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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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 Andhavarapu Andhavarapu
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Andhavarapu
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Toc

Table of Contents (17) Chapters Close

Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to Elasticsearch 2. Setting Up Elasticsearch and Kibana FREE CHAPTER 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)

Thread pools


Elasticsearch has a thread pool for all the major modules. Each thread pool has a queue associated with the pool. For example, if the index thread pool receives more requests than it can process, the requests are queued up. If the queue is full, the request is rejected. Watching for the number of requests in the queue is important. If the requests are frequently queued, the response times are degraded. The pool size is calculated based on the available processors. The important thread pools are as follows:

Thread pool

Description

index

This is used for index and delete operations. It has a queue size of 200.

search

This is used for search operations. It has a queue size of 1,000.

bulk

This is used for bulk operations. It has a queue size of 50.

refresh

This is used for refresh operations.

Note

Note that if the queue is full, the request is rejected with an HTTP 503 error.

You can use cat API to look at the active thread in each pool:

GET /_cat/thread_pool?v&h=name,active,queue,rejected...
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