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<!DOCTYPE HTML>
<html lang="zh-CN">
<head><meta name="generator" content="Hexo 3.9.0">
<meta charset="utf-8">
<meta name="keywords" content="Elasticsearch, 记录">
<meta name="baidu-site-verification" content="fmlEuI34ir">
<meta name="google-site-verification" content="yCy2azpds5XSuGZvis6OuA-XIGF5GuGpYRAaGfD6o48">
<meta name="360-site-verification" content="b7c11a830ef90fd1464ad6206bb7b6e7">
<meta name="description" content="相关概念倒排索引倒排索引的概念是基于MySQL这样的正向索引而言的。
正向索引那么什么是正向索引呢？例如给下表（tb_goods）中的id创建索引：
如果是根据id查询，那么直接走索引，查询速度非常快。
但如果是基于title做模糊查询，">
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<title>Elasticsearch | Ji`s Blog</title>
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</script></head>
<div id="loading-container">
<p class="loading-text"></p>
<div class="loading-image">
<div></div>
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</div><body>
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<h1 id="相关概念"><a href="#相关概念" class="headerlink" title="相关概念"></a>相关概念</h1><h2 id="倒排索引"><a href="#倒排索引" class="headerlink" title="倒排索引"></a>倒排索引</h2><p>倒排索引的概念是基于MySQL这样的正向索引而言的。</p>
<h3 id="正向索引"><a href="#正向索引" class="headerlink" title="正向索引"></a>正向索引</h3><p>那么什么是正向索引呢？例如给下表（tb_goods）中的id创建索引：</p>
<p><img src="/elasticsearch/image-20210720195531539.png" alt="image-20210720195531539"></p>
<p>如果是根据id查询，那么直接走索引，查询速度非常快。</p>
<p>但如果是基于title做模糊查询，只能是逐行扫描数据，流程如下：</p>
<p>1）用户搜索数据，条件是title符合<code>"%手机%"</code></p>
<p>2）逐行获取数据，比如id为1的数据</p>
<p>3）判断数据中的title是否符合用户搜索条件</p>
<p>4）如果符合则放入结果集，不符合则丢弃。回到步骤1</p>
<p>逐行扫描，也就是全表扫描，随着数据量增加，其查询效率也会越来越低。当数据量达到数百万时，就是一场灾难。</p>
<h3 id="倒排索引-1"><a href="#倒排索引-1" class="headerlink" title="倒排索引"></a>倒排索引</h3><p>倒排索引中有两个非常重要的概念：</p>
<ul>
<li>文档（<code>Document</code>）：用来搜索的数据，其中的每一条数据就是一个文档。例如一个网页、一个商品信息</li>
<li>词条（<code>Term</code>）：对文档数据或用户搜索数据，利用某种算法分词，得到的具备含义的词语就是词条。例如：我是中国人，就可以分为：我、是、中国人、中国、国人这样的几个词条</li>
</ul>
<p><strong>创建倒排索引</strong>是对正向索引的一种特殊处理，流程如下：</p>
<ul>
<li>将每一个文档的数据利用算法分词，得到一个个词条</li>
<li>创建表，每行数据包括词条、词条所在文档id、位置等信息</li>
<li>因为词条唯一性，可以给词条创建索引，例如hash表结构索引</li>
</ul>
<p>如图：</p>
<p><img src="/elasticsearch/image-20210720200457207.png" alt="image-20210720200457207"></p>
<p>倒排索引的<strong>搜索流程</strong>如下（以搜索”华为手机”为例）：</p>
<p>1）用户输入条件<code>"华为手机"</code>进行搜索。</p>
<p>2）对用户输入内容<strong>分词</strong>，得到词条：<code>华为</code>、<code>手机</code>。</p>
<p>3）拿着词条在倒排索引中查找，可以得到包含词条的文档id：1、2、3。</p>
<p>4）拿着文档id到正向索引中查找具体文档。</p>
<p>如图：</p>
<p><img src="/elasticsearch/image-20210720201115192.png" alt="image-20210720201115192"></p>
<p>虽然要先查询倒排索引，再查询倒排索引，但是无论是词条、还是文档id都建立了索引，查询速度非常快！无需全表扫描。</p>
<h3 id="正向和倒排"><a href="#正向和倒排" class="headerlink" title="正向和倒排"></a>正向和倒排</h3><p>那么为什么一个叫做正向索引，一个叫做倒排索引呢？</p>
<ul>
<li><p><strong>正向索引</strong>是最传统的，根据id索引的方式。但根据词条查询时，必须先逐条获取每个文档，然后判断文档中是否包含所需要的词条，是<strong>根据文档找词条的过程</strong>。</p>
