mapped_pages:
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.
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.
A filter answers the binary question “Does this document match this query clause?”. The answer is simply "yes" or "no". Filtering has several benefits:
Filters are particularly effective for querying structured data and implementing "must have" criteria in complex searches.
Structured data refers to information that is highly organized and formatted in a predefined manner. In the context of Elasticsearch, this typically includes:
Unlike full-text fields, structured data has a consistent, predictable format, making it ideal for precise filtering operations.
Common filter applications include:
timestamp
field between 2015 and 2016status
field equal to "published" or is the author
field equal to "John Doe"Filter context applies when a query clause is passed to a filter
parameter, such as:
filter
or must_not
parameters in bool
queriesfilter
parameter in constant_score
queriesfilter
aggregationsFilters optimize query performance and efficiency, especially for structured data queries and when combined with full-text searches.
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:
title
field contains the word search
.content
field contains the word elasticsearch
.status
field contains the exact word published
.The publish_date
field contains a date from 1 Jan 2015 onwards.
GET /_search
{
"query": { <1>
"bool": { <2>
"must": [
{ "match": { "title": "Search" }},
{ "match": { "content": "Elasticsearch" }}
],
"filter": [ <3>
{ "term": { "status": "published" }},
{ "range": { "publish_date": { "gte": "2015-01-01" }}}
]
}
}
}
query
parameter indicates query context.bool
and two match
clauses are used in query context, which means that they are used to score how well each document matches.filter
parameter indicates filter context. Its term
and range
clauses are used in filter context. They will filter out documents which do not match, but they will not affect the score for matching documents.::::{warning} Scores calculated for queries in query context are represented as single precision floating point numbers; they have only 24 bits for significand’s precision. Score calculations that exceed the significand’s precision will be converted to floats with loss of precision. ::::
::::{tip} Use query clauses in query context for conditions which should affect the score of matching documents (i.e. how well does the document match), and use all other query clauses in filter context. ::::