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<div><h1>07 查询：DSL查询之复合查询详解</h1>
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<h2>复合查询引入</h2>
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<p>在(前文-多条件查询-bool)中，我们使用<code>bool</code>查询来组合多个查询条件。</p>
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<p>比如之前介绍的语句</p>
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<pre><code class="language-bash">GET /bank/_search
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{
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"query": {
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"bool": {
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"must": [
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{ "match": { "age": "40" } }
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],
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"must_not": [
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{ "match": { "state": "ID" } }
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]
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}
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}
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}
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</code></pre>
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<p>这种查询就是本文要介绍的<strong>复合查询</strong>，并且bool查询只是复合查询一种。</p>
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<h2>bool query(布尔查询)</h2>
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<blockquote>
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<p>通过布尔逻辑将较小的查询组合成较大的查询。</p>
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</blockquote>
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<h3>概念</h3>
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<p>Bool查询语法有以下特点</p>
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<ul>
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<li>子查询可以任意顺序出现</li>
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<li>可以嵌套多个查询，包括bool查询</li>
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<li>如果bool查询中没有must条件，should中必须至少满足一条才会返回结果。</li>
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</ul>
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<p>bool查询包含四种操作符，分别是must,should,must_not,filter。他们均是一种数组，数组里面是对应的判断条件。</p>
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<ul>
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<li><code>must</code>： 必须匹配。贡献算分</li>
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<li><code>must_not</code>：过滤子句，必须不能匹配，但不贡献算分</li>
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<li><code>should</code>： 选择性匹配，至少满足一条。贡献算分</li>
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<li><code>filter</code>： 过滤子句，必须匹配，但不贡献算分</li>
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</ul>
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<h3>一些例子</h3>
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<p>看下官方举例</p>
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<ul>
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||
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<li>例子1</li>
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||
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</ul>
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<pre><code class="language-bash">POST _search
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||
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{
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"query": {
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"bool" : {
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"must" : {
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"term" : { "user.id" : "kimchy" }
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},
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||
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"filter": {
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||
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"term" : { "tags" : "production" }
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},
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"must_not" : {
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"range" : {
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"age" : { "gte" : 10, "lte" : 20 }
