Book Image

Mastering Python Scientific Computing

Book Image

Mastering Python Scientific Computing

Overview of this book

Table of Contents (17 chapters)
Mastering Python Scientific Computing
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

A brief note about large-scale datasets


The datasets of various scientific applications range from several MB to a few GB. For some specific applications, the datasets may be huge. These gigantic datasets may span up to a couple of petabytes. We usually understand MB and GB; let's just get an idea of the scale of a petabyte. Suppose we store one petabyte of data in compact disks (CDs) and arrange these CDs in the form of a stack. The size of this stack will be approximately 1.75 kilometers. Due to recent advances in networking and distributed computing technologies, these days, there are a number of applications that process datasets of several petabytes. In order to efficiently process large-scale datasets, there are a number of options available at all levels of software or hardware.

There are several efficient frameworks for processing datasets of all scales. These frameworks can process small-, medium-, or large-scale data with equal efficiency, depending on the infrastructure provided...