Hadoop with Python (Zachary Radtka, et al)

 
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Hadoop with Python (Zachary Radtka, et al)

Although Python is particularly well-suited for use with this distributed storage and processing technology, Hadoop is primarily designed in Java.

This short book teaches you how to use Python with the Apache Pig platform and Pig Latin language, the Hadoop Distributed File System (HDFS), MapReduce, and the Apache Spark cluster-computing framework.

The fundamental ideas underlying Hadoop, MapReduce, Pig, and Spark are covered in this book. You'll then learn how to use a variety of Python tools to interact with these technologies through several examples and use cases.

  • Use the Python library Snakebite to access HDFS programmatically from within Python applications
  • Write MapReduce jobs in Python with mrjob, the Python MapReduce library
  • Extend Pig Latin with user-defined functions (UDFs) in Python
  • Use the Spark Python API (PySpark) to write Spark programs with Python
  • Learn how to use the Luigi Python workflow scheduler to manage MapReduce jobs and Pig scripts

Ebook Details

About the Authors
  • Platform engineer Zachary Radtke at Miner & Kasch has a lot of expertise in building custom analytics that operates on petabyte-scale data sets.
  • Donald Miner is a data scientist and an enthusiastic user of Apache Hadoop. He holds the position of Chief Technology Officer of ClearEdge IT Solutions, a business that offers expert Big Data services.
Published
Published Date / Year
(2016)
eBook Format
HTML, PDF, ePub, mobi (Kindle)
Language
English
ISBN-13
978-1-491-94227-7

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