Multi-match query
Multi-match query
The multi_match
query builds on the match query to allow multi-field queries:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'this is a test',
'fields' => [
'subject',
'message',
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "this is a test",
"fields": [
"subject",
"message"
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'this is a test',
fields: [
'subject',
'message'
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "this is a test",
"fields": [
"subject",
"message"
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "this is a test",
fields: ["subject", "message"],
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "this is a test",
"fields": [ "subject", "message" ]
}
}
}
The query string. | |
The fields to be queried. |
fields
and per-field boosting
Fields can be specified with wildcards, eg:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'Will Smith',
'fields' => [
'title',
'*_name',
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "Will Smith",
"fields": [
"title",
"*_name"
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'Will Smith',
fields: [
'title',
'*_name'
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "Will Smith",
"fields": [
"title",
"*_name"
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "Will Smith",
fields: ["title", "*_name"],
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "Will Smith",
"fields": [ "title", "*_name" ]
}
}
}
Query the |
Individual fields can be boosted with the caret (^
) notation:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'this is a test',
'fields' => [
'subject^3',
'message',
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "this is a test",
"fields": [
"subject^3",
"message"
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'this is a test',
fields: [
'subject^3',
'message'
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "this is a test",
"fields": [
"subject^3",
"message"
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "this is a test",
fields: ["subject^3", "message"],
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query" : "this is a test",
"fields" : [ "subject^3", "message" ]
}
}
}
The query multiplies the |
If no fields
are provided, the multi_match
query defaults to the index.query.default_field
index settings, which in turn defaults to *
. *
extracts all fields in the mapping that are eligible to term queries and filters the metadata fields. All extracted fields are then combined to build a query.
Field number limit
By default, there is a limit to the number of clauses a query can contain. This limit is defined by the indices.query.bool.max_clause_count setting, which defaults to 4096
. For multi-match queries, the number of clauses is calculated as the number of fields multiplied by the number of terms.
Types of multi_match
query:
The way the multi_match
query is executed internally depends on the type
parameter, which can be set to:
| (default) Finds documents which match any field, but uses the |
| Finds documents which match any field and combines the |
| Treats fields with the same |
| Runs a |
| Runs a |
| Creates a |
best_fields
The best_fields
type is most useful when you are searching for multiple words best found in the same field. For instance “brown fox” in a single field is more meaningful than “brown” in one field and “fox” in the other.
The best_fields
type generates a match query for each field and wraps them in a dis_max query, to find the single best matching field. For instance, this query:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'brown fox',
'type' => 'best_fields',
'fields' => [
'subject',
'message',
],
'tie_breaker' => 0.3,
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "brown fox",
"type": "best_fields",
"fields": [
"subject",
"message"
],
"tie_breaker": 0.3
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'brown fox',
type: 'best_fields',
fields: [
'subject',
'message'
],
tie_breaker: 0.3
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "brown fox",
"type": "best_fields",
"fields": [
"subject",
"message"
],
"tie_breaker": 0.3
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "brown fox",
type: "best_fields",
fields: ["subject", "message"],
tie_breaker: 0.3,
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "brown fox",
"type": "best_fields",
"fields": [ "subject", "message" ],
"tie_breaker": 0.3
}
}
}
would be executed as:
$params = [
'body' => [
'query' => [
'dis_max' => [
'queries' => [
[
'match' => [
'subject' => 'brown fox',
],
],
[
'match' => [
'message' => 'brown fox',
],
],
],
'tie_breaker' => 0.3,
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"dis_max": {
"queries": [
{
"match": {
"subject": "brown fox"
}
},
{
"match": {
"message": "brown fox"
}
}
],
"tie_breaker": 0.3
}
},
)
print(resp)
response = client.search(
body: {
query: {
dis_max: {
queries: [
{
match: {
subject: 'brown fox'
}
},
{
match: {
message: 'brown fox'
}
}
],
tie_breaker: 0.3
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"dis_max": {
"queries": [
{
"match": {
"subject": "brown fox"
}
},
{
"match": {
"message": "brown fox"
}
}
],
"tie_breaker": 0.3
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
dis_max: {
queries: [
{
match: {
subject: "brown fox",
},
},
{
match: {
message: "brown fox",
},
},
],
tie_breaker: 0.3,
},
},
});
console.log(response);
GET /_search
{
"query": {
"dis_max": {
"queries": [
{ "match": { "subject": "brown fox" }},
{ "match": { "message": "brown fox" }}
],
"tie_breaker": 0.3
}
}
}
Normally the best_fields
type uses the score of the single best matching field, but if tie_breaker
is specified, then it calculates the score as follows:
- the score from the best matching field
- plus
tie_breaker * _score
for all other matching fields
Also, accepts analyzer
, boost
, operator
, minimum_should_match
, fuzziness
, lenient
, prefix_length
, max_expansions
, fuzzy_rewrite
, zero_terms_query
, auto_generate_synonyms_phrase_query
and fuzzy_transpositions
, as explained in match query.
