Learning Cascading
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Learning Cascading

  1. 276 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
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Learning Cascading


Table of Contents

Learning Cascading
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers, and more
Why subscribe?
Free access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
1. The Big Data Core Technology Stack
Reviewing Hadoop
Hadoop architecture
HDFS – the Hadoop Distributed File System
The NameNode
The secondary NameNode
DataNodes
MapReduce execution framework
The JobTracker
The TaskTracker
Hadoop jobs
Distributed cache
Counters
YARN – MapReduce version 2
A simple MapReduce job
Beyond MapReduce
The Cascading framework
The execution graph and flow planner
How Cascading produces MapReduce jobs
Summary
2. Cascading Basics in Detail
Understanding common Cascading themes
Data flows as processes
Understanding how Cascading represents records
Using tuples and defining fields
Using a Fields object, named field groups, and selectors
Data typing and coercion
Defining schemes
Schemes in detail
TupleEntry
Understanding how Cascading controls data flow
Using pipes
Creating and chaining
Pipe operations
Each
Splitting
GroupBy and sorting
Every
Merging and joining
The Merge pipe
The join pipes – CoGroup and HashJoin
CoGroup
HashJoin
Default output selectors
Using taps
Flow
FlowConnector
Cascades
Local and Hadoop modes
Common errors
Putting it all together
Summary
3. Understanding Custom Operations
Understanding operations
Operations and fields
The Operation class and interface hierarchy
The basic operation lifecycle
Contexts
FlowProcess
OperationCall<Context>
An operation processing sequence and its methods
Operation types
Each operations
Filters
Filter calling sequence
Built-in filters
Function
Function calling sequence
Built-in functions
Every operations
Aggregator
Aggregator calling sequence
Built-in aggregators
Buffers
Buffer calling sequence
Built-in buffers
Assertions
ValueAssertion calling sequence
GroupAssertion calling sequence
AssertionLevel
Using assertions
Built-in assertions
A note about implementing BaseOperation methods
Summary
4. Creating Custom Operations
Writing custom operations
Writing a filter
Writing a function
Writing an aggregator
Writing a custom assertion
Writing a buffer
Identifying common use cases for custom operations
Putting it all together
Summary
5. Code Reuse and Integration
Creating and using subassemblies
Built-in subassemblies
Creating a new custom subassembly
Using custom subassemblies
Using cascades
Building a complex workflow using cascades
Skipping a flow in a cascade
Intermediate file management
Dynamically controlling flows
Instrumentation and counters
Using counters to control flow
Using existing MapReduce jobs
Using fluent programming techniques
The FlowDef fluent interface
Integrating external components
Flow and cascade events
Using external JAR files
Using Cascading as insulation from big data migrations and upgrades
Summary
6. Testing a Cascading Application
Debugging a Cascading application
Getting your environment ready for debugging
Using Cascading local mode debugging
Setting up Eclipse
Remote debugging
Using assertions
The Debug() filter
Managing exceptions with traps
Checkpoints
Managing bad data
Viewing flow sequencing using DOT files
Testing strategies
Unit testing and JUnit
Mocking
Integration testing
Load and performance testing
Summary
7. Optimizing the Performance of a Cascading Application
Optimizing performance
Optimizing Cascading
Optimizing Hadoop
A note about the effective use of checkpoints
Summary
8. Creating a Real-world Application in Cascading
Project description – Business Intelligence case study on monitoring the competition
Project scope – understanding requirements
Understanding the project domain – text analytics and natural language processing (NLP)
Conducting a simple named entity extraction
Defining the project – the Cascading development methodology
Project roles and responsibilities
Conducting data analysis
Performing functional decomposition
Designing the process and components
Creating and integrating the operations
Creating and using subassemblies
Building the workflow
Building flows
Managing the context
Building the cascade
Designing the test plan
Performing a unit test
Performing an integration test
Performing a cluster test
Performing a full load test
Refining and adjusting
Software packaging and delivery to the cluster
Next steps
Summary
9. Planning for Future Growth
Finding online resources
Using other Cascading tools
Lingual
Pattern
Driven
Fluid
Load
Multitool
Support for other languages
Hortonworks
Custom taps
Cascading serializers
Java open source mock frameworks
Summary
A. Downloadable Software
Contents
Installing and using
Index

Learning Cascading

Copyright © 2015 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: May 2015
Production reference: 1250515
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78528-891-3
www.packtpub.com

Credits

Authors
Michael Covert
Victoria Loewengart
Reviewers
Allen Driskill
Bernie French
Supreet Oberoi
Commissioning Editor
Veena Pagare
Acquisition Editor
Vivek Anantharaman
Content Development Editor
Prachi Bisht
Technical Editors
Ruchi Desai
Ankita Thakur
Copy Editors
Sonia Michelle Cheema
Ameesha Green
Project Coordinator
Shipra Chawhan
Proofreaders
Stephen Copestake
Safis Editing
Indexer
Monica Ajmera Mehta
Graphics
Disha Haria
Production Coordinator
Nilesh R. Mohite
Cover Work
Nilesh R. Mohite

Foreword

The Cascading project was started in 2007 to complete the promise that Apache Hadoop was indirectly making to people like me—that we can dramatically simplify data-oriented application development and deployment. This can be done not only from a tools perspective, but more importantly, from an organizational perspective. Take a thousand machines and make them look like one: one storage layer and a computing layer. This promise means I would never have to ask our IT group for another storage array, more disk space, or another overpriced box to manage. My team and I could just throw our data and applications at the cluster and move on...

Table of contents

  1. Learning Cascading

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