• elasticsearch 第二章 elasticsearch的详细用法及参数


    es的详细用法:

    #查看s18下所有的文件
    GET s18/doc/_search  

    如果PUT s18/doc/1 添加内容后,再次PUT s18/doc/1,会将之前的所有东西覆盖掉.

    查询文件中指定的字符串

    方法1:
      #
    查询年龄为19岁的数据   GET s18/doc/_search?q=age:19
    方法2:
      #DSL
      GET s18/doc/_search
      {
        "query":{
          "match":{
            "age":19
            }
         }
      }

    修改指定文件的指定字段

    #将第一条数据的age变为100
    POST s18/doc/1/_update { "doc":{ "age":100 } }

    删除指定字段

    POST s18/doc/_delete_by_query?q=age:30

    排序(不是所有的字段都能排序)

    GET s18/doc/_search
    {
      "query":{
            "match_all":{}
        },
        "sort":[
            {
          "age":{
          #升序
          "order": "asc"
          #降序
          "order":"desc"
              }
           }
        ]  
    }

    分页

    #从第一页开始,每页显示2条数据
    GET s18/doc/_search
    {
        "query":{
        "match_all":{}
      },
       "from":0,
       "size":2 
    }

    布尔查询(should(or:两者存在一个即可),must(and:两者必须都存在),must_not(not:不是这个的))

    should

    #查询出name为嘻哈天王age为19的数据
    GET s18/doc/_search { "query":{ "bool":{ "should":[ { "match":{ "name":"嘻哈天王" } }, "match":{ "age":19 } ] } } }

     must

    #查询出age为30并且name为guaishushu的数据
    GET s18/doc/_search { "query": { "bool": { "must": [ { "match": { "age": "30" } }, { "match": { "name": "guaishushu" } } ] } } }

    must_not

    #查询出name不为tiantian的和age不为30的数据
    GET s18/doc/_search
    {
      "query": {
        "bool": {
          "must_not": [
            {
              "match": {
                "age": "30"
              }
            },
            {
              "match": {
                "name": "tiantian"
              }
            }
          ]
        }
      }
    }

    filter查询(gte,lte,可以结合bool查询)

    #查询年龄大于20岁的男的数据:
    GET s18/doc/_search
    {
      "query": {
        "bool": {
          "must": [
            {
              "match": {
                "sex": ""
              }
            }
          ],
          "filter": {
            "range": {
              "age": {
                "gt": 20
              }
            }
          }
        }
      }
    }

    # 查询年龄小于等于23的非男性

    GET s18/doc/_search
    {
    "query":{
        "bool":{
          must_not:[
             {
              "match":{
                "sex": ""
              }
            }
          ],
         {
         match:{
           filter:{
            "range":{
               "age":{
                  "lte":23
                  }
                }
              }
            }
          }
        }
      }
    }

    高亮查询

    #查询出name为tiantian的数据,给查出来的东西显示为下面的东西

    GET s18/doc/_search { "query": { "match": { "name": "tiantian" } }, "highlight": { "pre_tags": "<b style='color:red;font-size:20px;' class='tian'>", "post_tags": "</b>", "fields": { "name":{} } } }

    结果过滤

    #查询出name为xiaokeai的数据,并过滤出name和age
    
    GET s18/doc/_search
    {
      "query": {
        "match": {
          "name": "xiaokeai"
        }
      },
      #如果只想显示出一个东西,那么只需要写一个字符串就行,列表只是在多个数据的时候才用
      "_source": ["name","age"]
    }

    聚合查询

    # sum,查询所有男生的年龄总和
    GET s18/doc/_search
    {
      "query": {
        "match": {
          "sex": ""
        }
      },
      "aggs": {
        "age_sum": {
          "sum": {
            "field": "age"
          }
        }
      }
    }

    查询出男生的最大年龄

    GET s18/doc/_search
    {
      "query": {
        "match": {
          "sex": ""
        }
      },
      "aggs": {
        "max_age": {
          "max": {
            "field": "age"
          }
        }
      }
    }

    求所有人的平均值

    GET s18/doc/_search
    {
      "query": {
        "match_all": {}
      },
      "aggs": {
        "my_avg": {
          "avg": {
            "field": "age"
          }
        }
      }
    }

    分组查询

    # 分组,根据年龄,10-20,,20-30, 30-100
    GET s18/doc/_search
    {
      "aggs": {
        "my_age": {
          "range": {
            "field": "age",
            "ranges": [
              {
                "from": 10,
                "to": 20
              },
              {
                "from": 20,
                "to": 30
              },
              {
                "from": 30,
                "to": 100
              }
            ]
          }
        }
      }
    }

