安装Elasticsearch
Elasticsearch 8.5.2 点此下载
本机win10系统，下载解压后，直接双击bin/elasticsearch.bat 启动，启动时会显示用户名和密码，以及Kibana初始配置所使用的token.
-> Elasticsearch security features have been automatically configured!
-> Authentication is enabled and cluster connections are encrypted.
-> Password for the elastic user (reset with `bin/elasticsearch-reset-password -u elastic`):
CrkpwVRUn5u2do5IgZ9C
-> HTTP CA certificate SHA-256 fingerprint:
4d096912ddfa36cc6b57efece319bc597865e6c820c158aeea2922534773184e
-> Configure Kibana to use this cluster:
* Run Kibana and click the configuration link in the terminal when Kibana starts.
* Copy the following enrollment token and paste it into Kibana in your browser (valid for the next 30 minutes):
eyJ2ZXIiOiI4LjQuMyIsImFkciI6WyIxOTguMTguMC4xOjkyMDAiXSwiZmdyIjoiNGQwOTY5MTJkZGZhMzZjYzZiNTdlZmVjZTMxOWJjNTk3ODY1ZTZjODIwYzE1OGFlZWEyOTIyNTM0NzczMTg0ZSIsImtleSI6IlB4NWR3WVFCYi14OHVoNGt0Tmd5OlQ4LUs4ZWFjUWJLLVpiTTNIUmpVb3cifQ==
-> Configure other nodes to join this cluster:
* On this node:
- Create an enrollment token with `bin/elasticsearch-create-enrollment-token -s node`.
- Uncomment the transport.host setting at the end of config/elasticsearch.yml.
- Restart Elasticsearch.
* On other nodes:
- Start Elasticsearch with `bin/elasticsearch --enrollment-token <token>`, using the enrollment token that you generated.
这玩意只有第一次启动时会打印，如果忘记用户名密码，可以通过工具重置。
D:\tools\elasticsearch-8.5.2\bin>elasticsearch-reset-password.bat -u elastic
warning: ignoring JAVA_HOME=D:\tools\JDK\17; using bundled JDK
This tool will reset the password of the [elastic] user to an autogenerated value.
The password will be printed in the console.
Please confirm that you would like to continue [y/N]y
Password for the [elastic] user successfully reset.
New value: QC68LA4-9Au5Ks_5lXl1
Kibana 安装配置
Kibana 8.5.2 点此下载
下载解压即可，为了让界面显示中文，需要在config/kibana.yml文件中添加一行配置：i18n.locale: "zh-CN"
双击bin/kibana.bat 启动Kibana.
首次启动时会生成带code的链接，复制该链接到浏览器打开，填写elasticsearch启动时生成的token，即可完成配置。
点开左边的菜单栏，向下划动，选择Management->开发工具(dev tools)。即可进入开发调试页面，调用Elasticsearch API进行测试。
移动到某一行命令时，当前行右上解会显示三角形按钮，点击按钮可执行当前的命令。
使用Postman访问Elasticsearch
Postman也是一种常用来测试Elasticsearch API的方式，使用Postman调用Elasticsearch的rest api需要进行身份认证。点开Postman的Authorization栏选择使用Basic Auth,设置Elasticsearch用户名/密码。如下图所示：
使用https://127.0.0.1:9200 获取版本信息，可以看到调用成功。
中文分词插件
默认情况下，Elasticsearch中文分词是一个字一个字的拆分的。尝试下面命令
GET _analyze
{
"text": "上海东方明珠",
"tokenizer": "standard"
}
得到的结果：
上、海、东、方、明、珠
这没有任任意义，想要得到有意义的分词结果，需要安装中文分词插件，目前使用最广泛的中文分词插件为IK.点此下载 v8.4.3
- 下载后解压将目录拷贝到elasticsearch的plugin目录下
- 修改plugin-descriptor.properties文件，将elasticsearch.version配置项改成你所使用的版本，我这里是8.5.2
- 重启elasticsearch即可生效
tokenizer支持两种类型：ik_smart , ik_max_word
- ik_max_word:尽量匹配更多的词组,会穷尽各种可能的组合,适合Term Query
- ik_smart:智能分析应该提取哪些有意义的词语,适合Phrase查询
测试一下效果：
GET _analyze
{
"text": "上海东方明珠",
"tokenizer": "ik_smart"
}
返回结果：
上海、东方明珠
GET _analyze
{
"text": "上海东方明珠",
"tokenizer": "ik_max_word"
}
返回结果 ：
上海、海东、东方明珠、东方、明珠
使用API管理索引
创建索引
POST my_index/_doc/1
{
"user_id":"1",
"user_name":"cody",
"city":"shanghai",
"province":"shanghai",
"country":"china"
}
查询索引：
GET /my_index/_doc/1
根据主键修改索引
PUT my_index/_doc/1
{
"user_id":"1",
"user_name":"andy",
"city":"shanghai",
"province":"shanghai",
"country":"china"
}
通过查询修改索引
POST /my_index/_update_by_query
{
"query": {
"match": {
"user_name": "andy"
}
},
"script": {
"source": "ctx._source.city=params.city;ctx._source.province=params.province;ctx._source.country=params.country",
"lang": "painless",
"params": {