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}
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||
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},
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||
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"should" : [
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{ "term" : { "tags" : "env1" } },
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||
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{ "term" : { "tags" : "deployed" } }
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||
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],
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||
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"minimum_should_match" : 1,
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||
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"boost" : 1.0
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||
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||
}
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||
|
||
}
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||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>在filter元素下指定的查询对评分没有影响 , 评分返回为0。分数仅受已指定查询的影响。</p>
|
||
|
||
<ul>
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||
|
||
<li>例子2</li>
|
||
|
||
</ul>
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||
|
||
<pre><code class="language-bash">GET _search
|
||
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||
{
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||
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||
"query": {
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||
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||
"bool": {
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||
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||
"filter": {
|
||
|
||
"term": {
|
||
|
||
"status": "active"
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||
|
||
}
|
||
|
||
}
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||
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||
}
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||
|
||
}
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||
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||
}
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||
|
||
</code></pre>
|
||
|
||
<p>这个例子查询查询为所有文档分配0分，因为没有指定评分查询。</p>
|
||
|
||
<ul>
|
||
|
||
<li>例子3</li>
|
||
|
||
</ul>
|
||
|
||
<pre><code class="language-bash">GET _search
|
||
|
||
{
|
||
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||
"query": {
|
||
|
||
"bool": {
|
||
|
||
"must": {
|
||
|
||
"match_all": {}
|
||
|
||
},
|
||
|
||
"filter": {
|
||
|
||
"term": {
|
||
|
||
"status": "active"
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>此bool查询具有match_all查询，该查询为所有文档指定1.0分。</p>
|
||
|
||
<ul>
|
||
|
||
<li>例子4</li>
|
||
|
||
</ul>
|
||
|
||
<pre><code class="language-bash">GET /_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"bool": {
|
||
|
||
"should": [
|
||
|
||
{ "match": { "name.first": { "query": "shay", "_name": "first" } } },
|
||
|
||
{ "match": { "name.last": { "query": "banon", "_name": "last" } } }
|
||
|
||
],
|
||
|
||
"filter": {
|
||
|
||
"terms": {
|
||
|
||
"name.last": [ "banon", "kimchy" ],
|
||
|
||
"_name": "test"
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>每个query条件都可以有一个<code>_name</code>属性，用来追踪搜索出的数据到底match了哪个条件。</p>
|
||
|
||
<h2>boosting query(提高查询)</h2>
|
||
|
||
<blockquote>
|
||
|
||
<p>不同于bool查询，bool查询中只要一个子查询条件不匹配那么搜索的数据就不会出现。而boosting query则是降低显示的权重/优先级（即score)。</p>
|
||
|
||
</blockquote>
|
||
|
||
<h3>概念</h3>
|
||
|
||
<p>比如搜索逻辑是 name = 'apple' and type ='fruit'，对于只满足部分条件的数据，不是不显示，而是降低显示的优先级（即score)</p>
|
||
|
||
<h3>例子</h3>
|
||
|
||
<p>首先创建数据</p>
|
||
|
||
<pre><code class="language-bash">POST /test-dsl-boosting/_bulk
|
||
|
||
{ "index": { "_id": 1 }}
|
||
|
||
{ "content":"Apple Mac" }
|
||
|
||
{ "index": { "_id": 2 }}
|
||
|
||
{ "content":"Apple Fruit" }
|
||
|
||
{ "index": { "_id": 3 }}
|
||
|
||
{ "content":"Apple employee like Apple Pie and Apple Juice" }
|
||
|
||
</code></pre>
|
||
|
||
<p>对匹配<code>pie</code>的做降级显示处理</p>
|
||
|
||
<pre><code class="language-bash">GET /test-dsl-boosting/_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"boosting": {
