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Advanced Elasticsearch 7.0

You're reading from  Advanced Elasticsearch 7.0

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781789957754
Pages 560 pages
Edition 1st Edition
Languages
Author (1):
Wai Tak Wong Wai Tak Wong
Profile icon Wai Tak Wong

Table of Contents (25) Chapters

Preface Section 1: Fundamentals and Core APIs
Overview of Elasticsearch 7 Index APIs Document APIs Mapping APIs Anatomy of an Analyzer Search APIs Section 2: Data Modeling, Aggregations Framework, Pipeline, and Data Analytics
Modeling Your Data in the Real World Aggregation Frameworks Preprocessing Documents in Ingest Pipelines Using Elasticsearch for Exploratory Data Analysis Section 3: Programming with the Elasticsearch Client
Elasticsearch from Java Programming Elasticsearch from Python Programming Section 4: Elastic Stack
Using Kibana, Logstash, and Beats Working with Elasticsearch SQL Working with Elasticsearch Analysis Plugins Section 5: Advanced Features
Machine Learning with Elasticsearch Spark and Elasticsearch for Real-Time Analytics Building Analytics RESTful Services Other Books You May Enjoy

Summary

Excellent! We have enjoyed learning about document APIs including how to store, retrieve, and manage documents in document-oriented Elasticsearch. We have delved into the document life cycle, and then we practiced the single document and multi-document APIs. Finally, we also completed the index rebuilding example for migrating indices from old versions to version 7.0.

In Chapter 4, Mapping APIs, we will drill down to the mapping APIs. A mapping in Elasticsearch is a description of how documents and their fields are stored and indexed. Although dynamic mapping is provided during indexing if you do not provide the mapping explicitly, in most cases you will still need to have your overall mapping designed properly for your search engine database. We will learn how and when to specify a custom mapping.

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