Beginning Apache Pig

1. Front Matter

   Pages i-xxiii

   PDF

2. MapReduce and Its Abstractions

   • Balaswamy Vaddeman

   Pages 1-20

3. Data Types

   • Balaswamy Vaddeman

   Pages 21-31

4. Grunt

   • Balaswamy Vaddeman

   Pages 33-40

5. Pig Latin Fundamentals

   • Balaswamy Vaddeman

   Pages 41-67

6. Joins and Functions

   • Balaswamy Vaddeman

   Pages 69-87

7. Creating and Scheduling Workflows Using Apache Oozie

   • Balaswamy Vaddeman

   Pages 89-101

8. HCatalog

   • Balaswamy Vaddeman

   Pages 103-113

9. Pig Latin in Hue

   • Balaswamy Vaddeman

   Pages 115-122

10. Pig Latin Scripts in Apache Falcon

    • Balaswamy Vaddeman

    Pages 123-136

11. Macros

    • Balaswamy Vaddeman

    Pages 137-145

12. User-Defined Functions

    • Balaswamy Vaddeman

    Pages 147-155

13. Writing Eval Functions

    • Balaswamy Vaddeman

    Pages 157-169

14. Writing Load and Store Functions

    • Balaswamy Vaddeman

    Pages 171-186

15. Troubleshooting

    • Balaswamy Vaddeman

    Pages 187-199

16. Data Formats

    • Balaswamy Vaddeman

    Pages 201-208

17. Optimization

    • Balaswamy Vaddeman

    Pages 209-223

18. Hadoop Ecosystem Tools

    • Balaswamy Vaddeman

    Pages 225-248

19. Back Matter

    Pages 249-274

    PDF

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 asgathering 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

• Apache Pig
• Grunt
• Pig Latin
• HCatalogue
• HCatalog
• Pig Jobs
• Hue
• Apache Falcon
• Macros
• Hadoop

• Hyderabad, India

  Balaswamy Vaddeman

Balaswamy Vaddeman, Thinker, Blogger, Serious and Self-motivated Big data evangelist with 9 years of experience in IT and 4 years of experience in Big data space. My Big data experience covers multiple areas like delivery of analytical applications, product development, consulting, training, book reviews, hackathons and mentoring and helping people on forums. I have proved myself while delivering analytical applications in retail, banking and finance domain in 3 aspects (Development, Administration and Architecture) of Hadoop related technologies. At Startup Company, I had developed a Hadoop based product that was used for delivering of analytical applications without writing code.
 In 2013 I had won Hadoop Hackathon event for Hyderabad conducted by Cloudwick technologies. Being top contributor at stackoverflow.com, I helped many people on big data at multiple websites like stackoverflow.com and quora.com. With so much passion on big data I went ahead as independenttrainer and consultant to train hundreds of people and to set big data teams in couple of companies.

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