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Pig Design Patterns

By : Pradeep Pasupuleti
Book Image

Pig Design Patterns

By: Pradeep Pasupuleti

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Pig Design Patterns
Pradeep Pasupuleti
Apr, 2014 | 310 pages
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Table of Contents (16 chapters)
Pig Design Patterns
Pig Design Patterns
Credits
Credits
Foreword
Foreword
About the Author
About the Author
Acknowledgments
Acknowledgments
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Setting the Context for Design Patterns in Pig
Setting the Context for Design Patterns in Pig
Understanding design patterns
The scope of design patterns in Pig
Hadoop demystified – a quick reckoner
Pig – a quick intro
Understanding Pig through the code
Summary
2
Data Ingest and Egress Patterns
Data Ingest and Egress Patterns
The context of data ingest and egress
Types of data in the enterprise
Ingest and egress patterns for multistructured data
The ingress and egress patterns for the NoSQL data
The ingress and egress patterns for structured data
The ingress and egress patterns for semi-structured data
JSON ingress and egress patterns
Summary
3
Data Profiling Patterns
Data Profiling Patterns
Data profiling for Big Data
Rationale for using Pig in data profiling
The data type inference pattern
The basic statistical profiling pattern
The pattern-matching pattern
The string profiling pattern
The unstructured text profiling pattern
Summary
4
Data Validation and Cleansing Patterns
Data Validation and Cleansing Patterns
Data validation and cleansing for Big Data
Choosing Pig for validation and cleansing
The constraint validation and cleansing design pattern
The regex validation and cleansing design pattern
The corrupt data validation and cleansing design pattern
The unstructured text data validation and cleansing design pattern
Summary
5
Data Transformation Patterns
Data Transformation Patterns
Data transformation processes
The structured-to-hierarchical transformation pattern
The data normalization pattern
The data integration pattern
The aggregation pattern
The data generalization pattern
Summary
6
Understanding Data Reduction Patterns
Understanding Data Reduction Patterns
Data reduction – a quick introduction
Data reduction considerations for Big Data
Dimensionality reduction – the Principal Component Analysis design pattern
Numerosity reduction – the histogram design pattern
Numerosity reduction – sampling design pattern
Numerosity reduction – clustering design pattern
Summary
7
Advanced Patterns and Future Work
Advanced Patterns and Future Work
The clustering pattern
The topic discovery pattern
The natural language processing pattern
The classification pattern
Future trends
Summary
Index
Index

Credits

Author

Pradeep Pasupuleti

Reviewers

Aaron Binns

Shingo Furuyama

Shashwat Shriparv

Fábio Uechi

Acquisition Editor

Owen Roberts

Content Development Editor

Priya Singh

Technical Editors

Aparna Kumar

Pooja Nair

Nikhil Potdukhe

Copy Editors

Alisha Aranha

Brandt D'Mello

Gladson Monteiro

Adithi Shetty

Project Coordinator

Wendell Palmer

Proofreaders

Ting Baker

Elinor Perry-Smith

Indexer

Hemangini Bari

Graphics

Sheetal Aute

Ronak Dhruv

Yuvraj Mannari

Abhinash Sahu

Production Coordinator

Aditi Gajjar Patel

Cover Work

Aditi Gajjar Patel

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