Boolean query
Boolean query
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:
Occur | Description |
---|---|
| The clause (query) must appear in matching documents and will contribute to the score. |
| The clause (query) must appear in matching documents. However unlike |
| The clause (query) should appear in the matching document. |
| The clause (query) must not appear in the matching documents. Clauses are executed in filter context meaning that scoring is ignored and clauses are considered for caching. Because scoring is ignored, a score of |
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.
resp = client.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
}
},
)
print(resp)
response = client.search(
body: {
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
}
}
}
)
puts response
const response = await client.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,
},
},
});
console.log(response);
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_match
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.filter
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);
resp = client.search(
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({
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);
resp = client.search(
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({
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);
resp = client.search(
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({
query: {
constant_score: {
filter: {
term: {
status: "active",
},
},
},
},
});
console.log(response);
GET _search
{
"query": {
"constant_score": {
"filter": {
"term": {
"status": "active"
}
}
}
}
}
Named queries
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.
Supplying duplicate _name
values in the same request results in undefined behavior. Queries with duplicate names may overwrite each other. Query names are assumed to be unique within a single request.
resp = client.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"
}
}
}
},
)
print(resp)
response = client.search(
body: {
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'
}
}
}
}
}
)
puts response
const response = await client.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",
},
},
},
},
});
console.log(response);
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"
}
}
}
}
}
The request parameter named include_named_queries_score
controls whether scores associated with the matched queries are returned or not. When set, the response includes a matched_queries
map that contains the name of the query that matched as a key and its associated score as the value.
Note that the score might not have contributed to the final score of the document, for instance named queries that appear in a filter or must_not contexts, or inside a clause that ignores or modifies the score like constant_score
or function_score_query
.
resp = client.search(
include_named_queries_score=True,
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"
}
}
}
},
)
print(resp)
response = client.search(
include_named_queries_score: true,
body: {
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'
}
}
}
}
}
)
puts response
const response = await client.search({
include_named_queries_score: "true",
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",
},
},
},
},
});
console.log(response);
GET /_search?include_named_queries_score
{
"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.