</li>
<li><p>而<strong>倒排索引</strong>则相反，是先找到用户要搜索的词条，根据词条得到保护词条的文档的id，然后根据id获取文档。是<strong>根据词条找文档的过程</strong>。</p>
</li>
</ul>
<p>是不是恰好反过来了？</p>
<p>那么两者方式的优缺点是什么呢？</p>
<p><strong>正向索引</strong>：</p>
<ul>
<li>优点：<ul>
<li>可以给多个字段创建索引</li>
<li>根据索引字段搜索、排序速度非常快</li>
</ul>
</li>
<li>缺点：<ul>
<li>根据非索引字段，或者索引字段中的部分词条查找时，只能全表扫描。</li>
</ul>
</li>
</ul>
<p><strong>倒排索引</strong>：</p>
<ul>
<li>优点：<ul>
<li>根据词条搜索、模糊搜索时，速度非常快</li>
</ul>
</li>
<li>缺点：<ul>
<li>只能给词条创建索引，而不是字段</li>
<li>无法根据字段做排序</li>
</ul>
</li>
</ul>
<h3 id="文档和字段"><a href="#文档和字段" class="headerlink" title="文档和字段"></a>文档和字段</h3><p>elasticsearch是面向<strong>文档（Document）</strong>存储的，可以是数据库中的一条商品数据，一个订单信息。文档数据会被序列化为json格式后存储在elasticsearch中：</p>
<p><img src="/elasticsearch/image-20210720202707797.png" alt="image-20210720202707797"></p>
<p>而Json文档中往往包含很多的<strong>字段（Field）</strong>，类似于数据库中的列。</p>
<h3 id="索引和映射"><a href="#索引和映射" class="headerlink" title="索引和映射"></a>索引和映射</h3><p><strong>索引（Index）</strong>，就是相同类型的文档的集合。</p>
<p>例如：</p>
<ul>
<li>所有用户文档，就可以组织在一起，称为用户的索引；</li>
<li>所有商品的文档，可以组织在一起，称为商品的索引；</li>
<li>所有订单的文档，可以组织在一起，称为订单的索引；</li>
</ul>
<p><img src="/elasticsearch/image-20210720203022172.png" alt="image-20210720203022172"></p>
<p>因此，我们可以把索引当做是数据库中的表。</p>
<p>数据库的表会有约束信息，用来定义表的结构、字段的名称、类型等信息。因此，索引库中就有<strong>映射（mapping）</strong>，是索引中文档的字段约束信息，类似表的结构约束。</p>
<h3 id="mysql与elasticsearch"><a href="#mysql与elasticsearch" class="headerlink" title="mysql与elasticsearch"></a>mysql与elasticsearch</h3><p>我们统一的把mysql与elasticsearch的概念做一下对比：</p>
<table>
<thead>
<tr>
<th><strong>MySQL</strong></th>
<th><strong>Elasticsearch</strong></th>
<th><strong>说明</strong></th>
</tr>
</thead>
<tbody><tr>
<td>Table</td>
<td>Index</td>
<td>索引(index)，就是文档的集合，类似数据库的表(table)</td>
</tr>
<tr>
<td>Row</td>
<td>Document</td>
<td>文档（Document），就是一条条的数据，类似数据库中的行（Row），文档都是JSON格式</td>
</tr>
<tr>
<td>Column</td>
<td>Field</td>
<td>字段（Field），就是JSON文档中的字段，类似数据库中的列（Column）</td>
</tr>
<tr>
<td>Schema</td>
<td>Mapping</td>
<td>Mapping（映射）是索引中文档的约束，例如字段类型约束。类似数据库的表结构（Schema）</td>
</tr>
<tr>
<td>SQL</td>
<td>DSL</td>
<td>DSL是elasticsearch提供的JSON风格的请求语句，用来操作elasticsearch，实现CRUD</td>
</tr>
</tbody></table>
<p>两者各自有自己的擅长支出：</p>
<ul>
<li><p>Mysql：擅长事务类型操作，可以确保数据的安全和一致性</p>
</li>
<li><p>Elasticsearch：擅长海量数据的搜索、分析、计算</p>
</li>
</ul>
<p>因此在企业中，往往是两者结合使用：</p>
<ul>
<li>对安全性要求较高的写操作，使用mysql实现</li>
<li>对查询性能要求较高的搜索需求，使用elasticsearch实现</li>
<li>两者再基于某种方式，实现数据的同步，保证一致性</li>
</ul>
<p><img src="/elasticsearch/image-20210720203534945.png" alt="image-20210720203534945"></p>
<h1 id="索引库操作"><a href="#索引库操作" class="headerlink" title="索引库操作"></a>索引库操作</h1><p>索引库就类似数据库表，mapping映射就类似表的结构。</p>
<p>我们要向es中存储数据，必须先创建“库”和“表”。</p>
<h2 id="mapping映射属性"><a href="#mapping映射属性" class="headerlink" title="mapping映射属性"></a>mapping映射属性</h2><p>mapping是对索引库中文档的约束，常见的mapping属性包括：</p>
<ul>
<li>type：字段数据类型，常见的简单类型有：<ul>
