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Hadoop with Python

Hadoop is mostly written in Java, but that doesn't exclude the use of other programming languages with this distributed storage and processing framework, particularly Python. With this concise book, you'll learn how to use Python with the Hadoop Distributed File System (HDFS), MapReduce, the Apache Pig platform and Pig Latin script, and the Apache Spark cluster-computing framework. This link for educational purpose only. Please remove file from your computer after familiarization.

Hadoop is mostly written in Java, but that doesn't exclude the use of other programming languages with this distributed storage and processing framework, particularly Python. With this concise book, you'll learn how to use Python with the Hadoop Distributed File System (HDFS), MapReduce, the Apache Pig platform and Pig Latin script, and the Apache Spark cluster-computing framework.

Authors Zachary Radtka and Donald Miner from the data science firm Miner & Kasch take you through the basic concepts behind Hadoop, MapReduce, Pig, and Spark. Then, through multiple examples and use cases, you'll learn how to work with these technologies by applying various Python tools.

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 

Book year:

Book pages: 71

ISBN: 1491942274

Book language: en

File size: 1.75 MB

File type: pdf

Published: 22 December 2019 - 13:00