"city":"上海",
"province":"上海",
"country":"中国"
}
}
}
列出所有索引
GET /_cat/indices
yellow open my_index Syr-XvB-QCm0bAabXg-t7Q 1 1 1 2 32.2kb 32.2kb
删除索引
DELETE my_index
批量插入索引
POST _bulk
{"index":{"_index":"my_index"}}
{"user_id":"1","user_name":"上海浦东刘一","age":"24","city":"上海","province":"上海","country":"中国","address":"上海市浦东新区东方明珠","location":{"lat":"13.234321","lon":"141.234867"}}
{"index":{"_index":"my_index"}}
{"user_id":"1","user_name":"上海浦东陈二","age":"32","city":"上海","province":"上海","country":"中国","address":"上海市浦东新区世纪公园","location":{"lat":"13.256321","lon":"141.345121"}}
{"index":{"_index":"my_index"}}
{"user_id":"1","user_name":"上海黄浦张三","age":"36","city":"上海","province":"上海","country":"中国","address":"上海市黄浦区人民广场","location":{"lat":"13.247311","lon":"141.423126"}}
{"index":{"_index":"my_index"}}
{"user_id":"2","user_name":"湖南株洲李四","age":"27","city":"株洲","province":"湖南","country":"中国","address":"湖南省株洲市荷塘区流芳公园","location":{"lat":"14.0642","lon":"61.234809"}}
{"index":{"_index":"my_index"}}
{"user_id":"2","user_name":"湖南长沙王五","age":"45","city":"长沙","province":"湖南","country":"中国","address":"湖南省长沙市岳麓区橘子洲","location":{"lat":"17.345003","lon":"67.346821"}}
{"index":{"_index":"my_index"}}
{"user_id":"2","user_name":"湖南长沙赵六","age":"51","city":"长沙","province":"湖南","country":"中国","address":"湖南省长沙市芙蓉区马王堆","location":{"lat":"16.245307","lon":"71.234569"}}
查询所有数据
GET my_index/_search
查看索引结构定义mapping
GET my_index/_mapping
由查询的结果可知，插入索引时自动生成的mapping中，location的类型并不是地理信息类型，所以我们需要自定义mapping。
自定义索引结构mapping
将location设置为geo_point类型。
PUT my_index
PUT my_index/_mapping
{
"properties": {
"location": {
"type": "geo_point"
},
"address": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"uid": {
"type": "long"
},
"age": {
"type": "short"
},
"city": {
"type": "keyword"
},
"province": {
"type": "keyword"
},
"country": {
"type": "keyword"
}
}
}
索引简单查询
GET my_index/_search
{
"query":{
"match":{
"city":"上海"
}
}
}
查询得到三条数据。
逻辑与（and）查询：
GET my_index/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"province": "湖南"
}
},
{
"match": {
"city": "长沙"
}
}
]
}
}
}
查询得到两条数据。
逻辑或(or)查询：
GET my_index/_search
{
"query": {
"bool": {
"should": [
{
"match": {
"city": "株洲"
}
},
{
"match": {
"city": "长沙"
}
}
]
}
}
}
逻辑非(not)查询：
GET my_index/_search
{
"query": {
"bool": {
"must_not": [
{
"match": {
"city": "株洲"
}
}
]
}
}
}
范围查询
查询年龄30到50之间的记录
GET my_index/_search
{
"query": {
"range": {
"age": {
"gte": 30,
"lte": 50
}
}
}
}
地理位置按距离查询
距离指定地址5KM以内只有一条记录
GET my_index/_search
{
"query":{
"match":{
"city":"上海"
}
},
"post_filter": {
"geo_distance": {
"distance": "5km",
"location": {
"lat": 13.245,
"lon": 141.254
}
}
}
}
上海浦东刘一
距离指定地址20KM以内有三条记录
GET my_index/_search
{
"query":{
"match":{
"city":"上海"
}
},
"post_filter": {
"geo_distance": {
"distance": "20km",
"location": {
"lat": 13.245,
"lon": 141.254
}
}
}
}
上海浦东刘一、上海浦东陈二、上海黄浦张三
按距离排序
按距离倒序排列，看看谁距离最远
GET my_index/_search
{
"query": {
"match": {
"city": "上海"
}
},
"post_filter": {
"geo_distance": {
"distance": "20km",
"location": {
"lat": 13.245,
"lon": 141.254
}
}
},
"sort": [
{"_geo_distance": {
"location": {
"lat": 13.245,
"lon": 141.254
},
"order": "desc"
}}
]
}
上海黄浦张三
聚合统计
按年龄区间统计
GET my_index/_search
{
"size":0,
"aggs":{
"age":{
"range": {
"field": "age",
"ranges": [
{
"from": 20,
"to": 30
},{
"from": 30,
"to": 40
},{
"from": 40,
"to": 50
}
]
}
}
}
}
湖南省按城市分组统计
GET my_index/_search
{
"query": {
"match": {
"province": "湖南"
}
},
"size":0,
"aggs":{
"city_aggs":{
"terms": {
"field": "city",
"size": 10
}
}
}
}
