### 最佳字段查詢的調優
如果用戶((("multifield search", "best fields queries", "tuning")))((("best fields queries", "tuning")))搜索的是"quick pets",那么會發生什么呢?兩份文檔都包含了單詞quick,但是只有文檔2包含了單詞pets。兩份文檔都沒能在一個字段中同時包含搜索的兩個單詞。
一個像下面那樣的簡單dis_max查詢會選擇出擁有最佳匹配字段的查詢子句,而忽略其他的查詢子句:
```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> 可以發現,兩份文檔的分值是一模一樣的。
我們期望的是同時匹配了title字段和body字段的文檔能夠擁有更高的排名,但是結果并非如此。需要記住:dis_max查詢只是簡單的使用最佳匹配查詢子句得到的_score。
#### tie_breaker
但是,將其它匹配的查詢子句考慮進來也是可能的。通過指定tie_breaker參數:
```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
它會返回以下結果:
```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> 現在文檔2的分值比文檔1稍高一些。
tie_breaker參數會讓dis_max查詢的行為更像是dis_max和bool的一種折中。它會通過下面的方式改變分值計算過程:
* 1.取得最佳匹配查詢子句的_score。
* 2.將其它每個匹配的子句的分值乘以tie_breaker。
* 3.將以上得到的分值進行累加并規范化。
通過tie_breaker參數,所有匹配的子句都會起作用,只不過最佳匹配子句的作用更大。
> 提示:tie_breaker的取值范圍是0到1之間的浮點數,取0時即為僅使用最佳匹配子句(譯注:和不使用tie_breaker參數的dis_max查詢效果相同),取1則會將所有匹配的子句一視同仁。它的確切值需要根據你的數據和查詢進行調整,但是一個合理的值會靠近0,(比如,0.1 -0.4),來確保不會壓倒dis_max查詢具有的最佳匹配性質。
<!--
=== 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`.
====
-->
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