ElasticSearch（三）：通分词器（Analyzer）进行分词（Analysis）
ElasticSearch（三）：通过分词器（Analyzer）进行分词（Analysis）
## Analysis与Analyzer
* Analysis文本分析就是把全文转换成一系列单词的过程，也叫做分词。
* Analysis是通过Analyzer来实现的，它是专门处理分词的组件。可以使用ElasticSearch内置的分词器，也可以按需定制化分词器。
* 除了在数据写入时用分词器转换词条，在匹配查询语句时，也需要用相同的分词器对查询语句进行分析。
Analyzer的组成
分词器是专门处理分词的组件，Analyzer由三个部分组成：
- Character Filters：主要作用是对原始文本进行处理，例如去除HTML标签。
- Tokenizer：主要作用是按照规则来切分单词。
- Token Filter：将切分好的单词进行加工，例如：小写转换、删除停用词、增加同义词。
ElasticSearch的内置分词器
- Standard Analyzer：默认分词器，按词切分，小写处理。
#standard
GET _analyze
{
"analyzer": "standard",
"text": "2 running Quick brown-foxes leap over lazy dogs in the summer evening."
}
#分词结果：Quick小写处理， brown-foxes被切分为 brown，foxes
{
"tokens" : [
{
"token" : "2",
"start_offset" : 0,
"end_offset" : 1,
"type" : "<NUM>",
"position" : 0
},
{
"token" : "running",
"start_offset" : 2,
"end_offset" : 9,
"type" : "<ALPHANUM>",
"position" : 1
},
{
"token" : "quick",#小写处理
"start_offset" : 10,
"end_offset" : 15,
"type" : "<ALPHANUM>",
"position" : 2
},
{
"token" : "brown",
"start_offset" : 16,
"end_offset" : 21,
"type" : "<ALPHANUM>",
"position" : 3
},
{
"token" : "foxes",
"start_offset" : 22,
"end_offset" : 27,
"type" : "<ALPHANUM>",
"position" : 4
},
{
"token" : "leap",
"start_offset" : 28,
"end_offset" : 32,
"type" : "<ALPHANUM>",
"position" : 5
},
{
"token" : "over",
"start_offset" : 33,
"end_offset" : 37,
"type" : "<ALPHANUM>",
"position" : 6
},
{
"token" : "lazy",
"start_offset" : 38,
"end_offset" : 42,
"type" : "<ALPHANUM>",
"position" : 7
},
{
"token" : "dogs",
"start_offset" : 43,
"end_offset" : 47,
"type" : "<ALPHANUM>",
"position" : 8
},
{
"token" : "in",
"start_offset" : 48,
"end_offset" : 50,
"type" : "<ALPHANUM>",
"position" : 9
},
{
"token" : "the",
"start_offset" : 51,
"end_offset" : 54,
"type" : "<ALPHANUM>",
"position" : 10
},
{
"token" : "summer",
"start_offset" : 55,
"end_offset" : 61,
"type" : "<ALPHANUM>",
"position" : 11
},
{
"token" : "evening",
"start_offset" : 62,
"end_offset" : 69,
"type" : "<ALPHANUM>",
"position" : 12
}
]
}
- Simple Analyzer：按照非字母切分（符号被过滤），小写处理。
#simpe
GET _analyze
{
"analyzer": "simple",
"text": "2 running Quick brown-foxes leap over lazy dogs in the summer evening."
