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Learning Elasticsearch

You're reading from   Learning Elasticsearch Structured and unstructured data using distributed real-time search and analytics

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787128453
Length 404 pages
Edition 1st Edition
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Author (1):
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Abhishek Andhavarapu Abhishek Andhavarapu
Author Profile Icon Abhishek Andhavarapu
Abhishek Andhavarapu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Elasticsearch FREE CHAPTER 2. Setting Up Elasticsearch and Kibana 3. Modeling Your Data and Document Relations 4. Indexing and Updating Your Data 5. Organizing Your Data and Bulk Data Ingestion 6. All About Search 7. More Than a Search Engine (Geofilters, Autocomplete, and More) 8. How to Slice and Dice Your Data Using Aggregations 9. Production and Beyond 10. Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Modeling Your Data and Document Relations

In the previous chapter, we learned how to set up and configure Elasticsearch. Once the cluster is up and running, you can start indexing your data. Elasticsearch will automatically figure out the schema of the documents when you index, which works great for getting started. But for all practical purposes, you have to tell Elasticsearch the schema of your data to avoid any surprises. Modeling your data is one of the most important steps before using Elasticsearch. In this chapter, you’ll learn how to model your data and handle relations between different document types. In this chapter, we will cover the following:

  • Configure mappings
  • Dynamic mapping
  • Core data types
  • Complex data types
  • Geo location
  • Modeling relations in Elasticsearch
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