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Hands-On Data Analysis with Scala

You're reading from   Hands-On Data Analysis with Scala Perform data collection, processing, manipulation, and visualization with Scala

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789346114
Length 298 pages
Edition 1st Edition
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Author (1):
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Rajesh Gupta Rajesh Gupta
Author Profile Icon Rajesh Gupta
Rajesh Gupta
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Rajesh is a Hands-on Big Data Tech Lead and Enterprise Architect with extensive experience in the full life cycle of software development. He has successfully architected, developed and deployed highly scalable data solutions using Spark, Scala and Hadoop technology stack for several enterprises. A passionate, hands-on technologist, Rajesh has masters degrees in Mathematics and Computer Science from BITS, Pilani (India).
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Table of Contents (14) Chapters Close

Preface 1. Section 1: Scala and Data Analysis Life Cycle FREE CHAPTER
2. Scala Overview 3. Data Analysis Life Cycle 4. Data Ingestion 5. Data Exploration and Visualization 6. Applying Statistics and Hypothesis Testing 7. Section 2: Advanced Data Analysis and Machine Learning
8. Introduction to Spark for Distributed Data Analysis 9. Traditional Machine Learning for Data Analysis 10. Section 3: Real-Time Data Analysis and Scalability
11. Near Real-Time Data Analysis Using Streaming 12. Working with Data at Scale 13. Another Book You May Enjoy

Spark Datasets and DataFrames

In the previous section, we looked at Spark's core functionality using RDDs. RDDs are powerful constructs; however, there are still some low-level details that a Spark user has to understand and master before making use of it. Spark's Datasets and DataFrame constructs provide higher level APIs for working with data.

Spark's Dataset brings a declarative style of programming along with the functional programming style of RDD. Structured Query Language (SQL) is a very popular declarative language, and is extremely popular among people who do not have a strong background in functional programming. The Spark DataFrame is a special type of dataset that provides the concepts of the row and column, as seen in the tradition relational database (RDBS) work.

Let's explore the example we used earlier using RDD. We will use the dataset and...

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Authors (1)

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Gupta
Rakesh Gupta is best known as an automation champion in the Salesforce ecosystem. He has written over 150 articles on Visual Workflow and Process Builder to show how someone can use Visual Workflow and Process Builder to minimize code usage. He is one of the Visual Workflow and Process Builder experts in the industry. He has trained more than 700 individual professionals around the globe and conducted corporate training. Currently, Rakesh is working as a Salesforce solution architect consultant.
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