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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)

Organizing your data

In this section, we will discuss how to divide your data into multiple indices. Elasticsearch provides index aliases, which make it very easy to query multiple indices at once. It also supports index templates to configure automatic index creation. We will also discuss how to deal with time-based data, such as logs, which is a common Elasticsearch use case.

Index alias

An index alias is a pointer to one or more indexes. A search operation executed against an alias is executed across all the indexes the alias points to. The coordinating node executes the request on all indices, collects the results, and sends them back to the client. The index operation, on the other hand, cannot be executed on an alias...

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