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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

Custom analyzers

Elasticsearch gives you a way to customize your analyzer. The first step is to define the analyzer and then use it in the mappings. You must define the analyzer in the index settings. You can then define your analyzer either in an index or in an index template for multiple indices that match the index pattern. Recall that an analyzer must only have one tokenizer and, optionally, many character filters and token filters. Let's create a custom analyzer to extract the tokens that we will use in the next chapter, which contain the following components:

  • tokenizer: Use the char_group tokenizer to have separators such as whitespace, digit, punctuation except for hyphens, end-of-line, symbols, and more.
  • token filter: Use the pattern_replace, lowercase, stemmer, stop, length, and unique filters.

Since the description text will be indexed differently, we need to...

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