In this chapter, we'll spend some time talking about SparkSQL. This is becoming an increasingly important part of Spark; it basically lets you deal with structured data formats. This means that instead of the RDDs that contain arbitrary information in every row, we're going to give the rows some structure. This will let us do a lot of different things, such as treat our RDDs as little databases. So, we're going to call them DataFrames and DataSets from now on, and you can actually perform SQL queries and SQL-like operations on them, which can be pretty powerful.
Frank Kane's Taming Big Data with Apache Spark and Python
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Frank Kane's Taming Big Data with Apache Spark and Python
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Overview of this book
Frank Kane’s Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you’ll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python.
Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses.
Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease.
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Current Title:
Frank Kane's Taming Big Data with Apache Spark and Python
Table of Contents (13 chapters)
Title Page
Credits
About the Author
www.PacktPub.com
Customer Feedback
Preface
Free Chapter
Getting Started with Spark
Spark Basics and Spark Examples
Advanced Examples of Spark Programs
Running Spark on a Cluster
SparkSQL, DataFrames, and DataSets
Other Spark Technologies and Libraries
Where to Go From Here? – Learning More About Spark and Data Science
Customer Reviews