Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Scala Data Analysis Cookbook (new)
Scala Data Analysis Cookbook (new)

Scala Data Analysis Cookbook (new): Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes

eBook
€20.98 €29.99
Paperback
€36.99
Subscription
Free Trial
Renews at €18.99p/m

What do you get with a Packt Subscription?

Free for first 7 days. €18.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing
Table of content icon View table of contents Preview book icon Preview Book

Scala Data Analysis Cookbook (new)

Chapter 2. Getting Started with Apache Spark DataFrames

In this chapter, we will cover the following recipes:

  • Getting Apache Spark
  • Creating a DataFrame from CSV
  • Manipulating DataFrames
  • Creating a DataFrame from Scala case classes

Introduction

Apache Spark is a cluster computing platform that claims to run about 10 times faster than Hadoop. In general terms, we could consider it as a means to run our complex logic over massive amounts of data at a blazingly fast speed. The other good thing about Spark is that the programs that we write are much smaller than the typical MapReduce classes that we write for Hadoop. So, not only do our programs run faster but it also takes less time to write them.

Spark has four major higher level tools built on top of the Spark Core: Spark Streaming, Spark MLlib (machine learning), Spark SQL (an SQL interface for accessing the data), and GraphX (for graph processing). The Spark Core is the heart of Spark. Spark provides higher level abstractions in Scala, Java, and Python for data representation, serialization, scheduling, metrics, and so on.

At the risk of stating the obvious, a DataFrame is one of the primary data structures used in data analysis. They are just like an RDBMS table...

Getting Apache Spark

In this recipe, we'll take a look at how to bring Spark into our project (using SBT) and how Spark works internally.

How to do it...

Let's now throw some Spark dependencies into our build.sbt file so that we can start playing with them in subsequent recipes. For now, we'll just focus on three of them: Spark Core, Spark SQL, and Spark MLlib. We'll take a look at a host of other Spark dependencies as we proceed further in this book:

  1. Under a brand new folder (which will be your project root), create a new file called build.sbt.
  2. Next, let's add the Spark libraries to the project dependencies.
  3. Note that Spark 1.4.x requires Scala 2.10.x. This becomes the first section of our build.sbt:
    organization := "com.packt"
    
    name := "chapter1-spark-csv"
    
    scalaVersion := "2.10.4"
    
    val sparkVersion=...

Creating a DataFrame from CSV

In this recipe, we'll look at how to create a new DataFrame from a delimiter-separated values file.

How to do it...

This recipe involves four steps:

  1. Add the spark-csv support to our project.
  2. Create a Spark Config object that gives information on the environment that we are running Spark in.
  3. Create a Spark context that serves as an entry point into Spark. Then, we proceed to create an SQLContext from the Spark context.
  4. Load the CSV using the SQLContext.
  5. CSV support isn't first-class in Spark, but it is available through an external library from Databricks. So, let's go ahead and add that to our build.sbt.

    After adding the spark-csv dependency, our complete build.sbt looks like this:

    organization := "com.packt"
    
    name := "chapter1-spark-csv"
    
    scalaVersion...

Manipulating DataFrames

In the previous recipe, we saw how to create a DataFrame. The next natural step, after creating DataFrames, is to play with the data inside them. Other than the numerous functions that help us to do that, we also find other interesting functions that help us sample the data, print the schema of the data, and so on. We'll take a look at them one by one in this recipe.

How to do it...

Now, let's see how we can manipulate DataFrames using the following subrecipes:

  • Printing the schema of the DataFrame
  • Sampling data in the DataFrame
  • Selecting specific columns in the DataFrame
  • Filtering data by condition
  • Sorting data in the frame
  • Renaming columns
  • Treating the DataFrame as a relational table to execute SQL queries
  • Saving the DataFrame as a file

Printing the schema...

Creating a DataFrame from Scala case classes

In this recipe, we'll see how to create a new DataFrame from Scala case classes.

How to do it...

  1. We create a new entity called Employee with the id and name fields, like this:
    case class Employee(id:Int, name:String)
    

    Similar to the previous recipe, we create SparkContext and SQLContext.

    val conf = new SparkConf().setAppName("colRowDataFrame").setMaster("local[2]")
    
    //Initialize Spark context with Spark configuration.  This is the core entry point to do anything with Spark
    val sc = new SparkContext(conf)
    
    //The easiest way to query data in Spark is to use SQL queries.
    val sqlContext=new SQLContext(sc)
    
  2. We can source these employee objects from a variety of sources, such as an RDBMS data source, but for the sake of this example...
Left arrow icon Right arrow icon

Key benefits

  • • Implement Scala in your data analysis using features from Spark, Breeze, and Zeppelin
  • • Scale up your data anlytics infrastructure with practical recipes for Scala machine learning
  • • Recipes for every stage of the data analysis process, from reading and collecting data to distributed analytics

Description

This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you’ll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX.

Who is this book for?

This book shows data scientists and analysts how to leverage their existing knowledge of Scala for quality and scalable data analysis

What you will learn

  • • Familiarize and set up the Breeze and Spark libraries and use data structures
  • • Import data from a host of possible sources and create dataframes from CSV
  • • Clean, validate and transform data using Scala to pre-process numerical and string data
  • • Integrate quintessential machine learning algorithms using Scala stack
  • • Bundle and scale up Spark jobs by deploying them into a variety of cluster managers
  • • Run streaming and graph analytics in Spark to visualize data, enabling exploratory analysis

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 30, 2015
Length: 254 pages
Edition : 1st
Language : English
ISBN-13 : 9781784396749
Vendor :
EPFL
Category :
Languages :
Concepts :

What do you get with a Packt Subscription?

Free for first 7 days. €18.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Oct 30, 2015
Length: 254 pages
Edition : 1st
Language : English
ISBN-13 : 9781784396749
Vendor :
EPFL
Category :
Languages :
Concepts :

Packt Subscriptions

See our plans and pricing
Modal Close icon
€18.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
€189.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts
€264.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total 133.97
Scala for Machine Learning
€49.99
Scala Data Analysis Cookbook (new)
€36.99
Scala for Data Science
€46.99
Total 133.97 Stars icon
Banner background image

Table of Contents

8 Chapters
1. Getting Started with Breeze Chevron down icon Chevron up icon
2. Getting Started with Apache Spark DataFrames Chevron down icon Chevron up icon
3. Loading and Preparing Data – DataFrame Chevron down icon Chevron up icon
4. Data Visualization Chevron down icon Chevron up icon
5. Learning from Data Chevron down icon Chevron up icon
6. Scaling Up Chevron down icon Chevron up icon
7. Going Further Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
(3 Ratings)
5 star 0%
4 star 100%
3 star 0%
2 star 0%
1 star 0%
satish Dec 25, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
The Author has done an excellent job!
Amazon Verified review Amazon
Yuvaraj SV Dec 25, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I found the book filled with very useful and practical examples on usage of Spark. The Machine Learning and the Scaling up chapter are pretty detailed. Loved it !
Amazon Verified review Amazon
JaY Dec 25, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Very useful
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.