|
||
|
||
"positive": {
|
||
|
||
"term": {
|
||
|
||
"content": "apple"
|
||
|
||
}
|
||
|
||
},
|
||
|
||
"negative": {
|
||
|
||
"term": {
|
||
|
||
"content": "pie"
|
||
|
||
}
|
||
|
||
},
|
||
|
||
"negative_boost": 0.5
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>执行结果如下</p>
|
||
|
||
<p><img src="assets/es-dsl-com-2.png" alt="img" /></p>
|
||
|
||
<h2>constant_score（固定分数查询）</h2>
|
||
|
||
<blockquote>
|
||
|
||
<p>查询某个条件时，固定的返回指定的score；显然当不需要计算score时，只需要filter条件即可，因为filter context忽略score。</p>
|
||
|
||
</blockquote>
|
||
|
||
<h3>例子</h3>
|
||
|
||
<p>首先创建数据</p>
|
||
|
||
<pre><code class="language-bash">POST /test-dsl-constant/_bulk
|
||
|
||
{ "index": { "_id": 1 }}
|
||
|
||
{ "content":"Apple Mac" }
|
||
|
||
{ "index": { "_id": 2 }}
|
||
|
||
{ "content":"Apple Fruit" }
|
||
|
||
</code></pre>
|
||
|
||
<p>查询apple</p>
|
||
|
||
<pre><code class="language-bash">GET /test-dsl-constant/_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"constant_score": {
|
||
|
||
"filter": {
|
||
|
||
"term": { "content": "apple" }
|
||
|
||
},
|
||
|
||
"boost": 1.2
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>执行结果如下</p>
|
||
|
||
<p><img src="assets/es-dsl-com-3.png" alt="img" /></p>
|
||
|
||
<h2>dis_max(最佳匹配查询）</h2>
|
||
|
||
<blockquote>
|
||
|
||
<p>分离最大化查询（Disjunction Max Query）指的是： 将任何与任一查询匹配的文档作为结果返回，但只将最佳匹配的评分作为查询的评分结果返回 。</p>
|
||
|
||
</blockquote>
|
||
|
||
<h3>例子</h3>
|
||
|
||
<p>假设有个网站允许用户搜索博客的内容，以下面两篇博客内容文档为例：</p>
|
||
|
||
<pre><code class="language-bash">POST /test-dsl-dis-max/_bulk
|
||
|
||
{ "index": { "_id": 1 }}
|
||
|
||
{"title": "Quick brown rabbits","body": "Brown rabbits are commonly seen."}
|
||
|
||
{ "index": { "_id": 2 }}
|
||
|
||
{"title": "Keeping pets healthy","body": "My quick brown fox eats rabbits on a regular basis."}
|
||
|
||
</code></pre>
|
||
|
||
<p>用户输入词组 “Brown fox” 然后点击搜索按钮。事先，我们并不知道用户的搜索项是会在 title 还是在 body 字段中被找到，但是，用户很有可能是想搜索相关的词组。用肉眼判断，文档 2 的匹配度更高，因为它同时包括要查找的两个词：</p>
|
||
|
||
<p>现在运行以下 bool 查询：</p>
|
||
|
||
<pre><code class="language-bash">GET /test-dsl-dis-max/_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"bool": {
|
||
|
||
"should": [
|
||
|
||
{ "match": { "title": "Brown fox" }},
|
||
|
||
{ "match": { "body": "Brown fox" }}
|
||
|
||
]
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p><img src="assets/es-dsl-dismax-2.png" alt="img" /></p>
|
||
|
||
<p>为了理解导致这样的原因，需要看下如何计算评分的</p>
|
||
|
||
<ul>
|
||
|
||
<li><strong>should 条件的计算分数</strong></li>
|
||
|
||
</ul>
|
||
|
||
<pre><code class="language-bash">GET /test-dsl-dis-max/_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"bool": {
|
||
|
||
"should": [
|
||
|
||
{ "match": { "title": "Brown fox" }},
|
||
|
||
{ "match": { "body": "Brown fox" }}
|
||
|
||
]
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>要计算上述分数，首先要计算match的分数</p>
|
||
|
||
<ol>
|
||
|
||
<li>第一个match 中 <code>brown的分数</code></li>
|
||
|
||
</ol>
|
||
|
||
<p>doc 1 分数 = 0.6931471</p>
|
||
|
||
<p><img src="assets/es-dsl-dismax-4.png" alt="img" /></p>
|
||
|
||
<ol>
|
||
|
||
<li>title中没有fox，所以第一个match 中 <code>brown fox 的分数 = brown分数 + 0 = 0.6931471</code></li>
|
||
|
||
</ol>
|
||
|
||
<p>doc 1 分数 = 0.6931471 + 0 = 0.6931471</p>
|
||
|
||
<p><img src="assets/es-dsl-dismax-5.png" alt="img" /></p>
|
||
|
||
<ol>
|
||
|
||
<li>第二个 match 中 <code>brown分数</code></li>
|
||
|
||
</ol>
|
||
|
||
<p>doc 1 分数 = 0.21110919</p>
|
||
|
||
<p>doc 2 分数 = 0.160443</p>
|
||
|
||
<p><img src="assets/es-dsl-dismax-6.png" alt="img" /></p>
|
||
|
||
<ol>
|
||
|
||
<li>第二个 match 中 <code>fox分数</code></li>
|
||
|
||
</ol>
|
||
|
||
<p>doc 1 分数 = 0</p>
|
||
|
||
<p>doc 2 分数 = 0.60996956</p>
|
||
|
||
<p><img src="assets/es-dsl-dismax-7.png" alt="img" /></p>
|
||
|
||
<ol>
|
||
|
||
<li>所以第二个 match 中 <code>brown fox分数 = brown分数 + fox分数</code></li>
|
||
|
||
</ol>
|
||
|
||
<p>doc 1 分数 = 0.21110919 + 0 = 0.21110919</p>
|
||
|
||
<p>doc 2 分数 = 0.160443 + 0.60996956 = 0.77041256</p>
|
||
|
||
<p><img src="assets/es-dsl-dismax-8.png" alt="img" /></p>
|
||
|
||
<ol>
|
||
|
||
<li>所以整个语句分数， <code>should分数 = 第一个match + 第二个match分数</code></li>
|
||
|
||
</ol>
|
||
|
||
<p>doc 1 分数 = 0.6931471 + 0.21110919 = 0.90425634</p>
|
||
|
||
<p>doc 2 分数 = 0 + 0.77041256 = 0.77041256</p>
|
||
|
||