    根据分组查每一组的详细信息

    # 分组,根据年龄,10-20,,20-30, 30-100,并查出每一组的平均值
    GET s18/doc/_search
    {
      "aggs": {
        "my_agg": {
          "range": {
            "field": "age",
            "ranges": [
              {
                "from": 10,
                "to": 20
              },
              {
                "from": 20,
                "to":30
              },
              {
                "from": 30,
                "to": 100
              }
            ]
          },
          "aggs": {
            "my_avg": {
              "avg": {
                "field": "age"
              }
            }
          }
        }
      }
    }

    映射(简而言之,映射就是之前都是es帮我自动创建表结构,映射就是我们自己创建表结构)

    查看映射的数据结构

    GET s6/_mapping
    PUT s5
    {
      "mappings": {
        "doc":{
          "properties":{
            "name":{
              "type":"text"
            },
            "age":{
              "type": "long"
            },
            "desc":{
              "type":"text"
            }
          }
        }
      }
    }

    这里我们要注意,如果我们给定的类型是文本,但是我们插入的时候是long类型,es会帮我们将long类型转化为文本类型

     稍微复杂点的映射

    PUT s6
    {
      "mappings": {
        "doc":{
          "properties":{
            "age":{
              "type":"long"
            },
            "b":{
              "type":"text",
              "fields":{
                "keyword":{
                  "type":"keyword",
                  "ignore_above":256
                }
              }
            },
            "desc":{
              "type":"text",
              "fields":{
                "keyword":{
                  "type":"keyword",
                  "ignore_above":256
                }
              }
            },
            "name":{
              "type":"text",
              "fields":{
                "keyword":{
                  "type":"keyword",
                  "ignore_above":256
                }
              }
            },
            "sex":{
              "type":"text",
              "fields":{
              "keyword":{
                "type":"keyword",
                "ignore_above":256
                }
              }
            }
          }
        }
      }
    }

    dynamic的三种状态

    ture
    false
    strict

    ture

    PUT s7
    {
      "mappings": {
        "doc":{
          "dynamic":true,
          "properies":{
            "name":{"type":"text"}
          }
        }
      }
    }

    false

    PUT s7
    {
      "mappings": {
        "doc":{
          "dynamic":false,
          "properies":{
            "name":{"type":"text"}
          }
        }
      }
    }

     strict

    PUT s8
    {
      "mappings": {
        "doc":{
          "dynamic":"strict",
          "properies":{
            "name":{
              "type":"text"
            }
          }
        }
      }
    }

    ignore_above

    PUT s9
    {
      "mappings": {
        "doc":{
          "properies":{
            "title":{
              "type":"text",
              "ignore_above":256
            }
          }
        }
      }
    }

    mappings中的index参数

    PUT s10
    {
      "mappings": {
        "doc":{
          "properies":{
            "t1":{
            "name":"text",
            "index":true
          },
          "t2":{
            "name":"text",
            "index":false
            }
          }
        }
      }
    }

    copy_to

    PUT s11
    {
      "mappings": {
        "doc":{
          "properies":{
            "t1":{
            "name":"text",
            "copy_to":"full_name"
          },
          "t2":{
            "name":"text",
            "copy_to":"full_name"
            },
            "full_name":{
              "type":"text"
            }
          }
        }
      }
    }
    PUT s10
    {
      "mappings": {
        "doc":{
          "properties":{
            "t1":{
              "type":"text",
              "copy_to":["f1", "f2"]
            },
            "t2":{
              "type":"text",
              "copy_to":["f1", "f2"]
            },
            "f1":{
              "type":"text"
            },
            "f2":{
              "type":"keyword"
            }
          }
        }
      }
    }

    嵌套类型

    PUT q1
    {
      "mappings": {
        "doc":{
          "properties":{
            "name":{
              "type":"text"
            },
            "age":{
              "type":"long"
            },
            "info":{
              "properties":{
                "addr":{
                  "type":"text"
                },
                "tel":{
                  "type":"long"
                }
              }
            }
          }
        }
      }
    }

    嵌套类型取值的时候

    GET w1/doc/_search
    {
      "query": {
        "match": {
          "info.tel": "10010"
        }
      }
    }
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  • 原文地址:https://www.cnblogs.com/zty1304368100/p/10902448.html
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