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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)

Bulk operations

In this section, we will discuss various bulk operations Elasticsearch supports. Batching multiple requests together saves network round trips, and the requests in the batch can be executed in parallel. Elasticsearch has a dedicated thread pool for bulk operations, and the number of requests it can process in parallel depends on the number of the CPU processors in the node.

The following are the different bulk operations supported:

  • Bulk API: This can be used to batch multiple index and delete operations and execute them using a single API call.
  • Multi Get API: This can be used to retrieve documents using document IDs.
  • Update by query: This can be used to update a set of documents that match a query.
  • Delete by query: This can be used to delete the documents that match a query.
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