Beginning Apache Pig: Big Data Processing Made Easy

  • 3h 21m
  • Balaswamy Vaddeman
  • Apress
  • 2016

Learn to use Apache Pig to develop lightweight big data applications easily and quickly. This book shows you many optimization techniques and covers every context where Pig is used in big data analytics. Beginning Apache Pig shows you how Pig is easy to learn and requires relatively little time to develop big data applications.

The book is divided into four parts: the complete features of Apache Pig; integration with other tools; how to solve complex business problems; and optimization of tools. You'll discover topics such as MapReduce and why it cannot meet every business need; the features of Pig Latin such as data types for each load, store, joins, groups, and ordering; how Pig workflows can be created; submitting Pig jobs using Hue; and working with Oozie. You'll also see how to extend the framework by writing UDFs and custom load, store, and filter functions. Finally you'll cover different optimization techniques such as gathering statistics about a Pig script, joining strategies, parallelism, and the role of data formats in good performance.

What You Will Learn

  • Use all the features of Apache Pig
  • Integrate Apache Pig with other tools
  • Extend Apache Pig
  • Optimize Pig Latin code
  • Solve different use cases for Pig Latin

Who This Book Is For

All levels of IT professionals: architects, big data enthusiasts, engineers, developers, and big data administrators

In this Book

  • MapReduce and Its Abstractions
  • Data Types
  • Grunt
  • Pig Latin Fundamentals
  • Joins and Functions
  • Creating and Scheduling Workflows Using Apache Oozie
  • HCatalog
  • Pig Latin in Hue
  • Pig Latin Scripts in Apache Falcon
  • Macros
  • User-Defined Functions
  • Writing Eval Functions
  • Writing Load and Store Functions
  • Troubleshooting
  • Data Formats
  • Optimization
  • Hadoop Ecosystem Tools