### match匹配怎么當成布爾查詢來使用 到現在為止，你可能已經意識到在一個布爾查詢中多字段`match`查詢僅僅包裹了已經生成的`term`查詢。通過默認的`or`操作符，每個`term`查詢都會像一個`should`子句一樣被添加，只要有一個子句匹配就可以了。下面的兩個查詢是等價的： ```Javacript { "match": { "title": "brown fox"} } ``` ```Javascript { "bool": { "should": [ { "term": { "title": "brown" }}, { "term": { "title": "fox" }} ] } } ``` 通過`and`操作符，所有的`term`查詢會像`must`子句一樣被添加，因此所有的子句都必須匹配。下面的兩個查詢是等價的： ```Javascript { "match": { "title": { "query": "brown fox", "operator": "and" } } } ``` ```Javascript { "bool": { "must": [ { "term": { "title": "brown" }}, { "term": { "title": "fox" }} ] } } ``` 如果`minimum_should_match`參數被指定，`match`查詢就直接被轉換成一個`bool`查詢，下面兩個查詢是等價的： ```Javascript { "match": { "title": { "query": "quick brown fox", "minimum_should_match": "75%" } } } ``` ```Javascript { "bool": { "should": [ { "term": { "title": "brown" }}, { "term": { "title": "fox" }}, { "term": { "title": "quick" }} ], "minimum_should_match": 2 <1> } } ``` <1>因為只有三個子句，所以 `minimum_should_match`參數在`match`查詢中的值`75%`就下舍到了`2`。3個`should`子句中至少有兩個子句匹配。 當然，我們通常寫這些查詢類型的時候還是使用`match`查詢的，但是理解`match`查詢在內部是怎么工作的可以讓你在任何你需要使用的時候更加得心應手。有些情況僅僅使用一個`match`查詢是不夠的，比如給某些查詢詞更高的權重。這種情況我們會在下一節看個例子。 <!-- === How match Uses bool By now, you have probably realized that <<match-multi-word,multiword `match` queries>> simply wrap((("match query", "use of bool query in multi-word searches")))((("bool query", "use by match query in multi-word searches")))((("full text search", "how match query uses bool query"))) the generated `term` queries in a `bool` query. With the default `or` operator, each `term` query is added as a `should` clause, so at least one clause must match. These two queries are equivalent: [source,js] -------------------------------------------------- { "match": { "title": "brown fox"} } -------------------------------------------------- [source,js] -------------------------------------------------- { "bool": { "should": [ { "term": { "title": "brown" }}, { "term": { "title": "fox" }} ] } } -------------------------------------------------- With the `and` operator, all the `term` queries are added as `must` clauses, so _all_ clauses must match. These two queries are equivalent: [source,js] -------------------------------------------------- { "match": { "title": { "query": "brown fox", "operator": "and" } } } -------------------------------------------------- [source,js] -------------------------------------------------- { "bool": { "must": [ { "term": { "title": "brown" }}, { "term": { "title": "fox" }} ] } } -------------------------------------------------- And if the `minimum_should_match` parameter is((("minimum_should_match parameter", "match query using bool query"))) specified, it is passed directly through to the `bool` query, making these two queries equivalent: [source,js] -------------------------------------------------- { "match": { "title": { "query": "quick brown fox", "minimum_should_match": "75%" } } } -------------------------------------------------- [source,js] -------------------------------------------------- { "bool": { "should": [ { "term": { "title": "brown" }}, { "term": { "title": "fox" }}, { "term": { "title": "quick" }} ], "minimum_should_match": 2 <1> } } -------------------------------------------------- <1> Because there are only three clauses, the `minimum_should_match` value of `75%` in the `match` query is rounded down to `2`. At least two out of the three `should` clauses must match. Of course, we would normally write these types of queries by using the `match` query, but understanding how the `match` query works internally lets you take control of the process when you need to. Some things can't be done with a single `match` query, such as give more weight to some query terms than to others. We will look at an example of this in the next section. -->