operator
and minimum_should_match
The best_fields
and most_fields
types are field-centric — they generate a match
query per field. This means that the operator
and minimum_should_match
parameters are applied to each field individually, which is probably not what you want.
Take this query for example:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'Will Smith',
'type' => 'best_fields',
'fields' => [
'first_name',
'last_name',
],
'operator' => 'and',
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "Will Smith",
"type": "best_fields",
"fields": [
"first_name",
"last_name"
],
"operator": "and"
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'Will Smith',
type: 'best_fields',
fields: [
'first_name',
'last_name'
],
operator: 'and'
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "Will Smith",
"type": "best_fields",
"fields": [
"first_name",
"last_name"
],
"operator": "and"
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "Will Smith",
type: "best_fields",
fields: ["first_name", "last_name"],
operator: "and",
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "Will Smith",
"type": "best_fields",
"fields": [ "first_name", "last_name" ],
"operator": "and"
}
}
}
All terms must be present. |
This query is executed as:
(+first_name:will +first_name:smith)
| (+last_name:will +last_name:smith)
In other words, all terms must be present in a single field for a document to match.
The combined_fields query offers a term-centric approach that handles operator
and minimum_should_match
on a per-term basis. The other multi-match mode cross_fields also addresses this issue.
most_fields
The most_fields
type is most useful when querying multiple fields that contain the same text analyzed in different ways. For instance, the main field may contain synonyms, stemming and terms without diacritics. A second field may contain the original terms, and a third field might contain shingles. By combining scores from all three fields we can match as many documents as possible with the main field, but use the second and third fields to push the most similar results to the top of the list.
This query:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'quick brown fox',
'type' => 'most_fields',
'fields' => [
'title',
'title.original',
'title.shingles',
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "quick brown fox",
"type": "most_fields",
"fields": [
"title",
"title.original",
"title.shingles"
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'quick brown fox',
type: 'most_fields',
fields: [
'title',
'title.original',
'title.shingles'
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "quick brown fox",
"type": "most_fields",
"fields": [
"title",
"title.original",
"title.shingles"
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "quick brown fox",
type: "most_fields",
fields: ["title", "title.original", "title.shingles"],
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "quick brown fox",
"type": "most_fields",
"fields": [ "title", "title.original", "title.shingles" ]
}
}
}
would be executed as:
$params = [
'body' => [
'query' => [
'bool' => [
'should' => [
[
'match' => [
'title' => 'quick brown fox',
],
],
[
'match' => [
'title.original' => 'quick brown fox',
],
],
[
'match' => [
'title.shingles' => 'quick brown fox',
],
],
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"bool": {
"should": [
{
"match": {
"title": "quick brown fox"
}
},
{
"match": {
"title.original": "quick brown fox"
}
},
{
"match": {
"title.shingles": "quick brown fox"
}
}
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
bool: {
should: [
{
match: {
title: 'quick brown fox'
}
},
{
match: {
'title.original' => 'quick brown fox'
}
},
{
match: {
'title.shingles' => 'quick brown fox'
}
}
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"bool": {
"should": [
{
"match": {
"title": "quick brown fox"
}
},
{
"match": {
"title.original": "quick brown fox"
}
},
{
"match": {
"title.shingles": "quick brown fox"
}
}
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
bool: {
should: [
{
match: {
title: "quick brown fox",
},
},
{
match: {
"title.original": "quick brown fox",
},
},
{
match: {
"title.shingles": "quick brown fox",
},
},
],
},
},
});
console.log(response);
GET /_search
{
"query": {
"bool": {
"should": [
{ "match": { "title": "quick brown fox" }},
{ "match": { "title.original": "quick brown fox" }},
{ "match": { "title.shingles": "quick brown fox" }}
]
}
}
}
The score from each match
clause is added together, just like a bool
query.
