安装

docker 安装 es

#新建es的config配置⽂件夹
mkdir -p /data/elasticsearch/config
#新建es的data⽬录
mkdir -p /data/elasticsearch/data
#新建es的plugins⽬录
mkdir -p /data/elasticsearch/plugins
#给⽬录设置权限
chmod 777 -R /data/elasticsearch
#写⼊配置到elasticsearch.yml中， 下⾯的 > 表示覆盖的⽅式写⼊， >>表示追加的⽅式写⼊，但是要确
echo "http.host: 0.0.0.0" >> /data/elasticsearch/config/elasticsearch.yml
#安装es
docker run --name elasticsearch -p 9200:9200 -p 9300:9300 \
-e "discovery.type=single-node" \
-e ES_JAVA_OPTS="-Xms128m -Xmx256m" \
-v /data/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml \
-v /data/elasticsearch/data:/usr/share/elasticsearch/data \
-v /data/elasticsearch/plugins:/usr/share/elasticsearch/plugins \
-d elasticsearch:7.10.1

docker安装kibana

docker run -d  --name kibana -e ELASTICSEARCH_HOSTS="http://172.19.141.58:9200" -p 5601:5601 kibana:7.10.1

命令执行

mapping

# 创建/修改 mapping
PUT my_index
{
  "mappings": {
    "properties": {
      "name": { 
        "type": "text",
        "analyzer": "ik_smart"
      }
    }
  }
}
PUT my_index/_mapping
{
  "properties": {
    "name": { 
      "type": "text",
      "analyzer": "ik_smart"
    }
  }
}

新增

# 创建索引
POST /users/_doc/1
{
  "name": "sni",
  "age": 21
}

查询

# 查询所有索引
GET /_cat/indices
# 获取users索引的详情
GET /users
# 获取id=1的索引的数据内容详细信息
GET /users/_doc/1
# 获取id=1的索引的数据内容
GET /users/_source/1

删除

# 删除id=1的数据
DELETE /users/_doc/1
# 删除索引
DELETE /users

修改

# 修改: 数据没有产生变动则不做处理
POST /users/_update/1
{
  "doc": {
    "age": 22
  }
}
# 修改: 数据没有产生变动 也执行处理
POST /users/_doc/1
{
  "age": 22
}

搜索-分词

# 根据条件搜索
GET /users/_search
{
  "query": {
    "match_all": {}
  }
}

模糊匹配

不区分大小写

# field = address 模糊匹配 street
GET /users/_search
{
 "query": {
   "match": {
       "address": "street"
   }
 }
}

精确匹配

GET /users/_search
{
 "query": {
 "match_phrase": {
   "address": "Madison street"
   }
     }
}

多字段模糊匹配

POST resume/_doc/12
{
 "title": "后端⼯程师",
 "desc": "多年go语⾔开发经验， 熟悉go的基本语法， 熟悉常⽤的go语⾔库",
 "want_learn":"python语⾔"
}
POST resume/_doc/13
{
 "title": "go⼯程师",
 "desc": "多年开发经验",
 "want_learn":"java语⾔"
}
POST resume/_doc/14
{
 "title": "后端⼯程师",
 "desc": "多年开发经验",
 "want_learn":"rust语⾔"
}
# title desc 模糊匹配
GET /resume/_search
{
 "query": {
 "multi_match": {
   "query": "go",
   "fields": ["title", "desc"]
   }
 }
}
# 增加字段权重 ^num
GET /resume/_search
{
 "query": {
 "multi_match": {
   "query": "go",
   "fields": ["title^2", "desc"]
   }
 }
}

match_all

GET /users/_search
{
  "query": {
    "match_all": {}
  }
}

搜索

term

精确查询

注意：当条件输入有大写字母时无法搜索出数据

GET /users/_search
{
 "query": {
   "term": {
   "address": "madison street"
   }
 }
}

范围查询

# 年龄大于等于20 小于等于30
GET user/_search
{
 "query":{
   "range": {
     "age": {
     "gte": 20,
     "lte": 30
     }
       }
   }
}

exists

# 查询所以存在age字段的数据
GET user/_search
{
 "query": {
 "exists": {
 "field": "age"
 }
 }
}

fuzzy模糊查询

# fuzzy模糊查询 拼错单词可以纠错 streat -> street
GET /users/_search
{
  "query": {
    "fuzzy": {
      "address": "streat"
    }
  }
}
# 在match中开启纠错
GET users/_search
{
  "query": {
    "match": {
      "address": {
        "query": "streat",
        "fuzziness": 1
      }
    }
  }  
}

复合搜索

# must: 必须匹配,查询上下⽂,加分
# should: 应该匹配,查询上下⽂,加分
# must_not: 必须不匹配,过滤上下⽂,过滤
# filter: 必须匹配,过滤上下⽂,过滤
GET /users/_search
{
  "query":{
    "bool":{
      "must":[
      ],
      "should":[
      ],
      "must_not":[
      ],
      "filter":[
      ],
    }
  }
}

示例

GET /users/_search
{
  "query":{
    "bool":{
      "must":[
        {
          "term": {
            "state": "tn"
          }
        },
        {
          "range": {
            "age": {
              "gte": 20,
              "lte": 30
            }
          }
        }
      ],
      "should": [
         {
           "match": {
              "firstname": "Decker"
            }
         }
      ],
      "must_not":[
        {
          "term": {
            "gender": "male"
          }
        }
      ],
      "filter":[
        {
         "range": {
           "age": {
             "gte": 25,
             "lte": 30
            }
         }
        }
      ]
    }
  }
}

批量操作

# 批量操作
POST _bulk
{ "index" : { "_index" : "test", "_id" : "1" } }
{ "field1" : "value1" }
{ "delete" : { "_index" : "test", "_id" : "2" } }
{ "create" : { "_index" : "test", "_id" : "3" } }
{ "field1" : "value3" }
{ "update" : {"_id" : "1", "_index" : "test"} }
{ "doc" : {"field2" : "value2"} }

批量导入数据

mock数据：https://mxshop-files.oss-cn-hangzhou.aliyuncs.com/accounts.json

# 批量导入
POST /users/_bulk
{"index":{"_id":"1"}}
{"account_number":1,"balance":39225,"firstname":"Amber","lastname":"Duke","age":32,"gender":"M","address":"880 Holmes Lane","employer":"Pyrami","email":"amberduke@pyrami.com","city":"Brogan","state":"IL"}
{"index":{"_id":"6"}}
{"account_number":6,"balance":5686,"firstname":"Hattie","lastname":"Bond","age":36,"gender":"M","address":"671 Bristol Street","employer":"Netagy","email":"hattiebond@netagy.com","city":"Dante","state":"TN"}
{"index":{"_id":"13"}}
{"account_number":13,"balance":32838,"firstname":"Nanette","lastname":"Bates","age":28,"gender":"F","address":"789 Madison Street","employer":"Quility","email":"nanettebates@quility.com","city":"Nogal","state":"VA"}
{"index":{"_id":"18"}}
{"account_number":18,"balance":4180,"firstname":"Dale","lastname":"Adams","age":33,"gender":"M","address":"467 Hutchinson Court","employer":"Boink","email":"daleadams@boink.com","city":"Orick","state":"MD"}

批量查询数据

# 批量查询
# index = users
# index = account
GET /_mget
{
 "docs": [
   {
   "_index": "users",
   "_id": "1"
   },
   {
   "_index": "account",
   "_id": "2"
   }
 ]
}