology stack

Installing Storm on Linux

Submitting topologies to a Storm cluster

Automating the cluster configuration

A rapid introduction to Puppet

Summary

Trident Topologies and Sensor Data

Trident Topologies and Sensor Data

Examining our use case

Introducing Trident topologies

Introducing Trident spouts

Introducing Trident operations – filters and functions

Introducing Trident aggregators – Combiners and Reducers

Introducing the Trident state

Executing the topology

Summary

Real-time Trend Analysis

Real-time Trend Analysis

Use case

Architecture

Installing the required software

Introducing the sample application

Introducing the log analysis topology

The final topology

Running the log analysis topology

Summary

Real-time Graph Analysis

Real-time Graph Analysis

Use case

Architecture

A brief introduction to graph databases

Software installation

Setting up Titan to use the Cassandra storage backend

Graph data model

Connecting to the Twitter stream

Twitter graph topology

Implementing GraphState

Implementing GraphFactory

Implementing GraphTupleProcessor

Putting it all together – the TwitterGraphTopology class

Querying the graph with Gremlin

Summary

Artificial Intelligence

Artificial Intelligence

Designing for our use case

Establishing the architecture

Implementing the architecture

Summary

Integrating Druid for Financial Analytics

Integrating Druid for Financial Analytics

Use case

Integrating a non-transactional system

The topology

Implementing the architecture

Executing the implementation

Examining the analytics

Summary

Natural Language Processing

Natural Language Processing

Motivating a Lambda architecture

Examining our use case

Realizing a Lambda architecture

Designing the topology for our use case

Implementing the design

Examining the analytics

Batch processing / historical analysis

Hadoop

Summary

Deploying Storm on Hadoop for Advertising Analysis

Deploying Storm on Hadoop for Advertising Analysis

Examining the use case

Establishing the architecture

Configuring the infrastructure

Deploying the analytics

Performing the analytics

Deploying the topology

Executing the topology

Summary

Storm in the Cloud

Storm in the Cloud

Introducing Amazon Elastic Compute Cloud (EC2)

Introducing Apache Whirr

Configuring a Storm cluster with Whirr

Introducing Whirr Storm

Introducing Vagrant

Creating Storm-provisioning scripts

Summary

Index

Index

Chapter 1. Distributed Word Count

In this chapter, we will introduce you to the core concepts involved in creating distributed stream processing applications with Storm. We do this by building a simple application that calculates a running word count from a continuous stream of sentences. The word count example involves many of the structures, techniques, and patterns required for more complex computation, yet it is simple and easy to follow.

We will begin with an overview of Storm's data structures and move on to implementing the components that comprise a fully fledged Storm application. By the end of the chapter, you will have gained a basic understanding of the structure of Storm computations, setting up a development environment, and techniques for developing and debugging Storm applications.

This chapter covers the following topics:

Storm's basic constructs – topologies, streams, spouts, and bolts
Setting up a Storm development environment
Implementing a basic word count application
Parallelization and fault tolerance
Scaling by parallelizing computation tasks

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83

Tech Concepts

36

Programming languages

73

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