Is a type of training that duplicates the exact combination of conditions that occur on the job

A query that matches documents matching boolean combinations of other queries. The bool query maps to Lucene BooleanQuery. It is built using one or more boolean clauses, each clause with a typed occurrence. The occurrence types are:

The bool query takes a more-matches-is-better approach, so the score from each matching must or should clause will be added together to provide the final _score for each document.

POST _search { "query": { "bool" : { "must" : { "term" : { "user.id" : "kimchy" } }, "filter": { "term" : { "tags" : "production" } }, "must_not" : { "range" : { "age" : { "gte" : 10, "lte" : 20 } } }, "should" : [ { "term" : { "tags" : "env1" } }, { "term" : { "tags" : "deployed" } } ], "minimum_should_match" : 1, "boost" : 1.0 } } }

Using minimum_should_matchedit

You can use the minimum_should_match parameter to specify the number or percentage of should clauses returned documents must match.

If the bool query includes at least one should clause and no must or filter clauses, the default value is 1. Otherwise, the default value is 0.

For other valid values, see the minimum_should_match parameter.

Scoring with bool.filteredit

Queries specified under the filter element have no effect on scoring — scores are returned as 0. Scores are only affected by the query that has been specified. For instance, all three of the following queries return all documents where the status field contains the term active.

This first query assigns a score of 0 to all documents, as no scoring query has been specified:

$params = [ 'body' => [ 'query' => [ 'bool' => [ 'filter' => [ 'term' => [ 'status' => 'active', ], ], ], ], ], ]; $response = $client->search($params);

var searchResponse = client.Search<Blog>(s => s .AllIndices() .Query(q => +q.Term(p => p.Status, PublishStatus.Active)) );

resp = client.search( body={"query": {"bool": {"filter": {"term": {"status": "active"}}}}}, ) print(resp)

response = client.search( body: { query: { bool: { filter: { term: { status: 'active' } } } } } ) puts response

res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "query": { "bool": { "filter": { "term": { "status": "active" } } } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)

const response = await client.search({ body: { query: { bool: { filter: { term: { status: 'active' } } } } } }) console.log(response)

GET _search { "query": { "bool": { "filter": { "term": { "status": "active" } } } } }

This bool query has a match_all query, which assigns a score of 1.0 to all documents.

$params = [ 'body' => [ 'query' => [ 'bool' => [ 'must' => [ 'match_all' => [ ], ], 'filter' => [ 'term' => [ 'status' => 'active', ], ], ], ], ], ]; $response = $client->search($params);

var searchResponse = client.Search<Blog>(s => s .AllIndices() .Query(q => +q.Term(p => p.Status, PublishStatus.Active) && q.MatchAll() ) );

resp = client.search( body={ "query": { "bool": { "must": {"match_all": {}}, "filter": {"term": {"status": "active"}}, } } }, ) print(resp)

response = client.search( body: { query: { bool: { must: { match_all: { } }, filter: { term: { status: 'active' } } } } } ) puts response

res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "query": { "bool": { "must": { "match_all": {} }, "filter": { "term": { "status": "active" } } } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)

const response = await client.search({ body: { query: { bool: { must: { match_all: {} }, filter: { term: { status: 'active' } } } } } }) console.log(response)

GET _search { "query": { "bool": { "must": { "match_all": {} }, "filter": { "term": { "status": "active" } } } } }

This constant_score query behaves in exactly the same way as the second example above. The constant_score query assigns a score of 1.0 to all documents matched by the filter.

$params = [ 'body' => [ 'query' => [ 'constant_score' => [ 'filter' => [ 'term' => [ 'status' => 'active', ], ], ], ], ], ]; $response = $client->search($params);

var searchResponse = client.Search<Blog>(s => s .AllIndices() .Query(q => q.ConstantScore(cs => cs .Filter(f => f .Term(p => p.Status, PublishStatus.Active) ) ) ) );

resp = client.search( body={ "query": { "constant_score": {"filter": {"term": {"status": "active"}}} } }, ) print(resp)

response = client.search( body: { query: { constant_score: { filter: { term: { status: 'active' } } } } } ) puts response

res, err := es.Search( es.Search.WithBody(strings.NewReader(`{ "query": { "constant_score": { "filter": { "term": { "status": "active" } } } } }`)), es.Search.WithPretty(), ) fmt.Println(res, err)

const response = await client.search({ body: { query: { constant_score: { filter: { term: { status: 'active' } } } } } }) console.log(response)

GET _search { "query": { "constant_score": { "filter": { "term": { "status": "active" } } } } }

Each query accepts a _name in its top level definition. You can use named queries to track which queries matched returned documents. If named queries are used, the response includes a matched_queries property for each hit.

GET /_search { "query": { "bool": { "should": [ { "match": { "name.first": { "query": "shay", "_name": "first" } } }, { "match": { "name.last": { "query": "banon", "_name": "last" } } } ], "filter": { "terms": { "name.last": [ "banon", "kimchy" ], "_name": "test" } } } } }

This functionality reruns each named query on every hit in a search response. Typically, this adds a small overhead to a request. However, using computationally expensive named queries on a large number of hits may add significant overhead. For example, named queries in combination with a top_hits aggregation on many buckets may lead to longer response times.

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