<li>字符串：text（可分词的文本）、keyword（精确值，例如：品牌、国家、ip地址）</li>
<li>数值：long、integer、short、byte、double、float、</li>
<li>布尔：boolean</li>
<li>日期：date</li>
<li>对象：object</li>
</ul>
</li>
<li>index：是否创建索引，默认为true</li>
<li>analyzer：使用哪种分词器</li>
<li>properties：该字段的子字段</li>
</ul>
<p>例如下面的json文档：</p>
<pre class="line-numbers language-json"><code class="language-json"><span class="token punctuation">{</span>
<span class="token property">"age"</span><span class="token operator">:</span> <span class="token number">21</span><span class="token punctuation">,</span>
<span class="token property">"weight"</span><span class="token operator">:</span> <span class="token number">52.1</span><span class="token punctuation">,</span>
<span class="token property">"isMarried"</span><span class="token operator">:</span> <span class="token boolean">false</span><span class="token punctuation">,</span>
<span class="token property">"info"</span><span class="token operator">:</span> <span class="token string">"黑马程序员Java讲师"</span><span class="token punctuation">,</span>
<span class="token property">"email"</span><span class="token operator">:</span> <span class="token string">"zy@itcast.cn"</span><span class="token punctuation">,</span>
<span class="token property">"score"</span><span class="token operator">:</span> <span class="token punctuation">[</span><span class="token number">99.1</span><span class="token punctuation">,</span> <span class="token number">99.5</span><span class="token punctuation">,</span> <span class="token number">98.9</span><span class="token punctuation">]</span><span class="token punctuation">,</span>
<span class="token property">"name"</span><span class="token operator">:</span> <span class="token punctuation">{</span>
<span class="token property">"firstName"</span><span class="token operator">:</span> <span class="token string">"云"</span><span class="token punctuation">,</span>
<span class="token property">"lastName"</span><span class="token operator">:</span> <span class="token string">"赵"</span>
<span class="token punctuation">}</span>
<span class="token punctuation">}</span><span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>对应的每个字段映射（mapping）：</p>
<ul>
<li>age：类型为 integer；参与搜索，因此需要index为true；无需分词器</li>
<li>weight：类型为float；参与搜索，因此需要index为true；无需分词器</li>
<li>isMarried：类型为boolean；参与搜索，因此需要index为true；无需分词器</li>
<li>info：类型为字符串，需要分词，因此是text；参与搜索，因此需要index为true；分词器可以用ik_smart</li>
<li>email：类型为字符串，但是不需要分词，因此是keyword；不参与搜索，因此需要index为false；无需分词器</li>
<li>score：虽然是数组，但是我们只看元素的类型，类型为float；参与搜索，因此需要index为true；无需分词器</li>
<li>name：类型为object，需要定义多个子属性<ul>
<li>name.firstName；类型为字符串，但是不需要分词，因此是keyword；参与搜索，因此需要index为true；无需分词器</li>
<li>name.lastName；类型为字符串，但是不需要分词，因此是keyword；参与搜索，因此需要index为true；无需分词器</li>
</ul>
</li>
</ul>
