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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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Toc

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

Summary

Incredible! We have completed Python programming with Elasticsearch, and this chapter marks the end of Section 4 of this book. We learned about the different programming styles between the low-level client and the high-level library. We also tried to implement Bollinger Bands by using the high-level library and we discovered that the moving_fn aggregation type was not supported. Indeed, we can use the low-level client in case any method is missing from (or not supported in) the high-level library.

In the next chapter, we will start with Section 5, Elastic Stack. We will present an overview of the other components of Elastic Stack: Kibana, Logstash, and Beats. We will also learn some practical examples from an examination of some very basic usage of Kibana, Elasticsearch, Filebeat, and Logstash.

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