}
#分词结果：数字2被过滤，Quick小写处理， brown-foxes被切分为 brown，foxes
{
"tokens" : [
{
"token" : "running",
"start_offset" : 2,
"end_offset" : 9,
"type" : "word",
"position" : 0
},
{
"token" : "quick",
"start_offset" : 10,
"end_offset" : 15,
"type" : "word",
"position" : 1
},
{
"token" : "brown",
"start_offset" : 16,
"end_offset" : 21,
"type" : "word",
"position" : 2
},
{
"token" : "foxes",
"start_offset" : 22,
"end_offset" : 27,
"type" : "word",
"position" : 3
},
{
"token" : "leap",
"start_offset" : 28,
"end_offset" : 32,
"type" : "word",
"position" : 4
},
{
"token" : "over",
"start_offset" : 33,
"end_offset" : 37,
"type" : "word",
"position" : 5
},
{
"token" : "lazy",
"start_offset" : 38,
"end_offset" : 42,
"type" : "word",
"position" : 6
},
{
"token" : "dogs",
"start_offset" : 43,
"end_offset" : 47,
"type" : "word",
"position" : 7
},
{
"token" : "in",
"start_offset" : 48,
"end_offset" : 50,
"type" : "word",
"position" : 8
},
{
"token" : "the",
"start_offset" : 51,
"end_offset" : 54,
"type" : "word",
"position" : 9
},
{
"token" : "summer",
"start_offset" : 55,
"end_offset" : 61,
"type" : "word",
"position" : 10
},
{
"token" : "evening",
"start_offset" : 62,
"end_offset" : 69,
"type" : "word",
"position" : 11
}
]
}
- Stop Analyzer：停用词过滤（is/a/the），小写处理。
#stop
GET _analyze
{
"analyzer": "stop",
"text": "2 running Quick brown-foxes leap over lazy dogs in the summer evening."
}
#分词结果：2，in，the被过滤，Quick小写处理， brown-foxes被切分为 brown，foxes
{
"tokens" : [
{
"token" : "running",
"start_offset" : 2,
"end_offset" : 9,
"type" : "word",
"position" : 0
},
{
"token" : "quick",
"start_offset" : 10,
"end_offset" : 15,
"type" : "word",
"position" : 1
},
{
"token" : "brown",
"start_offset" : 16,
"end_offset" : 21,
"type" : "word",
"position" : 2
},
{
"token" : "foxes",
"start_offset" : 22,
"end_offset" : 27,
"type" : "word",
"position" : 3
},
{
"token" : "leap",
"start_offset" : 28,
"end_offset" : 32,
"type" : "word",
"position" : 4
},
{
"token" : "over",
"start_offset" : 33,
"end_offset" : 37,
"type" : "word",
"position" : 5
},
{
"token" : "lazy",
"start_offset" : 38,
"end_offset" : 42,
"type" : "word",
"position" : 6
},
{
"token" : "dogs",
"start_offset" : 43,
"end_offset" : 47,
"type" : "word",
"position" : 7
},
{
"token" : "summer",
"start_offset" : 55,
"end_offset" : 61,
"type" : "word",
"position" : 10
},
{
"token" : "evening",
"start_offset" : 62,
"end_offset" : 69,
"type" : "word",
"position" : 11
}
]
}
- WhiteSpace Analyzer：按照空格切分，不转小写。
#whitespace
GET _analyze
{
"analyzer": "whitespace",
"text": "2 running Quick brown-foxes leap over lazy dogs in the summer evening."
}
#分词结果：按空格切分
{
"tokens" : [
{
"token" : "2",
"start_offset" : 0,
"end_offset" : 1,
"type" : "word",
"position" : 0
},
{
"token" : "running",
"start_offset" : 2,
"end_offset" : 9,
"type" : "word",
"position" : 1
},
{
"token" : "Quick",
"start_offset" : 10,
"end_offset" : 15,
"type" : "word",
"position" : 2
},
{
"token" : "brown-foxes",
"start_offset" : 16,
"end_offset" : 27,
"type" : "word",
"position" : 3
},
{
"token" : "leap",
"start_offset" : 28,
"end_offset" : 32,
"type" : "word",
"position" : 4
},
{
"token" : "over",
"start_offset" : 33,
"end_offset" : 37,
"type" : "word",
"position" : 5
},
{
"token" : "lazy",
"start_offset" : 38,
"end_offset" : 42,
"type" : "word",
"position" : 6
},
{
"token" : "dogs",
"start_offset" : 43,
"end_offset" : 47,
"type" : "word",
"position" : 7
},
{
"token" : "in",
"start_offset" : 48,
"end_offset" : 50,
"type" : "word",
"position" : 8
},
{
"token" : "the",
"start_offset" : 51,
"end_offset" : 54,
"type" : "word",
"position" : 9
},
{
"token" : "summer",
"start_offset" : 55,
"end_offset" : 61,
"type" : "word",
"position" : 10
},
{
"token" : "evening.",
"start_offset" : 62,
"end_offset" : 70,
"type" : "word",
"position" : 11
}
]
}
- Keyword Analyzer：不分词，直接将输入当作输出。
#keyword
GET _analyze
{
"analyzer": "keyword",
"text": "2 running Quick brown-foxes leap over lazy dogs in the summer evening."
