Skip to Content
Python Data Analysis Cookbook
book

Python Data Analysis Cookbook

by Ivan Idris
July 2016
Beginner to intermediate
462 pages
9h 14m
English
Packt Publishing
Content preview from Python Data Analysis Cookbook

Using HDFS

Hadoop Distributed File System (HDFS) is the storage component of the Hadoop framework for Big Data. HDFS is a distributed filesystem, which spreads data on multiple systems, and is inspired by the Google File System used by Google for its search engine. HDFS requires a Java Runtime Environment (JRE), and it uses a NameNode server to keep track of the files. The system also replicates the data so that losing a few nodes doesn't lead to data loss. The typical use case for HDFS is processing large read-only files. Apache Spark, also covered in this chapter, can use HDFS too.

Getting ready

Install Hadoop and a JRE. As these are not Python frameworks, you will have to check what the appropriate procedure is for your operating system. I used ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Python Machine Learning Cookbook - Second Edition

Python Machine Learning Cookbook - Second Edition

Giuseppe Ciaburro, Prateek Joshi
Python: End-to-end Data Analysis

Python: End-to-end Data Analysis

Phuong Vothihong, Martin Czygan, Ivan Idris, Magnus Vilhelm Persson, Luiz Felipe Martins
Python Data Science Essentials - Third Edition

Python Data Science Essentials - Third Edition

Alberto Boschetti, Luca Massaron, Pietro Marinelli, Matteo Malosetti

Publisher Resources

ISBN: 9781785282287Supplemental Content