This guide is an ideal learning tool and reference for Apache Pig, the programming language that helps you describe and run large data projects on Hadoop. With Pig, you can analyze data without having to create a full-fledged application—making it easy for you to experiment with new data sets.
Programming Pig shows newcomers how to get started, and teaches intermediate users the benefits of using Pig Latin, the data flow language for building and maintaining pipelines for processing data. Advanced users learn how to build complex data processing pipelines with Pig’s macros and modularity features, and discover how to build systems for complex data processing needs by embedding Pig Latin into scripting languages.
- Learn the advantages and disadvantages of using Pig instead of MapReduce
- Understand how Pig fits in with other Hadoop components, such as HDFS, Hive, MapReduce, and HBase
- Follow examples that explain built-in Pig Latin functions, and data operators such as join and group
- Use grunt, the shell that Pig provides for exploring and working with HDFS
- Get performance tuning tips for running Pig Latin scripts on Hadoop clusters in less time
- Extend Pig with powerful user defined functions written in Java or Python
About the Author
Alan is an original member of the engineering team that took Pig from a Yahoo! Labs research project to a successful Apache open source project. In this role he oversaw the implementation of the language, including programming interfaces and the overall design. He has presented Pig at numerous conferences and user groups, universities, and companies. Alan is a member of the Apache Software Foundation and a co-founder of Hortonworks. He has a BS in Mathematics from Oregon State University and a MA in Theology from Fuller Theological Seminary.
- Paperback: 222 pages
- Publisher: O’Reilly Media (September 2011)
- Language: English
- ISBN-10: 1449302645
- ISBN-13: 978-1449302641