}
#分词结果：
{
"tokens" : [
{
"token" : "2 running Quick brown-foxes leap over lazy dogs in the summer evening.",
"start_offset" : 0,
"end_offset" : 70,
"type" : "word",
"position" : 0
}
]
}
- Pattern Analyzer：正则表达式分词，默认\W+（非字符分隔）。
#pattern
GET _analyze
{
"analyzer": "pattern",
"text": "2 running Quick brown-foxes leap over lazy dogs in the summer evening."
}
#分词结果：
{
"tokens" : [
{
"token" : "2",
"start_offset" : 0,
"end_offset" : 1,
"type" : "word",
"position" : 0
},
{
"token" : "running",
"start_offset" : 2,
"end_offset" : 9,
"type" : "word",
"position" : 1
},
{
"token" : "quick",
"start_offset" : 10,
"end_offset" : 15,
"type" : "word",
"position" : 2
},
{
"token" : "brown",
"start_offset" : 16,
"end_offset" : 21,
"type" : "word",
"position" : 3
},
{
"token" : "foxes",
"start_offset" : 22,
"end_offset" : 27,
"type" : "word",
"position" : 4
},
{
"token" : "leap",
"start_offset" : 28,
"end_offset" : 32,
"type" : "word",
"position" : 5
},
{
"token" : "over",
"start_offset" : 33,
"end_offset" : 37,
"type" : "word",
"position" : 6
},
{
"token" : "lazy",
"start_offset" : 38,
"end_offset" : 42,
"type" : "word",
"position" : 7
},
{
"token" : "dogs",
"start_offset" : 43,
"end_offset" : 47,
"type" : "word",
"position" : 8
},
{
"token" : "in",
"start_offset" : 48,
"end_offset" : 50,
"type" : "word",
"position" : 9
},
{
"token" : "the",
"start_offset" : 51,
"end_offset" : 54,
"type" : "word",
"position" : 10
},
{
"token" : "summer",
"start_offset" : 55,
"end_offset" : 61,
"type" : "word",
"position" : 11
},
{
"token" : "evening",
"start_offset" : 62,
"end_offset" : 69,
"type" : "word",
"position" : 12
}
]
}
- Language：提供了30多种常见语言的分词器。
#english
GET _analyze
{
"analyzer": "english",
"text": "2 running Quick brown-foxes leap over lazy dogs in the summer evening."
}
#分词结果：running转为run，Quick转为quick，brown-foxes 转为brown、fox，in、the过滤等等
{
"tokens" : [
{
"token" : "2",
"start_offset" : 0,
"end_offset" : 1,
"type" : "<NUM>",
"position" : 0
},
{
"token" : "run",
"start_offset" : 2,
"end_offset" : 9,
"type" : "<ALPHANUM>",
"position" : 1
},
{
"token" : "quick",
"start_offset" : 10,
"end_offset" : 15,
"type" : "<ALPHANUM>",
"position" : 2
},
{
"token" : "brown",
"start_offset" : 16,
"end_offset" : 21,
"type" : "<ALPHANUM>",
"position" : 3
},
{
"token" : "fox",
"start_offset" : 22,
"end_offset" : 27,
"type" : "<ALPHANUM>",
"position" : 4
},
{
"token" : "leap",
"start_offset" : 28,
"end_offset" : 32,
"type" : "<ALPHANUM>",
"position" : 5
},
{
"token" : "over",
"start_offset" : 33,
"end_offset" : 37,
"type" : "<ALPHANUM>",
"position" : 6
},
{
"token" : "lazi",
"start_offset" : 38,
