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Advanced Elasticsearch 7.0

You're reading from   Advanced Elasticsearch 7.0 A practical guide to designing, indexing, and querying advanced distributed search engines

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781789957754
Length 560 pages
Edition 1st Edition
Languages
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Author (1):
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Wai Tak Wong Wai Tak Wong
Author Profile Icon Wai Tak Wong
Wai Tak Wong
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Table of Contents (25) Chapters Close

Preface 1. Section 1: Fundamentals and Core APIs FREE CHAPTER
2. Overview of Elasticsearch 7 3. Index APIs 4. Document APIs 5. Mapping APIs 6. Anatomy of an Analyzer 7. Search APIs 8. Section 2: Data Modeling, Aggregations Framework, Pipeline, and Data Analytics
9. Modeling Your Data in the Real World 10. Aggregation Frameworks 11. Preprocessing Documents in Ingest Pipelines 12. Using Elasticsearch for Exploratory Data Analysis 13. Section 3: Programming with the Elasticsearch Client
14. Elasticsearch from Java Programming 15. Elasticsearch from Python Programming 16. Section 4: Elastic Stack
17. Using Kibana, Logstash, and Beats 18. Working with Elasticsearch SQL 19. Working with Elasticsearch Analysis Plugins 20. Section 5: Advanced Features
21. Machine Learning with Elasticsearch 22. Spark and Elasticsearch for Real-Time Analytics 23. Building Analytics RESTful Services 24. Other Books You May Enjoy

Modeling Your Data in the Real World

In the previous chapter, we have discussed different aspects of search APIs. We started from using a simple URI search and request body search. We investigated the Query DSL to learn how to write high-quality queries. We practiced troubleshooting techniques with the Profile API, the Validate API, the Explain API, and completion suggested and completed a detailed example of search-as-you-type feature. Since we know how to search now, we need to step back and think about the design of data modeling. In this chapter, we will discuss data modeling when using Elasticsearch.

Elasticsearch is a distributed, document-oriented NoSQL database for storing, retrieving, and managing document-oriented or semi-structured data. Basically, a document is stored with minimal support for relationships between documents. This chapter focuses on some of most common...

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