opensearch-docs-cn/_query-dsl/compound/bool.md

---
layout: default
title: Boolean
parent: Compound queries
grand_parent: Query DSL
nav_order: 10
redirect_from:
  - /opensearch/query-dsl/compound/bool/
  - /opensearch/query-dsl/bool/
  - /query-dsl/query-dsl/compound/bool/
---

# 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`]({{site.url}}{{site.baseurl}}/query-dsl/query-dsl/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:

```json
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:

1. The `text_entry` field must contain the word `love` and should contain either `life` or `grace`.
2. The `speaker` field must not contain `ROMEO`.
3. Filter these results to the play `Romeo and Juliet` without affecting the relevance score.

These requirements can be combined in the following query:

```json
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:

```json
{
  "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:

```json
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:

```json
"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`:

```json
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:

```json
{
  "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!"
        }
      }
    ]
  }
}
```