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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)

Caching

In Elasticsearch 5.0, a lot of refactoring has been done to support better caching. The different types of cache available are as follows:

  • Node Query cache: Queries that run in filter context are cached here
  • Shard request cache: The results of the entire query are cached here

Node Query cache

Queries, such as numeric or date range, which run in the filter context are great candidates for caching. Since they have no scoring phase, they can be reused. The Node query cache is a smart cache; you do not have to worry about invalidating the cache. Individual queries that run in filter context are cached here. This cache is maintained at a node level and defaults to 10% of the heap and can be configured using the elasticsearch...

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