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Boolean query
A Boolean (bool
) query can combine several query clauses into one advanced query. The clauses are combined with Boolean logic to find matching documents returned in the results.
Use the following query clauses within a bool
query:
Clause | Behavior |
---|---|
must | Logical and operator. The results must match all queries in this clause. |
must_not | Logical not operator. All matches are excluded from the results. |
should | Logical or operator. The results must match at least one of the queries. Matching more should clauses increases the document’s relevance score. You can set the minimum number of queries that must match using the minimum_should_match parameter. If a query contains a must or filter clause, the default minimum_should_match value is 0. Otherwise, the default minimum_should_match value is 1. |
filter | Logical and operator that is applied first to reduce your dataset before applying the queries. A query within a filter clause is a yes or no option. If a document matches the query, it is returned in the results; otherwise, it is not. The results of a filter query are generally cached to allow for a faster return. Use the filter query to filter the results based on exact matches, ranges, dates, or numbers. |
A Boolean query has the following structure:
GET _search
{
"query": {
"bool": {
"must": [
{}
],
"must_not": [
{}
],
"should": [
{}
],
"filter": {}
}
}
}
For example, assume you have the complete works of Shakespeare indexed in an OpenSearch cluster. You want to construct a single query that meets the following requirements:
- The
text_entry
field must contain the wordlove
and should contain eitherlife
orgrace
. - The
speaker
field must not containROMEO
. - Filter these results to the play
Romeo and Juliet
without affecting the relevance score.
These requirements can be combined in the following query:
GET shakespeare/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"text_entry": "love"
}
}
],
"should": [
{
"match": {
"text_entry": "life"
}
},
{
"match": {
"text_entry": "grace"
}
}
],
"minimum_should_match": 1,
"must_not": [
{
"match": {
"speaker": "ROMEO"
}
}
],
"filter": {
"term": {
"play_name": "Romeo and Juliet"
}
}
}
}
}
The response contains matching documents:
{
"took": 12,
"timed_out": false,
"_shards": {
"total": 4,
"successful": 4,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 11.356054,
"hits": [
{
"_index": "shakespeare",
"_id": "88020",
"_score": 11.356054,
"_source": {
"type": "line",
"line_id": 88021,
"play_name": "Romeo and Juliet",
"speech_number": 19,
"line_number": "4.5.61",
"speaker": "PARIS",
"text_entry": "O love! O life! not life, but love in death!"
}
}
]
}
}
If you want to identify which of these clauses actually caused the matching results, name each query with the _name
parameter. To add the _name
parameter, change the field name in the match
query to an object:
GET shakespeare/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"text_entry": {
"query": "love",
"_name": "love-must"
}
}
}
],
"should": [
{
"match": {
"text_entry": {
"query": "life",
"_name": "life-should"
}
}
},
{
"match": {
"text_entry": {
"query": "grace",
"_name": "grace-should"
}
}
}
],
"minimum_should_match": 1,
"must_not": [
{
"match": {
"speaker": {
"query": "ROMEO",
"_name": "ROMEO-must-not"
}
}
}
],
"filter": {
"term": {
"play_name": "Romeo and Juliet"
}
}
}
}
}
OpenSearch returns a matched_queries
array that lists the queries that matched these results:
"matched_queries": [
"love-must",
"life-should"
]
If you remove the queries not in this list, you will still see the exact same result. By examining which should
clause matched, you can better understand the relevance score of the results.
You can also construct complex Boolean expressions by nesting bool
queries. For example, use the following query to find a text_entry
field that matches (love
OR hate
) AND (life
OR grace
) in the play Romeo and Juliet
:
GET shakespeare/_search
{
"query": {
"bool": {
"must": [
{
"bool": {
"should": [
{
"match": {
"text_entry": "love"
}
},
{
"match": {
"text": "hate"
}
}
]
}
},
{
"bool": {
"should": [
{
"match": {
"text_entry": "life"
}
},
{
"match": {
"text": "grace"
}
}
]
}
}
],
"filter": {
"term": {
"play_name": "Romeo and Juliet"
}
}
}
}
}
The response contains matching documents:
{
"took": 10,
"timed_out": false,
"_shards": {
"total": 2,
"successful": 2,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 11.37006,
"hits": [
{
"_index": "shakespeare",
"_type": "doc",
"_id": "88020",
"_score": 11.37006,
"_source": {
"type": "line",
"line_id": 88021,
"play_name": "Romeo and Juliet",
"speech_number": 19,
"line_number": "4.5.61",
"speaker": "PARIS",
"text_entry": "O love! O life! not life, but love in death!"
}
}
]
}
}