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Elasticsearch 5.x Cookbook

You're reading from   Elasticsearch 5.x Cookbook Distributed Search and Analytics

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Product type Paperback
Published in Feb 2017
Publisher
ISBN-13 9781786465580
Length 696 pages
Edition 3rd Edition
Languages
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Author (1):
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Alberto Paro Alberto Paro
Author Profile Icon Alberto Paro
Alberto Paro
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Table of Contents (25) Chapters Close

Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface
1. Getting Started FREE CHAPTER 2. Downloading and Setup 3. Managing Mappings 4. Basic Operations 5. Search 6. Text and Numeric Queries 7. Relationships and Geo Queries 8. Aggregations 9. Scripting 10. Managing Clusters and Nodes 11. Backup and Restore 12. User Interfaces 13. Ingest 14. Java Integration 15. Scala Integration 16. Python Integration 17. Plugin Development 18. Big Data Integration

Reading data using SparkSQL


Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can also act as distributed SQL query engine. Elasticsearch Spark integration allows us to read data via SQL queries.

Note

Spark SQL works with structured data; in other words, all entries are expected to have the same structure (the same number of fields, of the same type and name). Using unstructured data (documents with different structures) is not supported and will cause problems.

Getting ready

You need an up-and-running Elasticsearch installation as we described in the Downloading and installing Elasticsearch recipe in Chapter 2, Downloading and Setup.

You also need a working installation of Apache Spark and the data indexed in the Indexing data via Apache Spark recipe of this chapter.

How to do it...

To read data in Elasticsearch via Apache Spark SQL and via DataFrame, we will perform the steps given as follows:

  1. We need to start the Spark shell...

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