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ElasticSearch Blueprints

You're reading from   ElasticSearch Blueprints A practical project-based guide to generating compelling search solutions using the dynamic and powerful features of Elasticsearch

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Product type Paperback
Published in Jul 2015
Publisher Packt
ISBN-13 9781783984923
Length 192 pages
Edition 1st Edition
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Toc

Table of Contents (10) Chapters Close

Preface 1. Google-like Web Search 2. Building Your Own E-Commerce Solution FREE CHAPTER 3. Relevancy and Scoring 4. Managing Relational Content 5. Analytics Using Elasticsearch 6. Improving the Search Experience 7. Spicing Up a Search Using Geo 8. Handling Time-based Data Index

Implementation of filters in Elasticsearch


This section sheds some light on the implementation of filters in Elasticsearch. All filters are not the same. We will see how each one differs from another and how we can implement these with Elasticsearch. First, let's see all the three implementation types of filters in Elasticsearch.

We have already showed you the most basic type of usage of a filter in the previous examples. You would have noticed the term constant score or filtered every time we used a filter. These are queries and they wrap the filter inside and apply it against the normal query's result. This is the first type of filter implementation of Elasticsearch.

Note that the filtered/constant score implementation of filters will affect both the results of the query and aggregations; some of the examples are shown as follows:

curl -XPOST 'http://localhost:9200/products/_search?pretty' -d '{
   "aggregations": {
     "department": {
       "terms": {
         "field": "color"
       ...
You have been reading a chapter from
ElasticSearch Blueprints
Published in: Jul 2015
Publisher: Packt
ISBN-13: 9781783984923
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