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This guide is an ideal learning tool and reference for Apache Pig, the open source engine for executing parallel data flows on Hadoop. With Pig, you can batch-process data without having to create a full-fledged application—making it easy for you to experiment with new datasets.
This fully updated edition of Programming Pig introduces new users to Pig, and provides experienced users with comprehensive coverage on key features such as the Pig Latin scripting language, the Grunt shell, and User Defined Functions (UDFs) for extending Pig. If you need to analyze terabytes of data, this book shows you how to do it efficiently with Pig.
Chapter 2Installing and Running Pig
Chapter 3Pig’s Data Model
Chapter 4Introduction to Pig Latin
Chapter 5Advanced Pig Latin
Chapter 6Developing and Testing Pig Latin Scripts
Chapter 7Making Pig Fly
Chapter 8Embedding Pig
Chapter 9Writing Evaluation and Filter Functions
Chapter 10Writing Load and Store Functions
Chapter 11Pig on Tez
Chapter 12Pig and Other Members of the Hadoop Community
Chapter 13Use Cases and Programming Examples
Appendix ABuilt-in User Defined Functions and Piggybank
Alan is co-founder of Hortonworks and an original member of the engineering team that took Pig from a Yahoo! Labs research project to a successful Apache open source project. Alan also designed HCatalog and guided its adoption as an Apache Incubator project. Alan has a BS in Mathematics from Oregon State University and a MA in Theology from Fuller Theological Seminary. He is also the author of Programming Pig, a book from O’Reilly Press. Follow Alan on Twitter: @alanfgates.
Daniel is an Apache Pig PMC member/committer involved with Pig for 6 years at Yahoo and now at Hortonworks. He has a PhD in Computer Science from University of Central Florida, with a specialization in distributed computing, data mining and computer security.