Relevance scoresedit

By default, Elasticsearch sorts matching search results by relevance score, which measures how well each document matches a query.

The relevance score is a positive floating point number, returned in the _score metadata field of the search API. The higher the _score, the more relevant the document. While each query type can calculate relevance scores differently, score calculation also depends on whether the query clause is run in a query or filter context.

Query contextedit

In the query context, a query clause answers the question “How well does this document match this query clause?” Besides deciding whether or not the document matches, the query clause also calculates a relevance score in the _score metadata field.

Query context is in effect whenever a query clause is passed to a query parameter, such as the query parameter in the search API.

Filter contextedit

In a filter context, a query clause answers the question “Does this document match this query clause?” The answer is a simple Yes or No — no scores are calculated. Filter context is mostly used for filtering structured data, e.g.

Frequently used filters will be cached automatically by Elasticsearch, to speed up performance.

Filter context is in effect whenever a query clause is passed to a filter parameter, such as the filter or must_not parameters in the bool query, the filter parameter in the constant_score query, or the filter aggregation.

Example of query and filter contextsedit

Below is an example of query clauses being used in query and filter context in the search API. This query will match documents where all of the following conditions are met:

GET /_search
{
  "query": { 
    "bool": { 
      "must": [
        { "match": { "title":   "Search"        }},
        { "match": { "content": "Elasticsearch" }}
      ],
      "filter": [ 
        { "term":  { "status": "published" }},
        { "range": { "publish_date": { "gte": "2015-01-01" }}}
      ]
    }
  }
}