<h2 id="索引库的CRUD"><a href="#索引库的CRUD" class="headerlink" title="索引库的CRUD"></a>索引库的CRUD</h2><h3 id="2-2-1-创建索引库和映射"><a href="#2-2-1-创建索引库和映射" class="headerlink" title="2.2.1.创建索引库和映射"></a>2.2.1.创建索引库和映射</h3><h4 id="基本语法："><a href="#基本语法：" class="headerlink" title="基本语法："></a>基本语法：</h4><ul>
<li>请求方式：PUT</li>
<li>请求路径：/索引库名，可以自定义</li>
<li>请求参数：mapping映射</li>
</ul>
<p>格式：</p>
<pre class="line-numbers language-json"><code class="language-json">PUT /索引库名称
<span class="token punctuation">{</span>
<span class="token property">"mappings"</span><span class="token operator">:</span> <span class="token punctuation">{</span>
<span class="token property">"properties"</span><span class="token operator">:</span> <span class="token punctuation">{</span>
<span class="token property">"字段名"</span><span class="token operator">:</span><span class="token punctuation">{</span>
<span class="token property">"type"</span><span class="token operator">:</span> <span class="token string">"text"</span><span class="token punctuation">,</span>
<span class="token property">"analyzer"</span><span class="token operator">:</span> <span class="token string">"ik_smart"</span>
<span class="token punctuation">}</span><span class="token punctuation">,</span>
<span class="token property">"字段名2"</span><span class="token operator">:</span><span class="token punctuation">{</span>
<span class="token property">"type"</span><span class="token operator">:</span> <span class="token string">"keyword"</span><span class="token punctuation">,</span>
<span class="token property">"index"</span><span class="token operator">:</span> <span class="token string">"false"</span>
<span class="token punctuation">}</span><span class="token punctuation">,</span>
<span class="token property">"字段名3"</span><span class="token operator">:</span><span class="token punctuation">{</span>
<span class="token property">"properties"</span><span class="token operator">:</span> <span class="token punctuation">{</span>
<span class="token property">"子字段"</span><span class="token operator">:</span> <span class="token punctuation">{</span>
<span class="token property">"type"</span><span class="token operator">:</span> <span class="token string">"keyword"</span>
<span class="token punctuation">}</span>
<span class="token punctuation">}</span>
<span class="token punctuation">}</span><span class="token punctuation">,</span>
// ...略
<span class="token punctuation">}</span>
<span class="token punctuation">}</span>
<span class="token punctuation">}</span><span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<h4 id="示例："><a href="#示例：" class="headerlink" title="示例："></a>示例：</h4><pre class="line-numbers language-sh"><code class="language-sh">PUT /heima
{
"mappings": {
"properties": {
"info":{
"type": "text",
"analyzer": "ik_smart"
},
"email":{
"type": "keyword",
"index": "falsae"
},
"name":{
"properties": {
"firstName": {
"type": "keyword"