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Elasticsearch Essentials

You're reading from   Elasticsearch Essentials Harness the power of ElasticSearch to build and manage scalable search and analytics solutions with this fast-paced guide

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781784391010
Length 240 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started with Elasticsearch FREE CHAPTER 2. Understanding Document Analysis and Creating Mappings 3. Putting Elasticsearch into Action 4. Aggregations for Analytics 5. Data Looks Better on Maps: Master Geo-Spatiality 6. Document Relationships in NoSQL World 7. Different Methods of Search and Bulk Operations 8. Controlling Relevancy 9. Cluster Scaling in Production Deployments 10. Backups and Security Index

Data pagination


We have seen that for any query, Elasticsearch by default returns only the top 10 documents after scoring and sorting them. However, they are not always enough to serve the purpose. A user always needs more and more data either to render on a page or to process in the backend. Let's see how we can do this.

Pagination with scoring

In the previous chapters, we discussed how Elasticsearch offers the from and to parameters to be passed with search requests. So, you always have an option to either increase the size parameter to load more results from Elasticsearch or send another query with the changed from and size values to get more data.

This pagination approach makes sense when you have to fetch a limited number of documents from Elasticsearch. As this approach is too costly and can kill Elasticsearch if you are hitting a request, for example, where from = 100000 and size = 100010 to get 10 documents, which have less score than those 1 lac documents in the index.

Pagination without...

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