"end_offset" : 42,
"type" : "<ALPHANUM>",
"position" : 7
},
{
"token" : "dog",
"start_offset" : 43,
"end_offset" : 47,
"type" : "<ALPHANUM>",
"position" : 8
},
{
"token" : "summer",
"start_offset" : 55,
"end_offset" : 61,
"type" : "<ALPHANUM>",
"position" : 11
},
{
"token" : "even",
"start_offset" : 62,
"end_offset" : 69,
"type" : "<ALPHANUM>",
"position" : 12
}
]
}
- Custom Analyzer：自定义分词器。
#需要安装analysis-icu插件
POST _analyze
{
"analyzer": "icu_analyzer",
"text": "他说的确实在理”"
}
#返回结果
{
"tokens" : [
{
"token" : "他",
"start_offset" : 0,
"end_offset" : 1,
"type" : "<IDEOGRAPHIC>",
"position" : 0
},
{
"token" : "说的",
"start_offset" : 1,
"end_offset" : 3,
"type" : "<IDEOGRAPHIC>",
"position" : 1
},
{
"token" : "确实",
"start_offset" : 3,
"end_offset" : 5,
"type" : "<IDEOGRAPHIC>",
"position" : 2
},
{
"token" : "在",
"start_offset" : 5,
"end_offset" : 6,
"type" : "<IDEOGRAPHIC>",
"position" : 3
},
{
"token" : "理",
"start_offset" : 6,
"end_offset" : 7,
"type" : "<IDEOGRAPHIC>",
"position" : 4
}
]
}
中文分词比较：
POST _analyze
{
"analyzer": "standard",
"text": "他说的确实在理”"
}
#返回结果
{
"tokens" : [
{
"token" : "他",
"start_offset" : 0,
"end_offset" : 1,
"type" : "<IDEOGRAPHIC>",
"position" : 0
},
{
"token" : "说",
"start_offset" : 1,
"end_offset" : 2,
"type" : "<IDEOGRAPHIC>",
"position" : 1
},
{
"token" : "的",
"start_offset" : 2,
"end_offset" : 3,
"type" : "<IDEOGRAPHIC>",
"position" : 2
},
{
"token" : "确",
"start_offset" : 3,
"end_offset" : 4,
"type" : "<IDEOGRAPHIC>",
"position" : 3
},
{
"token" : "实",
"start_offset" : 4,
"end_offset" : 5,
"type" : "<IDEOGRAPHIC>",
"position" : 4
},
{
"token" : "在",
"start_offset" : 5,
"end_offset" : 6,
"type" : "<IDEOGRAPHIC>",
"position" : 5
},
{
"token" : "理",
"start_offset" : 6,
"end_offset" : 7,
"type" : "<IDEOGRAPHIC>",
"position" : 6
}
]
}
ElasticSearch（三）：通分词器（Analyzer）进行分词（Analysis）的更多相关文章
- Elasticsearch(10) --- 内置分词器、中文分词器
Elasticsearch(10) --- 内置分词器.中文分词器 这篇博客主要讲:分词器概念.ES内置分词器.ES中文分词器. 一.分词器概念 1.Analysis 和 Analyzer Analy ...
- ElasticSearch7.3 学习之倒排索引揭秘及初识分词器(Analyzer)
一.倒排索引 1. 构建倒排索引 例如说有下面两个句子doc1,doc2 doc1:I really liked my small dogs, and I think my mom also like ...
- es的分词器analyzer
analyzer 分词器使用的两个情形: 1,Index time analysis. 创建或者更新文档时,会对文档进行分词2,Search time analysis. 查询时,对查询语句 ...
- Lucene.net(4.8.0)+PanGu分词器问题记录一:分词器Analyzer的构造和内部成员ReuseStategy
前言:目前自己在做使用Lucene.net和PanGu分词实现全文检索的工作,不过自己是把别人做好的项目进行迁移.因为项目整体要迁移到ASP.NET Core 2.0版本,而Lucene使用的版本是3 ...
- Lucene.net(4.8.0) 学习问题记录一:分词器Analyzer的构造和内部成员ReuseStategy
前言:目前自己在做使用Lucene.net和PanGu分词实现全文检索的工作,不过自己是把别人做好的项目进行迁移.因为项目整体要迁移到ASP.NET Core 2.0版本,而Lucene使用的版本是3 ...
