ElasticSearch 是强大的搜索工具，并且是ELK套件的重要组成部分
好记性不如乱笔头，这次是在windows环境下搭建es中文分词搜索测试环境，步骤如下
1、安装jdk1.8，配置好环境变量
2、下载ElasticSearch7.1.1，版本变化比较快，刚才看了下最新版已经是7.2.0，本环境基于7.1.1搭建，下载地址https://www.elastic.co/cn/downloads/elasticsearch，得到一个zip压缩包，解压缩后cmd下运行下面的命令即可启动ES
./bin/elasticsearch.bat
正常启动的话提示符下回输出一些日志记录
浏览器中输入http://localhost:9200/测试服务是否能够正常访问，正常情况会显示下面的概要信息，说明ES搭建成功
3、ElasticSearch 虽然提供了强大Restful接口，但没有一个UI界面操作起来不是很直观，elasticsearch-head很好的解决这个问题，elasticsearch-head是基于node的一个工具，通过连接ES服务提供可视化展示界面，详细参考：
https://github.com/mobz/elasticsearch-head，安装步骤也是很简单，如下
git clone git://github.com/mobz/elasticsearch-head.git
cd elasticsearch-head
npm install
npm run start
服务正常启动后显示界面如下
浏览器中输入http://localhost:9100/可以看到对应UI
4、中文分词插件详细介绍见https://github.com/medcl/elasticsearch-analysis-ik，注意版本不要选错，否则会按照失败，es7.1.1选择对应版本，安装步骤如下：
./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.1.1/elasticsearch-analysis-ik-7.1.1.zip
5、测试中文分词检索功能，先建立索引，在postman或者elasticsearch-head中发送如下请求
--创建索引
curl -XPUT http://localhost:9200/news --索引中添加数据
curl -XPOST http://localhost:9200/news/_create/1 -H 'Content-Type:application/json' -d'
{"content":"美国留给伊拉克的是个烂摊子吗"}
'
添加的数据如下
添加索引映射
curl -XPOST http://localhost:9200/news/_mapping -H 'Content-Type:application/json' -d'
{
"properties": {
"content": {
"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
}
} }'
ik_max_word ik_smart两者的区别
ik_max_word: 会将文本做最细粒度的拆分，比如会将“*国歌”拆分为“*,中华人民,中华,华人,人民*,人民,人,民,*,共和,和,国国,国歌”，会穷尽各种可能的组合，适合 Term Query；
ik_smart: 会做最粗粒度的拆分，比如会将“*国歌”拆分为“*,国歌”，适合 Phrase 查询。
测试示例：
http://localhost:9200/_analyze，通过ik_max_word分词，结果如下
输入
{"text":"*人民大会堂","analyzer":"ik_max_word" }
输出
{
"tokens": [
{
"token": "*",
"start_offset": 0,
"end_offset": 7,
"type": "CN_WORD",
"position": 0
},
{
"token": "中华人民",
"start_offset": 0,
"end_offset": 4,
"type": "CN_WORD",
"position": 1
},
{
"token": "中华",
"start_offset": 0,
"end_offset": 2,
"type": "CN_WORD",
"position": 2
},
{
"token": "华人",
"start_offset": 1,
"end_offset": 3,
"type": "CN_WORD",
"position": 3
},
{
"token": "人民*",
"start_offset": 2,
"end_offset": 7,
"type": "CN_WORD",
"position": 4
},
{
"token": "人民",
"start_offset": 2,
"end_offset": 4,
"type": "CN_WORD",
"position": 5
},
{
"token": "*",
"start_offset": 4,
"end_offset": 7,
"type": "CN_WORD",
"position": 6
},
{
"token": "共和",
"start_offset": 4,
"end_offset": 6,
"type": "CN_WORD",
"position": 7
},
{
"token": "国人",
"start_offset": 6,
"end_offset": 8,
"type": "CN_WORD",
"position": 8
},
{
"token": "人民大会堂",
"start_offset": 7,
"end_offset": 12,
"type": "CN_WORD",
"position": 9
},
{
"token": "人民大会",
"start_offset": 7,
"end_offset": 11,
"type": "CN_WORD",
"position": 10
},
{
"token": "人民",
"start_offset": 7,
"end_offset": 9,
"type": "CN_WORD",
"position": 11
},
{
"token": "大会堂",
"start_offset": 9,
"end_offset": 12,
"type": "CN_WORD",
"position": 12
},
{
"token": "大会",
"start_offset": 9,
"end_offset": 11,
"type": "CN_WORD",
"position": 13
},
{
"token": "会堂",
"start_offset": 10,
"end_offset": 12,
"type": "CN_WORD",
"position": 14
}
]
}
如果输入
{"text":"*人民大会堂","analyzer":"ik_smart" }
输出
{
"tokens": [
{
"token": "*",
"start_offset": 0,
"end_offset": 7,
"type": "CN_WORD",
"position": 0
},
{
"token": "人民大会堂",
"start_offset": 7,
"end_offset": 12,
"type": "CN_WORD",
"position": 1
}
]
}
根据分词检索输入语法，请求url：http://localhost:9200/news/_search
输入：
{
"query" : { "match" : { "content" : "*国歌" }},
"highlight" : {
"pre_tags" : ["<tag1>", "<tag2>"],
"post_tags" : ["</tag1>", "</tag2>"],
"fields" : {
"content" : {}
}
}
}
输出：
{
"took": 11,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 1.6810182,
"hits": [
{
"_index": "news",
"_type": "_doc",
"_id": "6",
"_score": 1.6810182,
"_source": {
"content": "中华民族国歌"
},
"highlight": {
"content": [
"<tag1>中华</tag1>民族<tag1>国歌</tag1>"
]
}
},
{
"_index": "news",
"_type": "_doc",
"_id": "5",
"_score": 0.9426802,
"_source": {
"content": "人民公社"
},
"highlight": {
"content": [
"<tag1>人民</tag1>公社"
]
}
}
]
}
}
运行效果如下