Also, accepts analyzer
, boost
, operator
, minimum_should_match
, fuzziness
, lenient
, prefix_length
, max_expansions
, fuzzy_rewrite
, and zero_terms_query
.
phrase
and phrase_prefix
The phrase
and phrase_prefix
types behave just like best_fields, but they use a match_phrase
or match_phrase_prefix
query instead of a match
query.
This query:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'quick brown f',
'type' => 'phrase_prefix',
'fields' => [
'subject',
'message',
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "quick brown f",
"type": "phrase_prefix",
"fields": [
"subject",
"message"
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'quick brown f',
type: 'phrase_prefix',
fields: [
'subject',
'message'
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "quick brown f",
"type": "phrase_prefix",
"fields": [
"subject",
"message"
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "quick brown f",
type: "phrase_prefix",
fields: ["subject", "message"],
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "quick brown f",
"type": "phrase_prefix",
"fields": [ "subject", "message" ]
}
}
}
would be executed as:
$params = [
'body' => [
'query' => [
'dis_max' => [
'queries' => [
[
'match_phrase_prefix' => [
'subject' => 'quick brown f',
],
],
[
'match_phrase_prefix' => [
'message' => 'quick brown f',
],
],
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"dis_max": {
"queries": [
{
"match_phrase_prefix": {
"subject": "quick brown f"
}
},
{
"match_phrase_prefix": {
"message": "quick brown f"
}
}
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
dis_max: {
queries: [
{
match_phrase_prefix: {
subject: 'quick brown f'
}
},
{
match_phrase_prefix: {
message: 'quick brown f'
}
}
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"dis_max": {
"queries": [
{
"match_phrase_prefix": {
"subject": "quick brown f"
}
},
{
"match_phrase_prefix": {
"message": "quick brown f"
}
}
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
dis_max: {
queries: [
{
match_phrase_prefix: {
subject: "quick brown f",
},
},
{
match_phrase_prefix: {
message: "quick brown f",
},
},
],
},
},
});
console.log(response);
GET /_search
{
"query": {
"dis_max": {
"queries": [
{ "match_phrase_prefix": { "subject": "quick brown f" }},
{ "match_phrase_prefix": { "message": "quick brown f" }}
]
}
}
}
Also, accepts analyzer
, boost
, lenient
and zero_terms_query
as explained in Match, as well as slop
which is explained in Match phrase. Type phrase_prefix
additionally accepts max_expansions
.
phrase
, phrase_prefix
and fuzziness
The fuzziness
parameter cannot be used with the phrase
or phrase_prefix
type.
cross_fields
The cross_fields
type is particularly useful with structured documents where multiple fields should match. For instance, when querying the first_name
and last_name
fields for “Will Smith”, the best match is likely to have “Will” in one field and “Smith” in the other.
This sounds like a job for most_fields but there are two problems with that approach. The first problem is that operator
and minimum_should_match
are applied per-field, instead of per-term (see explanation above).
The second problem is to do with relevance: the different term frequencies in the first_name
and last_name
fields can produce unexpected results.
For instance, imagine we have two people: “Will Smith” and “Smith Jones”. “Smith” as a last name is very common (and so is of low importance) but “Smith” as a first name is very uncommon (and so is of great importance).
If we do a search for “Will Smith”, the “Smith Jones” document will probably appear above the better matching “Will Smith” because the score of first_name:smith
has trumped the combined scores of first_name:will
plus last_name:smith
.
One way of dealing with these types of queries is simply to index the first_name
and last_name
fields into a single full_name
field. Of course, this can only be done at index time.
The cross_field
type tries to solve these problems at query time by taking a term-centric approach. It first analyzes the query string into individual terms, then looks for each term in any of the fields, as though they were one big field.