<p><img src="assets/es-dsl-dismax-9.png" alt="img" /></p>
|
||
|
||
<ul>
|
||
|
||
<li><strong>引入了dis_max</strong></li>
|
||
|
||
</ul>
|
||
|
||
<p>不使用 bool 查询，可以使用 dis_max 即分离 最大化查询（Disjunction Max Query） 。分离（Disjunction）的意思是 或（or） ，这与可以把结合（conjunction）理解成 与（and） 相对应。分离最大化查询（Disjunction Max Query）指的是： 将任何与任一查询匹配的文档作为结果返回，但只将最佳匹配的评分作为查询的评分结果返回 ：</p>
|
||
|
||
<pre><code class="language-bash">GET /test-dsl-dis-max/_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"dis_max": {
|
||
|
||
"queries": [
|
||
|
||
{ "match": { "title": "Brown fox" }},
|
||
|
||
{ "match": { "body": "Brown fox" }}
|
||
|
||
],
|
||
|
||
"tie_breaker": 0
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p><img src="assets/es-dsl-dismax-3.png" alt="img" /></p>
|
||
|
||
<p>0.77041256怎么来的呢？ 下文给你解释它如何计算出来的。</p>
|
||
|
||
<ul>
|
||
|
||
<li><strong>dis_max 条件的计算分数</strong></li>
|
||
|
||
</ul>
|
||
|
||
<p>分数 = 第一个匹配条件分数 + tie_breaker * 第二个匹配的条件的分数 ...</p>
|
||
|
||
<pre><code class="language-bash">GET /test-dsl-dis-max/_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"dis_max": {
|
||
|
||
"queries": [
|
||
|
||
{ "match": { "title": "Brown fox" }},
|
||
|
||
{ "match": { "body": "Brown fox" }}
|
||
|
||
],
|
||
|
||
"tie_breaker": 0
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>doc 1 分数 = 0.6931471 + 0.21110919 * 0 = 0.6931471</p>
|
||
|
||
<p>doc 2 分数 = 0.77041256 = 0.77041256</p>
|
||
|
||
<p><img src="assets/es-dsl-dismax-10.png" alt="img" /></p>
|
||
|
||
<p>这样你就能理解通过dis_max将doc 2 置前了， 当然这里如果缺省<code>tie_breaker</code>字段的话默认就是0，你还可以设置它的比例（在0到1之间）来控制排名。（显然值为1时和should查询是一致的）</p>
|
||
|
||
<h2>function_score(函数查询）</h2>
|
||
|
||
<blockquote>
|
||
|
||
<p>简而言之就是用自定义function的方式来计算_score。</p>
|
||
|
||
</blockquote>
|
||
|
||
<p>可以ES有哪些自定义function呢？</p>
|
||
|
||
<ul>
|
||
|
||
<li><code>script_score</code> 使用自定义的脚本来完全控制分值计算逻辑。如果你需要以上预定义函数之外的功能，可以根据需要通过脚本进行实现。</li>
|
||
|
||
<li><code>weight</code> 对每份文档适用一个简单的提升，且该提升不会被归约：当weight为2时，结果为2 * _score。</li>
|
||
|
||
<li><code>random_score</code> 使用一致性随机分值计算来对每个用户采用不同的结果排序方式，对相同用户仍然使用相同的排序方式。</li>
|
||
|
||
<li><code>field_value_factor</code> 使用文档中某个字段的值来改变_score，比如将受欢迎程度或者投票数量考虑在内。</li>
|
||
|
||
<li><code>衰减函数(Decay Function)</code> - <code>linear</code>，<code>exp</code>，<code>gauss</code></li>
|
||
|
||
</ul>
|
||
|
||
<h3>例子</h3>
|
||
|
||
<p>以最简单的random_score 为例</p>
|
||
|
||
<pre><code class="language-bash">GET /_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"function_score": {
|
||
|
||
"query": { "match_all": {} },
|
||
|
||
"boost": "5",
|
||
|
||
"random_score": {},
|
||
|
||
"boost_mode": "multiply"
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>进一步的，它还可以使用上述function的组合(functions)</p>
|
||
|
||
<pre><code class="language-bash">GET /_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"function_score": {
|
||
|
||
"query": { "match_all": {} },
|
||
|
||
"boost": "5",
|
||
|
||
"functions": [
|
||
|
||
{
|
||
|
||
"filter": { "match": { "test": "bar" } },
|
||
|
||
"random_score": {},
|
||
|
||
"weight": 23
|
||
|
||
},
|
||
|
||
{
|
||
|
||
"filter": { "match": { "test": "cat" } },
|
||
|
||
"weight": 42
|
||
|
||
}
|
||
|
||
],
|
||
|
||
"max_boost": 42,
|
||
|
||
"score_mode": "max",
|
||
|
||
"boost_mode": "multiply",
|
||
|
||
"min_score": 42
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>script_score 可以使用如下方式</p>
|
||
|
||
<pre><code class="language-bash">GET /_search
|
||
|
||
{
|
||
|
||
"query": {
|
||
|
||
"function_score": {
|
||
|
||
"query": {
|
||
|
||
"match": { "message": "elasticsearch" }
|
||
|
||
},
|
||
|
||
"script_score": {
|
||
|
||
"script": {
|
||
|
||
"source": "Math.log(2 + doc['my-int'].value)"
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
}
|
||
|
||
</code></pre>
|
||
|
||
<p>更多相关内容，可以参考<a href="https://www.elastic.co/guide/en/elasticsearch/reference/7.12/query-dsl-function-score-query.html">官方文档 </a>PS: 形成体系化认知以后，具体用的时候查询下即可。</p>
|
||
|
||
<h2>参考文章</h2>
|
||
|
||
<p>https://www.elastic.co/guide/en/elasticsearch/reference/current/compound-queries.html</p>
|
||
|
||
<p>https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html</p>
|
||
|
||
<p>https://www.elastic.co/guide/en/elasticsearch/reference/7.12/query-dsl-function-score-query.html</p>
|
||
|
||
</div>
|
||
|
||
</div>
|
||
|
||
<div>
|
||
|
||
<div style="float: left">
