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ElasticSearch Blueprints

You're reading from  ElasticSearch Blueprints

Product type Book
Published in Jul 2015
Publisher Packt
ISBN-13 9781783984923
Pages 192 pages
Edition 1st Edition
Languages

Table of Contents (15) Chapters

Elasticsearch Blueprints
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. Google-like Web Search 2. Building Your Own E-Commerce Solution 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

The product-with-tags search problem


A new requirement came into existence to search for products that have a specific attribute value set.

As in, the user should be able to search for a particular product based on any of its attributes. However, these attributes are not fixed and might change on a daily basis. Hence, it's not possible to keep this as a key-value pair. More keys mean more fields and each field costs Lucene a reverse index under the hood. So, a better approach would be to model the data as follows:

/products/product/LCD_TV

{
  "name" : "LCD TV",
  "tags" : [
    {
      "tagName" : "company" ,
      "value" : "Sony"
    },
    {
      "tagName" : "competitor" ,
      "value" : "Toshiba"
    }
  ]
}

With this approach, everything looks good, but then, the following query works true for the preceding document:

tags.tagName:company AND tags.value:Toshiba

This is not what we expected. The product actually belongs to the company Sony, but then, it matched against the company Toshiba...

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