You're viewing version 2.2 of the OpenSearch documentation. This version is no longer maintained. For the latest version, see the current documentation. For information about OpenSearch version maintenance, see Release Schedule and Maintenance Policy.

Query and filter context

Queries consist of query clauses, which can be run in a filter context or query context. A query clause in a filter context asks the question “Does the document match the query clause?” and returns matching documents. A query clause in a query context asks the question “How well does the document match the query clause?”, returns matching documents, and provides the relevance of each document in the form of a relevance score.

Relevance score

A relevance score measures how well a document matches a query. It is a positive floating-point number that OpenSearch records in the _score metadata field for each document:

"hits" : [
      {
        "_index" : "shakespeare",
        "_id" : "32437",
        "_score" : 18.781435,
        "_source" : {
          "type" : "line",
          "line_id" : 32438,
          "play_name" : "Hamlet",
          "speech_number" : 3,
          "line_number" : "1.1.3",
          "speaker" : "BERNARDO",
          "text_entry" : "Long live the king!"
        }
      },
...

A higher score indicates a more relevant document. While different query types calculate relevance scores differently, all query types take into account whether a query clause is run in a filter or query context.

Use query clauses that you want to affect the relevance score in a query context, and use all other query clauses in a filter context.

Filter context

A query clause in a filter context asks the question “Does the document match the query clause?”, which has a binary answer. For example, if you have an index with student data, you might use a filter context to answer the following questions about a student:

• Is the student’s honors status set to true?
• Is the student’s graduation_year in the 2020–2022 range?

With a filter context, OpenSearch returns matching documents without calculating a relevance score. Thus, you should use a filter context for fields with exact values.

To run a query clause in a filter context, pass it to a filter parameter. For example, the following Boolean query searches for students who graduated with honors in 2020–2022:

GET students/_search
{
  "query": { 
    "bool": { 
      "filter": [ 
        { "term":  { "honors": true }},
        { "range": { "graduation_year": { "gte": 2020, "lte": 2022 }}}
      ]
    }
  }
}

To improve performance, OpenSearch caches frequently used filters.

Query context

A query clause in a query context asks the question “How well does the document match the query clause?”, which does not have a binary answer. A query context is suitable for a full-text search, where you not only want to receive matching documents but also to determine the relevance of each document. For example, if you have an index with the complete works of Shakespeare, you might use a query context for the following searches:

• Find documents that contain the word dream, including its various forms (dreaming or dreams) and synonyms (contemplate).
• Find documents that match the words long live king.

With a query context, every matching document contains a relevance score in the _score field, which you can use to sort documents by relevance.

To run a query clause in a query context, pass it to a query parameter. For example, the following query searches for documents that match the words long live king in the shakespeare index:

GET shakespeare/_search
{
  "query": {
    "match": {
      "text_entry": "long live king"
    }
  }
}

Relevance scores are single-precision floating-point numbers with 24-bit significand precision. A loss of precision may occur if a score calculation exceeds the significand precision.