Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
Fast Data Processing with Spark 2

You're reading from   Fast Data Processing with Spark 2 Accelerate your data for rapid insight

Arrow left icon
Product type Paperback
Published in Oct 2016
Publisher Packt
ISBN-13 9781785889271
Length 274 pages
Edition 3rd Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Krishna Sankar Krishna Sankar
Author Profile Icon Krishna Sankar
Krishna Sankar
 Karau Karau
Author Profile Icon Karau
Karau
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Fast Data Processing with Spark 2 Third Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Installing Spark and Setting Up Your Cluster FREE CHAPTER 2. Using the Spark Shell 3. Building and Running a Spark Application 4. Creating a SparkSession Object 5. Loading and Saving Data in Spark 6. Manipulating Your RDD 7. Spark 2.0 Concepts 8. Spark SQL 9. Foundations of Datasets/DataFrames – The Proverbial Workhorse for DataScientists 10. Spark with Big Data 11. Machine Learning with Spark ML Pipelines 12. GraphX

Dataset APIs - an overview


Before we delve into Datasets and data wrangling, let's take a broader view of the APIs; we will focus on the relevant functions we need. This will give us a firm foundation when we wrangle with data later in this chapter. Refer to the following diagram:

The preceding diagram shows the broader hierarchy of the org.apache.spark.sql classes. Interestingly, pyspark.sql mirrors this hierarchy, except for DataFrame, which is basically the Scala Dataset. What I like about the PySpark interface is that it is very succinct and crisp, offering the same power, performance, and functionality as Scala or Java. But Scala has more elaborate hierarchies and more abstractions. One of the tricks to learn more about its functions is to refer to the Scala documentation, which I found to be a lot more detailed.

Each of these classes is rich with a lot of functions. The diagram shows only the most common ones we need in this chapter. You should refer to either https://spark.apache...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime
Visually different images