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Mastering Elasticsearch 5.x

You're reading from   Mastering Elasticsearch 5.x Master the intricacies of Elasticsearch 5 and use it to create flexible and scalable search solutions

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786460189
Length 428 pages
Edition 3rd Edition
Languages
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Author (1):
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Bharvi Dixit Bharvi Dixit
Author Profile Icon Bharvi Dixit
Bharvi Dixit
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Toc

Table of Contents (13) Chapters Close

Preface 1. Revisiting Elasticsearch and the Changes 2. The Improved Query DSL FREE CHAPTER 3. Beyond Full Text Search 4. Data Modeling and Analytics 5. Improving the User Search Experience 6. The Index Distribution Architecture 7. Low-Level Index Control 8. Elasticsearch Administration 9. Data Transformation and Federated Search 10. Improving Performance 11. Developing Elasticsearch Plugins 12. Introducing Elastic Stack 5.0

Structure of the rescore query


Let's now modify our query so that it uses the rescore functionality. Basically, let's assume that we want the score of the document to be equal to the value of the year field. The query that does that would look as follows:

{ 
  "query": { 
    "match_all": {} 
  }, 
  "rescore": { 
    "query": { 
      "rescore_query": { 
        "function_score": { 
          "query": { 
            "match_all": {} 
          }, 
          "script_score": { 
            "script": { 
              "inline": "doc['year'].value", 
              "lang": "painless" 
            } 
          } 
        } 
      } 
    } 
  } 
  "_source": ["title", "available"] 
} 

Let's now look at the preceding query in more detail. The first thing you may have noticed is the rescore object. The mentioned object holds the query that will affect the scoring of the documents returned by the query. In our case, the logic is very simple, we just assign the value of the year field as the score of...

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