A query like:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'Will Smith',
'type' => 'cross_fields',
'fields' => [
'first_name',
'last_name',
],
'operator' => 'and',
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "Will Smith",
"type": "cross_fields",
"fields": [
"first_name",
"last_name"
],
"operator": "and"
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'Will Smith',
type: 'cross_fields',
fields: [
'first_name',
'last_name'
],
operator: 'and'
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "Will Smith",
"type": "cross_fields",
"fields": [
"first_name",
"last_name"
],
"operator": "and"
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "Will Smith",
type: "cross_fields",
fields: ["first_name", "last_name"],
operator: "and",
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "Will Smith",
"type": "cross_fields",
"fields": [ "first_name", "last_name" ],
"operator": "and"
}
}
}
is executed as:
+(first_name:will last_name:will)
+(first_name:smith last_name:smith)
In other words, all terms must be present in at least one field for a document to match. (Compare this to the logic used for best_fields and most_fields.)
That solves one of the two problems. The problem of differing term frequencies is solved by blending the term frequencies for all fields in order to even out the differences.
In practice, first_name:smith
will be treated as though it has the same frequencies as last_name:smith
, plus one. This will make matches on first_name
and last_name
have comparable scores, with a tiny advantage for last_name
since it is the most likely field that contains smith
.
Note that cross_fields
is usually only useful on short string fields that all have a boost
of 1
. Otherwise boosts, term freqs and length normalization contribute to the score in such a way that the blending of term statistics is not meaningful anymore.
If you run the above query through the Validate, it returns this explanation:
+blended("will", fields: [first_name, last_name])
+blended("smith", fields: [first_name, last_name])
Also, accepts analyzer
, boost
, operator
, minimum_should_match
, lenient
and zero_terms_query
.
The cross_fields
type blends field statistics in a complex way that can be hard to interpret. The score combination can even be incorrect, in particular when some documents contain some of the search fields, but not all of them. You should consider the combined_fields query as an alternative, which is also term-centric but combines field statistics in a more robust way.
cross_field
and analysis
The cross_field
type can only work in term-centric mode on fields that have the same analyzer. Fields with the same analyzer are grouped together as in the example above. If there are multiple groups, the query will use the best score from any group.
For instance, if we have a first
and last
field which have the same analyzer, plus a first.edge
and last.edge
which both use an edge_ngram
analyzer, this query:
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'Jon',
'type' => 'cross_fields',
'fields' => [
'first',
'first.edge',
'last',
'last.edge',
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "Jon",
"type": "cross_fields",
"fields": [
"first",
"first.edge",
"last",
"last.edge"
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'Jon',
type: 'cross_fields',
fields: [
'first',
'first.edge',
'last',
'last.edge'
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "Jon",
"type": "cross_fields",
"fields": [
"first",
"first.edge",
"last",
"last.edge"
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "Jon",
type: "cross_fields",
fields: ["first", "first.edge", "last", "last.edge"],
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "Jon",
"type": "cross_fields",
"fields": [
"first", "first.edge",
"last", "last.edge"
]
}
}
}
would be executed as:
blended("jon", fields: [first, last])
| (
blended("j", fields: [first.edge, last.edge])
blended("jo", fields: [first.edge, last.edge])
blended("jon", fields: [first.edge, last.edge])
)
In other words, first
and last
would be grouped together and treated as a single field, and first.edge
and last.edge
would be grouped together and treated as a single field.
Having multiple groups is fine, but when combined with operator
or minimum_should_match
, it can suffer from the same problem as most_fields
or best_fields
.
