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### 最佳字段查询的调优 如果用户((("multifield search", "best fields queries", "tuning")))((("best fields queries", "tuning")))搜索的是"quick pets",那么会发生什么呢?两份文档都包含了单词quick,但是只有文档2包含了单词pets。两份文档都没能在一个字段中同时包含搜索的两个单词。 一个像下面那样的简单dis_max查询会选择出拥有最佳匹配字段的查询子句,而忽略其他的查询子句: ```Javascript { "query": { "dis_max": { "queries": [ { "match": { "title": "Quick pets" }}, { "match": { "body": "Quick pets" }} ] } } } ``` // SENSE: 110_Multi_Field_Search/15_Best_fields.json ```Javascript { "hits": [ { "_id": "1", "_score": 0.12713557, <1> "_source": { "title": "Quick brown rabbits", "body": "Brown rabbits are commonly seen." } }, { "_id": "2", "_score": 0.12713557, <1> "_source": { "title": "Keeping pets healthy", "body": "My quick brown fox eats rabbits on a regular basis." } } ] } ``` <1> 可以发现,两份文档的分值是一模一样的。 我们期望的是同时匹配了title字段和body字段的文档能够拥有更高的排名,但是结果并非如此。需要记住:dis_max查询只是简单的使用最佳匹配查询子句得到的_score。 #### tie_breaker 但是,将其它匹配的查询子句考虑进来也是可能的。通过指定tie_breaker参数: ```Javascript { "query": { "dis_max": { "queries": [ { "match": { "title": "Quick pets" }}, { "match": { "body": "Quick pets" }} ], "tie_breaker": 0.3 } } } ``` // SENSE: 110_Multi_Field_Search/15_Best_fields.json 它会返回以下结果: ```Javascript { "hits": [ { "_id": "2", "_score": 0.14757764, <1> "_source": { "title": "Keeping pets healthy", "body": "My quick brown fox eats rabbits on a regular basis." } }, { "_id": "1", "_score": 0.124275915, <1> "_source": { "title": "Quick brown rabbits", "body": "Brown rabbits are commonly seen." } } ] } ``` <1> 现在文档2的分值比文档1稍高一些。 tie_breaker参数会让dis_max查询的行为更像是dis_max和bool的一种折中。它会通过下面的方式改变分值计算过程: * 1.取得最佳匹配查询子句的_score。 * 2.将其它每个匹配的子句的分值乘以tie_breaker。 * 3.将以上得到的分值进行累加并规范化。 通过tie_breaker参数,所有匹配的子句都会起作用,只不过最佳匹配子句的作用更大。 > 提示:tie_breaker的取值范围是0到1之间的浮点数,取0时即为仅使用最佳匹配子句(译注:和不使用tie_breaker参数的dis_max查询效果相同),取1则会将所有匹配的子句一视同仁。它的确切值需要根据你的数据和查询进行调整,但是一个合理的值会靠近0,(比如,0.1 -0.4),来确保不会压倒dis_max查询具有的最佳匹配性质。 <!-- === Tuning Best Fields Queries What would happen if the user((("multifield search", "best fields queries", "tuning")))((("best fields queries", "tuning"))) had searched instead for ``quick pets''? Both documents contain the word `quick`, but only document 2 contains the word `pets`. Neither document contains _both words_ in the _same field_. A simple `dis_max` query like the following would ((("dis_max (disjunction max) query")))((("relevance scores", "calculation in dis_max queries")))choose the single best matching field, and ignore the other: [source,js] -------------------------------------------------- { "query": { "dis_max": { "queries": [ { "match": { "title": "Quick pets" }}, { "match": { "body": "Quick pets" }} ] } } } -------------------------------------------------- // SENSE: 110_Multi_Field_Search/15_Best_fields.json [source,js] -------------------------------------------------- { "hits": [ { "_id": "1", "_score": 0.12713557, <1> "_source": { "title": "Quick brown rabbits", "body": "Brown rabbits are commonly seen." } }, { "_id": "2", "_score": 0.12713557, <1> "_source": { "title": "Keeping pets healthy", "body": "My quick brown fox eats rabbits on a regular basis." } } ] } -------------------------------------------------- <1> Note that the scores are exactly the same. We would probably expect documents that match on both the `title` field and the `body` field to rank higher than documents that match on just one field, but this isn't the case. Remember: the `dis_max` query simply uses the `_score` from the _single_ best-matching clause. ==== tie_breaker It is possible, however, to((("dis_max (disjunction max) query", "using tie_breaker parameter")))((("relevance scores", "calculation in dis_max queries", "using tie_breaker parameter"))) also take the `_score` from the other matching clauses into account, by specifying ((("tie_breaker parameter")))the `tie_breaker` parameter: [source,js] -------------------------------------------------- { "query": { "dis_max": { "queries": [ { "match": { "title": "Quick pets" }}, { "match": { "body": "Quick pets" }} ], "tie_breaker": 0.3 } } } -------------------------------------------------- // SENSE: 110_Multi_Field_Search/15_Best_fields.json This gives us the following results: [source,js] -------------------------------------------------- { "hits": [ { "_id": "2", "_score": 0.14757764, <1> "_source": { "title": "Keeping pets healthy", "body": "My quick brown fox eats rabbits on a regular basis." } }, { "_id": "1", "_score": 0.124275915, <1> "_source": { "title": "Quick brown rabbits", "body": "Brown rabbits are commonly seen." } } ] } -------------------------------------------------- <1> Document 2 now has a small lead over document 1. The `tie_breaker` parameter makes the `dis_max` query behave more like a halfway house between `dis_max` and `bool`. It changes the score calculation as follows: 1. Take the `_score` of the best-matching clause. 2. Multiply the score of each of the other matching clauses by the `tie_breaker`. 3. Add them all together and normalize. With the `tie_breaker`, all matching clauses count, but the best-matching clause counts most. [NOTE] ==== The `tie_breaker` can be a floating-point value between `0` and `1`, where `0` uses just the best-matching clause((("tie_breaker parameter", "value of"))) and `1` counts all matching clauses equally. The exact value can be tuned based on your data and queries, but a reasonable value should be close to zero, (for example, `0.1 - 0.4`), in order not to overwhelm the best-matching nature of `dis_max`. ==== -->