技術標籤：gulimall專案

GET /bank/_search?q=*&sort=account_number:asc



GET /bank/_search
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "balance": "desc"
    }
  ],
  "from": 3,
  "size": 3,
  "_source": [
 
"firstname","balance"]
}


##全文檢索，按照評分進行排序，會對檢索條件進行分詞匹配
GET /bank/_search
{
  "query": {
    "match": {
      "balance": 16418
    }
  }
}

GET /bank/_search
{
  "query": {
    "match": {
      "address": "mill lane"
 

    }
  }
}


GET /bank/_search
{
  "query": {
    "match_phrase": {
      "address": "mill lane"
    }
  }
}

##多欄位匹配會進行分詞
GET /bank/_search
{
  "query": {
    "multi_match": {
      "query": "mill Movico", 
      "fields"
 
: ["address","city"]
    }
  }
}

##bool查詢 組合查詢，must:必須滿足；must:必須不滿足；should：滿不滿足都可以，滿足了分數就會更高
GET bank/_search
{
  "query": {
    "bool": {
      "must": [
        {"match": {
          "gender": "M"
        }},
        {
          "match": {
            "address": "mill"
          }
        }
      ],
      "must_not": [
        {"match": {
          "age": "18"
        }}
      ],
      "should": [
        {"match": {
          "lastname": "Wallace"
        }}
      ]
    }
  }
}


## filter 不會貢獻相關性得分
GET bank/_search
{
  "query": {
    "bool": {
      "must": [
        { "range": {
            "age": {
              "gte": 18,
              "lte": 30
            }
        }}
      ],
      "filter": {
        "range": {
          "age": {
            "gte": 18,
            "lte": 25
          }
        }
      }
    }
  }
}
GET bank/_search
{
  "query": {
    "bool": {
      "filter": {
        "range": {
          "age": {
            "gte": 18,
            "lte": 30
          }
        }
      }
    }
  }
}


## 精確值用term，全文檢索就有match
GET bank/_search
{
  "query": {
    "term": {
      "age": 28
    }
  }
}

##match_phrase 不會對查詢條件進行分詞， 查詢時只要匹配一部分即可
GET bank/_search
{
  "query": {
    "match_phrase": {
      "address": "789 Madison"
    }
  }
}

##精確匹配，必須和查詢條件值一樣才可以 即不會對查詢條件進行分詞， 查詢時必須完全匹配
GET bank/_search
{
  "query": {
    "match": {
      "address.keyword": "789 Madison"
    }
  }
}


##搜尋address中包含mill的所有人的年齡分佈以及平均年齡，但不顯示這些人的詳情
GET bank/_search
{
  "query": {
    "match": {
      "address": "mill"
    }
  },
  "aggs": {
    "ageAgg": {
      "terms": {
        "field": "age",
        "size": 10
      }
    },
    "ageAvg": {
      "avg": {
        "field": "age"
      } 
    },
    "balanceAvg": {
      "avg": {
        "field": "balance"
      }
    }
  },
  "size": 0
}


##按照年齡聚合，並且求這些年齡段的這些人的平均薪資(子聚合)
GET bank/_search
{
  "query": {
    "match_all": {}
  },
  "aggs": {
    "ageAgg": {
      "terms": {
        "field": "age",
        "size": 100
      },
      "aggs": {
        "ageAvg": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  }
}

##查出所有年齡分佈，並且這些年齡段中M的平均薪資和F的平均薪資以及這個年齡段的總體平均薪資
GET bank/_search
{
  "query": {
    "match_all": {}
  },
  "aggs": {
    "ageAgg": {
      "terms": {
        "field": "age",
        "size": 100
      },
      "aggs": {
        "genderAgg": {
          "terms": {
            "field": "gender.keyword"
          },
          "aggs": {
            "balanceAvg": {
              "avg": {
                "field": "balance"
              }
            }
          }
        },
        "ageBalance": {
          "avg": {
            "field": "balance"
          }
        }
      }
    }
  }
}

##檢視對映
GET bank/_mapping

##建立索引是指定型別
PUT /my_index
{
  "mappings": {
    "properties": {
      "age": {"type": "integer"},
      "email": {"type": "keyword"},
      "name": {"type": "text"}
    }
  }
}

##修改對映（對映作名詞就是對應資料庫的列的屬性）"index" 預設是true，表示可以被檢索，false表示不能被檢索，作為冗餘欄位 ##（這裡的不能被檢索是否是指不能被當作檢索條件，自己驗證）  這裡相當於添加了一個列的（對映）
PUT /my_index/_mapping
{
  "properties": {
    "emloyee-id": {
      "type": "keyword",
      "index": false
    }
  }
}

GET /bank/_search

GET /newbank/_mapping
 
##如何修改已存在的對映  只能是資料遷移，建立一個新的索引將資料遷移進去
PUT /newbank
{
  "mappings": {
    "properties": {
      "account_number": {
        "type": "long"
      },
      "address": {
        "type": "text"
      },
      "age": {
        "type": "integer"
      },
      "balance": {
        "type": "long"
      },
      "city": {
        "type": "keyword"
      },
      "email": {
        "type": "keyword"
      },
      "employer": {
        "type": "keyword"
      },
      "firstname": {
        "type": "text"
      },
      "gender": {
        "type": "keyword"
      },
      "lastname": {
        "type": "text",
        "fields": {
          "keyword": {
            "type": "keyword",
            "ignore_above": 256
          }
        }
      },
      "state": {
        "type": "keyword"
      }
    }
  }
}

##執行資料遷移  ES7以後的版本不在建議使用型別了，自己會有一個預設型別，—doc
POST _reindex
{
  "source": {
    "index": "bank",
    "type": "account"
  },
  "dest": {
    "index": "newbank"
  }
}


GET /newbank/_search


##分詞
POST _analyze
{
  "analyzer": "standard",
  "text": ["I love you yty."]
}

##可以識別正文的ik分詞器，自定義詞庫用Nginx配置，放在Nginx預設的檔案html
POST _analyze
{
  "analyzer": "ik_max_word",
  "text": ["喬碧蘿殿下，我愛你"]
}