You can easily rewrite this query yourself as two separate cross_fields
queries combined with a dis_max
query, and apply the minimum_should_match
parameter to just one of them:
resp = client.search(
query={
"dis_max": {
"queries": [
{
"multi_match": {
"query": "Will Smith",
"type": "cross_fields",
"fields": [
"first",
"last"
],
"minimum_should_match": "50%"
}
},
{
"multi_match": {
"query": "Will Smith",
"type": "cross_fields",
"fields": [
"*.edge"
]
}
}
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
dis_max: {
queries: [
{
multi_match: {
query: 'Will Smith',
type: 'cross_fields',
fields: [
'first',
'last'
],
minimum_should_match: '50%'
}
},
{
multi_match: {
query: 'Will Smith',
type: 'cross_fields',
fields: [
'*.edge'
]
}
}
]
}
}
}
)
puts response
const response = await client.search({
query: {
dis_max: {
queries: [
{
multi_match: {
query: "Will Smith",
type: "cross_fields",
fields: ["first", "last"],
minimum_should_match: "50%",
},
},
{
multi_match: {
query: "Will Smith",
type: "cross_fields",
fields: ["*.edge"],
},
},
],
},
},
});
console.log(response);
GET /_search
{
"query": {
"dis_max": {
"queries": [
{
"multi_match" : {
"query": "Will Smith",
"type": "cross_fields",
"fields": [ "first", "last" ],
"minimum_should_match": "50%"
}
},
{
"multi_match" : {
"query": "Will Smith",
"type": "cross_fields",
"fields": [ "*.edge" ]
}
}
]
}
}
}
Either |
You can force all fields into the same group by specifying the analyzer
parameter in the query.
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'Jon',
'type' => 'cross_fields',
'analyzer' => 'standard',
'fields' => [
'first',
'last',
'*.edge',
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "Jon",
"type": "cross_fields",
"analyzer": "standard",
"fields": [
"first",
"last",
"*.edge"
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'Jon',
type: 'cross_fields',
analyzer: 'standard',
fields: [
'first',
'last',
'*.edge'
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "Jon",
"type": "cross_fields",
"analyzer": "standard",
"fields": [
"first",
"last",
"*.edge"
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "Jon",
type: "cross_fields",
analyzer: "standard",
fields: ["first", "last", "*.edge"],
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "Jon",
"type": "cross_fields",
"analyzer": "standard",
"fields": [ "first", "last", "*.edge" ]
}
}
}
Use the |
which will be executed as:
blended("will", fields: [first, first.edge, last.edge, last])
blended("smith", fields: [first, first.edge, last.edge, last])
tie_breaker
By default, each per-term blended
query will use the best score returned by any field in a group. Then when combining scores across groups, the query uses the best score from any group. The tie_breaker
parameter can change the behavior for both of these steps:
| Take the single best score out of (eg) |
| Add together the scores for (eg) |
| Take the single best score plus |
cross_fields
and fuzziness
The fuzziness
parameter cannot be used with the cross_fields
type.
bool_prefix
The bool_prefix
type’s scoring behaves like most_fields, but using a match_bool_prefix query instead of a match
query.
$params = [
'body' => [
'query' => [
'multi_match' => [
'query' => 'quick brown f',
'type' => 'bool_prefix',
'fields' => [
'subject',
'message',
],
],
],
],
];
$response = $client->search($params);
resp = client.search(
query={
"multi_match": {
"query": "quick brown f",
"type": "bool_prefix",
"fields": [
"subject",
"message"
]
}
},
)
print(resp)
response = client.search(
body: {
query: {
multi_match: {
query: 'quick brown f',
type: 'bool_prefix',
fields: [
'subject',
'message'
]
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithBody(strings.NewReader(`{
"query": {
"multi_match": {
"query": "quick brown f",
"type": "bool_prefix",
"fields": [
"subject",
"message"
]
}
}
}`)),
es.Search.WithPretty(),
)
fmt.Println(res, err)
const response = await client.search({
query: {
multi_match: {
query: "quick brown f",
type: "bool_prefix",
fields: ["subject", "message"],
},
},
});
console.log(response);
GET /_search
{
"query": {
"multi_match" : {
"query": "quick brown f",
"type": "bool_prefix",
"fields": [ "subject", "message" ]
}
}
}
The analyzer
, boost
, operator
, minimum_should_match
, lenient
, zero_terms_query
, and auto_generate_synonyms_phrase_query
parameters as explained in match query are supported. The fuzziness
, prefix_length
, max_expansions
, fuzzy_rewrite
, and fuzzy_transpositions
parameters are supported for the terms that are used to construct term queries, but do not have an effect on the prefix query constructed from the final term.
The slop
parameter is not supported by this query type.