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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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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)

Summary

In this chapter, we discussed the various bulk operations Elasticsearch supports. You also learned about Reindex and Shrink APIs, which can be used to the change the index configuration, such as the number of shards, mapping of an existing index and so on without re-indexing the data.

We covered how to organize your data in Elasticsearch using aliases and index templates. We discussed how to use ingest node to pre-process your data before indexing into Elasticsearch. You learned how to use ingest node to transform unstructured log data into JSON documents and automatically index them into a month-based index.

In the next chapter, we will discuss different ways of querying Elasticsearch.

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