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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
Languages
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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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Toc

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

Sourcing data using Spark

Spark provides a mechanism to work with a variety of data sources and formats. It also has excellent support for integrating with the Hadoop Distributed File System (HDFS), as well as several other popular storage systems, such as Amazon S3. In this section, we will focus on the variety of data sources and formats supported by Spark.

Parquet file format

Apache Parquet (https://parquet.apache.org/) is an open source project and defines the specifications of a columnar data storage format. This storage format is extremely popular in the big data world for the following reasons:

  • It supports nested data structures, which is good because most real-world data fits more naturally into a nested structure...
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