elasticsearch练习

最近在学习elasticsearch,做了一些练习，分享下练习成果，es基于6.7.2，用kibana处理DSL，有兴趣的伙伴可以自己试试

1.简单查询练习 source: test003/doc

1.1 查询name中包含”li”的人，

GET test003/_search
{
  "query":
  {
    "regexp":{"user":".*li.*"}
  }
}

1.2 查询msg中含有birthday的数据，

GET test003/_search
{
  "query":
  {
    "match":{"message":"birthday"}
  }
}

1.3 查询city上海的，

GET /test003/_search
{
  "query":
  {
    "match":{"city":"上海"}
  }
}

1.4 查询name wangwu或lisi的，

GET test003/_search
{
  "query":
  {
    "terms":{
      "user":["lisi","wangwu"]
    }
  }
}

1.5 查询年龄大于35小于60的，同上/只显示name age city

GET test003/_search
{
  "_source": ["name","age","city"], 
  "query":
  {
    "range": {
      "age": {
        "gt": 35,
        "lt": 60
      }
    }
  }
}

1.6 查询年龄大于30且city不在北京的，

GET test003/_search
{
  "query":
  {
    "bool":
    {
      "must": [
        {"range": {
          "age": {
            "gte": 30
          }
        }}
      ],
      "must_not": [
        {
          "term": {
            "city": "北京"
            }
          }
      ]
    }
  }
}

1.7 查询name不含”li”且age大于20，

GET test003/_search
{
  "query":
  {
    "bool":
    {
      "must": [
        {"range": {
          "age": {
            "gte": 20
          }
        }}
      ],
      "must_not": [
        {"regexp": {
        "user": ".*li.*"
      }}
      ]
    }
  }
}

2.聚合复合查询 source: /employees/employee_info

2.1 查询salary最高的员工，只显示name和salary，返回top3

GET employees/_search
{
  "_source": ["name","salary"], 
  "size": 3, 
  "sort": [
    {
      "salary": {
        "order": "desc"
      }
    }
  ], 
  "aggs": {
    "max_salary": {
      "max": {
        "field": "salary"
      }
    }
  }
}

2.2 在gender 为male中，查询统计salary各项数据，top3

GET employees/_search
{
  "sort": [
    {
      "salary": {
        "order": "desc"
      }
    }
  ], 
  "size": 3, 
  "aggs": {
    "male":
    {
      "filter": {"term": {
        "gender": "male"}},
      "aggs": {
        "stats_salary": {
          "stats": {
            "field": "salary"
          }
        }
      }
    }
  }
}

2.3 查询不同岗位的职员的最高salary

GET employees/_search
{
  "aggs": {
    "job":
    {
      "terms": {"field": "job.keyword"},
      "aggs": {
        "stats_salary": {
          "stats": {
            "field": "salary"
          }
        }
      }
    }
  }
}

2.4 查询age大于25或salary大于12000的的java程序员

GET employees/employee_info/_search
{
  "query" :
  {
    "bool": 
    {
      "must": [
         { "match": {
            "job": "Java Programmer"
          }},
        {
          "range": {
            "age": {
              "gte": 25
            }
          }
        },
        {
          "bool": 
          {
            "should": [
              {
                "range": {
                  "salary": {
                    "gt": 20000
                  }
                }
              }
            ]
          }
        }
      ]
    }
  }
}

2.5 查询salary在15000下，15000-30000,30000以上的female员工

GET employees/_search
{
  "size": 3, 
  "sort": [
    {
      "salary": {
        "order": "desc"
      }
    }
  ], 
  "aggs": {
    "female_employee": {
      "filter": {"term": {
        "gender": "female"}},
      "aggs": 
      {
        "salary_range":
        {
          "range": {
            "field": "salary",
            "ranges": [
              {
                "to": 15000
              },
              {
                "from": 15000,
                "to":30000
              },
              {
                "from": 30000
              }
            ]
          }
        }
      }
    }
  }
}

数据源

// 操作数据3-聚合操作
PUT /employees/employee_info/_bulk
{ "index" : { "_id" : "1" } }
{ "name" : "Emma","age":32,"job":"Product Manager","gender":"female","salary":35000 }
{ "index" : { "_id" : "2" } }
{ "name" : "Underwood","age":41,"job":"Dev Manager","gender":"male","salary": 50000}
{ "index" : { "_id" : "3" } }
{ "name" : "Tran","age":25,"job":"Web Designer","gender":"male","salary":18000 }
{ "index" : { "_id" : "4" } }
{ "name" : "Rivera","age":26,"job":"Web Designer","gender":"female","salary": 22000}
{ "index" : { "_id" : "5" } }
{ "name" : "Rose","age":25,"job":"QA","gender":"female","salary":18000 }    
{ "index" : { "_id" : "6" } }
{ "name" : "Lucy","age":31,"job":"QA","gender":"female","salary": 25000}
{ "index" : { "_id" : "7" } }
{ "name" : "Byrd","age":27,"job":"QA","gender":"male","salary":20000 }
{ "index" : { "_id" : "8" } }
{ "name" : "Foster","age":27,"job":"Java Programmer","gender":"male","salary": 20000}
{ "index" : { "_id" : "9" } }
{ "name" : "Gregory","age":32,"job":"Java Programmer","gender":"male","salary":22000 }
{ "index" : { "_id" : "10" } }
{ "name" : "Bryant","age":20,"job":"Java Programmer","gender":"male","salary": 9000}
​
​
// 操作数据4-聚合操作之分组
POST _bulk
{"index":{"_index":"test003","_type":"doc"}}
{"user":"zhangsan", "age":30,"message":"happy birthday","city":"北京","location":{"lat":30,"lon":40}}
{"index":{"_index":"test003","_type":"doc"}}
{"user":"lisi", "age":30,"message":"happy birthday","city":"上海","location":{"lat":38.970718,"lon":116.325747}}
{"index":{"_index":"test003","_type":"doc"}}
{"user":"wangwu", "age":35,"message":"Happy birthday","city":"深圳","location":{"lat":37.970718,"lon":116.325747}}
{"index":{"_index":"test003","_type":"doc"}}
{"user":"zhaoliu", "age":40,"message":"birthday happy","city":"深圳","location":{"lat":36.970718,"lon":116.325747}}