Pig Design Patterns. Simplify Hadoop programming to create complex end-to-end Enterprise Big Data solutions with Pig

Spis treści ebooka

• Pig Design Patterns
  • Table of Contents
  • Pig Design Patterns
  • Credits
  • Foreword
  • About the Author
  • Acknowledgments
  • 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
      • Motivation for this book
    • What you need for this book
    • Who this book is for
    • Conventions
    • Reader feedback
    • Customer support
      • Downloading the example code
        • Third-party libraries
        • Datasets
      • Errata
      • Piracy
      • Questions
  • 1. Setting the Context for Design Patterns in Pig
    • Understanding design patterns
    • The scope of design patterns in Pig
    • Hadoop demystified a quick reckoner
      • The enterprise context
      • Common challenges of distributed systems
      • The advent of Hadoop
      • Hadoop under the covers
      • Understanding the Hadoop Distributed File System
        • HDFS design goals
        • Working of HDFS
      • Understanding MapReduce
        • Understanding how MapReduce works
        • The MapReduce internals
    • Pig a quick intro
      • Understanding the rationale of Pig
      • Understanding the relevance of Pig in the enterprise
      • Working of Pig an overview
        • Firing up Pig
        • The use case
        • Code listing
        • The dataset
    • Understanding Pig through the code
      • Pigs extensibility
      • Operators used in code
      • The EXPLAIN operator
      • Understanding Pig's data model
        • Primitive types
        • Complex types
          • The relevance of schemas
    • Summary
  • 2. 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
      • Considerations for log ingestion
        • The Apache log ingestion pattern
        • Background
        • Motivation
        • Use cases
        • Pattern implementation
        • Code snippets
          • Code for the CommonLogLoader class
          • Code for the CombinedLogLoader class
        • Results
        • Additional information
      • The Custom log ingestion pattern
        • Background
        • Motivation
        • Use cases
        • Pattern implementation
        • Code snippets
        • Results
        • Additional information
      • The image ingress and egress pattern
        • Background
        • Motivation
        • Use cases
        • Pattern implementation
          • The image Ingress Implementation
          • The image egress implementation
        • Code snippets
          • The image ingress
            • Pig script
            • Image to a sequence UDF snippet
          • The image egress
            • Pig script
            • Sequence to an image UDF
        • Results
        • Additional information
    • The ingress and egress patterns for the NoSQL data
      • MongoDB ingress and egress patterns
        • Background
        • Motivation
        • Use cases
        • Pattern implementation
          • The ingress implementation
          • The egress implementation
        • Code snippets
          • The ingress code
          • The egress code
        • Results
        • Additional information
      • The HBase ingress and egress pattern
        • Background
        • Motivation
        • Use cases
        • Pattern implementation
          • The ingress implementation
          • The egress implementation
        • Code snippets
          • The ingress code
          • The egress code
        • Results
        • Additional information
    • The ingress and egress patterns for structured data
      • The Hive ingress and egress patterns
        • Background
        • Motivation
        • Use cases
        • Pattern implementation
          • The ingress implementation
          • The egress implementation
        • Code snippets
          • The ingress Code
            • Importing data using RCFile
            • Importing data using HCatalog
          • The egress code
        • Results
        • Additional information
    • The ingress and egress patterns for semi-structured data
      • The mainframe ingestion pattern
        • Background
        • Motivation
        • Use cases
        • Pattern implementation
        • Code snippets
        • Results
        • Additional information
      • XML ingest and egress patterns
        • Background
        • Motivation
          • Motivation for ingesting raw XML
          • Motivation for ingesting binary XML
          • Motivation for egression of XML
        • Use cases
        • Pattern implementation
          • The implementation of the XML raw ingestion
          • The implementation of the XML binary ingestion
      • Code snippets
        • The XML raw ingestion code
        • The XML binary ingestion code
        • The XML egress code
          • Pig script
          • The XML storage
        • Results
        • Additional information
    • JSON ingress and egress patterns
      • Background
        • Motivation
        • Use cases
        • Pattern implementation
          • The ingress implementation
          • The egress implementation
        • Code snippets
          • The ingress code
            • The code for simple JSON
            • The code for nested JSON
          • The egress code
        • Results
        • Additional information
    • Summary
  • 3. Data Profiling Patterns
    • Data profiling for Big Data
      • Big Data profiling dimensions
      • Sampling considerations for profiling Big Data
        • Sampling support in Pig
    • Rationale for using Pig in data profiling
    • The data type inference pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
        • Pig script
        • Java UDF
      • Results
      • Additional information
    • The basic statistical profiling pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
        • Pig script
        • Macro
      • Results
      • Additional information
    • The pattern-matching pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
        • Pig script
        • Macro
      • Results
      • Additional information
    • The string profiling pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
        • Pig script
        • Macro
      • Results
      • Additional information
    • The unstructured text profiling pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
        • Pig script
        • Java UDF for stemming
        • Java UDF for generating TF-IDF
      • Results
      • Additional information
    • Summary
  • 4. 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
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The regex validation and cleansing design pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The corrupt data validation and cleansing design pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The unstructured text data validation and cleansing design pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • Summary
  • 5. Data Transformation Patterns
    • Data transformation processes
    • The structured-to-hierarchical transformation pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The data normalization pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The data integration pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The aggregation pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The data generalization pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • Summary
  • 6. Understanding Data Reduction Patterns
    • Data reduction a quick introduction
    • Data reduction considerations for Big Data
    • Dimensionality reduction the Principal Component Analysis design pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
        • Limitations of PCA implementation
      • Code snippets
      • Results
      • Additional information
    • Numerosity reduction the histogram design pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • Numerosity reduction sampling design pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • Numerosity reduction clustering design pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • Summary
  • 7. Advanced Patterns and Future Work
    • The clustering pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The topic discovery pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The natural language processing pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • The classification pattern
      • Background
      • Motivation
      • Use cases
      • Pattern implementation
      • Code snippets
      • Results
      • Additional information
    • Future trends
      • Emergence of data-driven patterns
      • The emergence of solution-driven patterns
      • Patterns addressing programmability constraints
    • Summary
  • Index

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