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Learning Apache Spark 2

You're reading from  Learning Apache Spark 2

Product type Book
Published in Mar 2017
Publisher Packt
ISBN-13 9781785885136
Pages 356 pages
Edition 1st Edition
Languages
Concepts

Table of Contents (18) Chapters

Learning Apache Spark 2
Credits
About the Author
About the Reviewers
www.packtpub.com
Customer Feedback
Preface
1. Architecture and Installation 2. Transformations and Actions with Spark RDDs 3. ETL with Spark 4. Spark SQL 5. Spark Streaming 6. Machine Learning with Spark 7. GraphX 8. Operating in Clustered Mode 9. Building a Recommendation System 10. Customer Churn Prediction 1. Theres More with Spark

Structured Data sources and Databases

Spark works with a variety of structured data sources including, but not limited to, the following:

  1. Parquet Files: Apache Parquet is a columnar storage format. More details about the structure of Parquet and how spark makes use of it is available in the Spark SQL chapter.
  2. Hive tables.
  3. JDBC: Spark allows the use of JDBC to connect to a wide variety of databases. Of course the data access via JDBC is relatively slow compared to native database utilities.

We'll cover most of the structured sources in Chapter 4, Spark SQL later in this book.

Working with NoSQL Databases

A NoSQL (originally referring to non SQL, non relational or not only SQL) database provides a mechanism for storage (https://en.wikipedia.org/wiki/Computer_data_storage) and retrieval (https://en.wikipedia.org/wiki/Data_retrieval) of data which is modeled in means other than the tabular relations used in Relational databases (https://en.wikipedia.org/wiki/Relational_database). NoSQL is a relatively...

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