|
||
|
||
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|
||
|
||
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|
||
|
||
<div style="float: right">
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||
|
||
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|
||
|
||
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|
||
|
||
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|
||
|
||
|
||
|
||
</div>
|
||
|
||
</div>
|
||
|
||
</div>
|
||
|
||
</div>
|
||
|
||
|
||
|
||
<a class="off-canvas-overlay" onclick="hide_canvas()"></a>
|
||
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|
||
|
||
<script defer src="https://static.cloudflareinsights.com/beacon.min.js/v652eace1692a40cfa3763df669d7439c1639079717194" integrity="sha512-Gi7xpJR8tSkrpF7aordPZQlW2DLtzUlZcumS8dMQjwDHEnw9I7ZLyiOj/6tZStRBGtGgN6ceN6cMH8z7etPGlw==" data-cf-beacon='{"rayId":"70996f9a4ca23d60","version":"2021.12.0","r":1,"token":"1f5d475227ce4f0089a7cff1ab17c0f5","si":100}' crossorigin="anonymous"></script>
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</body>
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<!-- Global site tag (gtag.js) - Google Analytics -->
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<script async src="https://www.googletagmanager.com/gtag/js?id=G-NPSEEVD756"></script>
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<script>
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window.dataLayer = window.dataLayer || [];
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function gtag() {
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dataLayer.push(arguments);
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}
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gtag('js', new Date());
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gtag('config', 'G-NPSEEVD756');
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var path = window.location.pathname
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var cookie = getCookie("lastPath");
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console.log(path)
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if (path.replace("/", "") === "") {
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if (cookie.replace("/", "") !== "") {
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console.log(cookie)
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document.getElementById("tip").innerHTML = "<a href='" + cookie + "'>跳转到上次进度</a>"
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}
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} else {
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setCookie("lastPath", path)
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}
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function setCookie(cname, cvalue) {
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var d = new Date();
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d.setTime(d.getTime() + (180 * 24 * 60 * 60 * 1000));
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var expires = "expires=" + d.toGMTString();
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document.cookie = cname + "=" + cvalue + "; " + expires + ";path = /";
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}
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function getCookie(cname) {
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var name = cname + "=";
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var ca = document.cookie.split(';');
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for (var i = 0; i < ca.length; i++) {
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var c = ca[i].trim();
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if (c.indexOf(name) === 0) return c.substring(name.length, c.length);
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}
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||
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||
return "";
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}
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|
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</script>
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</html>
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