- Elasticsearch修改分词器以及自定义分词器
Elasticsearch修改分词器以及自定义分词器 参考博客:https://blog.csdn.net/shuimofengyang/article/details/88973597
- 【Lucene3.6.2入门系列】第05节_自定义停用词分词器和同义词分词器
首先是用于显示分词信息的HelloCustomAnalyzer.java package com.jadyer.lucene; import java.io.IOException; import j ...
- Lucene学习-深入Lucene分词器,TokenStream获取分词详细信息
Lucene学习-深入Lucene分词器,TokenStream获取分词详细信息 在此回复牛妞的关于程序中分词器的问题,其实可以直接很简单的在词库中配置就好了,Lucene中分词的所有信息我们都可以从 ...
- 自然语言处理之中文分词器－jieba分词器详解及python实战
(转https://blog.csdn.net/gzmfxy/article/details/78994396) 中文分词是中文文本处理的一个基础步骤,也是中文人机自然语言交互的基础模块,在进行中文自 ...
- 【ELK】【docker】【elasticsearch】2.使用elasticSearch+kibana+logstash+ik分词器+pinyin分词器+繁简体转化分词器 6.5.4 启动 ELK+logstash概念描述
官网地址:https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#docker-cli-run-prod ...
随机推荐
- 记一次客户DB CPU短时间内冲高至99%处理
问题背景: 客户反映DB CPU短时间内冲高,查询变得缓慢,记录此背景下的处理方式 1> 查看系统负载及相关sql 2> 查看相关sql的执行计划 3> 想看相关sql的执行计划是否 ...
- Tomcat7.0.40注册到服务启动报错error Code 1 +connector attribute sslcertificateFile must be defined when using ssl with apr
Tomcat7.0.40 注册到服务启动遇到以下几个问题: 1.启动报错errorCode1 查看日志如下图: 解决办法: 这个是因为我的jdk版本问题,因为电脑是64位,安装的jdk是32位的所以会 ...
- python编程基础之十八
字符串的查找和替换常用函数: str.count(sub,start = 0,end = len(str)) 计算sub 在str中出现的次数,[start,end)寻找区间 str.find(str ...
- POJ1017&&UVA311 Packets(中文题面版)
感谢有道翻译--- Description A工厂生产的产品是用相同高度h的方形包装,尺寸为1* 1,2 * 2,3 * 3,4 * 4,5 * 5,6 6.这些产品总是以与产品高度h相同,尺寸为66 ...
- Java总结---继承（不断完善ing..）
java三大特性:封装.继承.多态 继承 一.目的:实现代码的复用 二.简单例子(A继承了C): public class A extends C { //检测哪些可以在子类里使用 public vo ...
- 实验吧之【简单的sql注入 1、2、3】
实验吧的三道sql注入(感觉实验吧大部分web都是注入) 简单的SQL注入 地址:http://ctf5.shiyanbar.com/423/web/ 这道题也是sql注入,输入1,页面显示正常,输出 ...
- 初识域渗透利器Empire
Empire 是一款类似Metasploit 的渗透测试框架,基于python 编写,Empire是一个纯粹的PowerShell 后开发代理,建立在密码安全通信和灵活的架构上.Empire 实现了无 ...
- Zeppelin的安装和SparkSQL使用总结
zeppelin是spark的web版本notebook编辑器,相当于ipython的notebook编辑器. 一Zeppelin安装 (前提是spark已经安装好) 1 下载https://zepp ...
- NodeJS操作MongoDB数据库
一.node.js对于mongodb的基本操作 1.数据库的开机 首先我们要先对数据库进行开机的操作,建立一个文件夹用于存放数据库文档.如D:\mongo,接下去在cmd当中键入命令-> mon ...
- 概念理解：boost::asio::io_service
IO模型 io_service对象是asio框架中的调度器,所有异步io事件都是通过它来分发处理的(io对象的构造函数中都需要传入一个io_service对象). asio::io_service i ...