es 查询

内容详细

es的查询

0.1 准备数据

        # 准备数据
        PUT lqz/_doc/1
        {
          "name":"顾老二",
          "age":30,
          "from": "gu",
          "desc": "皮肤黑、武器长、性格直",
          "tags": ["黑", "长", "直"]
        }

        PUT lqz/_doc/2
        {
          "name":"大娘子",
          "age":18,
          "from":"sheng",
          "desc":"肤白貌美，娇憨可爱",
          "tags":["白", "富","美"]
        }

        PUT lqz/_doc/3
        {
          "name":"龙套偏房",
          "age":22,
          "from":"gu",
          "desc":"mmp，没怎么看，不知道怎么形容",
          "tags":["造数据", "真","难"]
        }


        PUT lqz/_doc/4
        {
          "name":"石头",
          "age":29,
          "from":"gu",
          "desc":"粗中有细，狐假虎威",
          "tags":["粗", "大","猛"]
        }

        PUT lqz/_doc/5
        {
          "name":"魏行首",
          "age":25,
          "from":"广云台",
          "desc":"仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
          "tags":["闭月","羞花"]
        }

0.2 match和term

        match和term中必须要加条件，但是我们有时候需要查询所有，不带条件，需要用到match_all

0.3match_all

        # 查询所有
        GET lqz/_search
        {
          "query": {
            "match_all": {}
          }
        }

0.4 前缀查询match_phrase_prefix

        # 查英文   beautiful   --->be开头的---》能查到
        GET lqz/_search
        {
          "query": {
            "match_phrase_prefix": {
              "name": "顾"
            }
          }
        }

0.5 match_phrase

        # 会分词，分词完成后，如果写了slop，会按分词之间间隔是slop数字去抽
        GET t1/doc/_search
        {
          "query": {
            "match_phrase": {
              "title": {
                "query": "中国世界",
                "slop": 2
              }
            }
          }
        }

0.6 多条件查询，或的关系

        GET lqz/_search  # 只要name或者desc中带龙套就查出来
        {
          "query": {
            "multi_match": {
              "query": "龙套",
              "fields": ["name", "desc"]
            }
          }
        }

1 Elasticsearch之排序查询

        # 结构化查询 
        GET lqz/_search
        {
          "query": {
            "match": {
              "name": ""
            }
          }
        }

        # 排序查询---》可以按多个排序条件-->sort的列表中继续加
        GET lqz/_search
        {
          "query": {
            "match": {
              "from": "gu"
            }
          },
          "sort": [
            {
              "age": {
                "order": "asc"
              }
            }
          ]
        }


        # 不是所有字段都可以排序--->只能是数字字段

2 Elasticsearch之分页查询

        # from 和size
        GET lqz/_search
        {
          "query": {
            "match_all": {}
          },
          "sort": [
            {
              "age": {
                "order": "desc"
              }
            }
          ], 
          "from": 3,
          "size": 2
        }

3 Elasticsearch之布尔查询

        #   must（and）  should（or）  must_not（not）    filter

        # must条件  and条件
        GET lqz/_search
        {
          "query": {
            "bool": {
              "must": [
                {
                  "match": {
                    "from": "sheng"
                  }
                },
                {
                  "match": {
                    "age": 18
                  }
                }
              ]
            }
          }
        }


        # 咱们认为的and查询，但是不行
        GET lqz/_search
        {
          "query": {
            "match": {
              "from": "sheng",
              "age":18
            }
          }
        }

        # 查询课程标题或者课程介绍中带python的数据




        # shoud   or 条件---》搜索框，就是用它
        GET lqz/_search
        {
          "query": {
            "bool": {
              "should": [
                {
                  "match": {
                    "from": "sheng"
                  }
                },
                {
                  "match": {
                    "age": 22
                  }
                }
              ]
            }
          }
        }


        # must_not  既不是也不是
        GET lqz/_search
        {
          "query": {
            "bool": {
              "must_not": [
                {
                  "match": {
                    "from": "gu"
                  }
                },
                {
                  "match": {
                    "tags": "可爱"
                  }
                },
                {
                  "match": {
                    "age": 18
                  }
                }
              ]
            }
          }
        }


        # 查询from为gu，age大于25的数据怎么查
        GET lqz/_search
        {
          "query": {
            "bool": {
              "must": [
                {
                  "match": {
                    "from": "gu"
                  }
                }
              ],
              "filter": {
                "range": {
                  "age": {
                    "lt": 25
                  }
                }
              }
            }
          }
        }

4 Elasticsearch之查询结果过滤

        # 只查某几个字段
        GET lqz/_search
        {
          "query": {
            "match": {
              "name": "顾老二"
            }
          },
          "_source": ["name", "age"]
        }

5 Elasticsearch之高亮查询

        # 默认高亮
        GET lqz/_search
        {
          "query": {
            "match": {
              "name": "石头"
            }
          },
          "highlight": {
            "fields": {
              "name": {}
            }
          }
        }

        # 自定义高亮
        GET lqz/_search
        {
          "query": {
            "match": {
              "from": "gu"
            }
          },
          "highlight": {
            "pre_tags": "<b class='key' style='color:red'>",
            "post_tags": "</b>",
            "fields": {
              "from": {}
            }
          }
        }

6 Elasticsearch之聚合函数

        # avg   max   min   sum

        # avg
        GET lqz/_search
        {
          "query": {
            "match": {
              "from": "gu"
            }
          },
          "aggs": {
            "my_avg": {
              "avg": {
                "field": "age"
              }
            }
          },
          "_source": ["name", "age"]
        }

7 Python操作es

        # 如果官方没提供，使用requests模块，发送http请求即可

        '''

        PUT lqz/_doc/2
        {
          "name":"大娘子",
          "age":18,
          "from":"sheng",
          "desc":"肤白貌美，娇憨可爱",
          "tags":["白", "富","美"]
        }
        '''
        #
        # import requests
        #
        # data = {
        #     "name": "大娘子",
        #     "age": 18,
        #     "from": "sheng",
        #     "desc": "肤白貌美，娇憨可爱",
        #     "tags": ["白", "富", "美"]
        # }
        # res=requests.put('http://127.0.0.1:9200/lqz/_doc/6', json=data)
        # print(res.text)

        # 查询

        #  官方提供了python操作es包，基础包--》建议你用---》类似于pymysql
        # pip install elasticsearch
        from elasticsearch import Elasticsearch

        # Instantiate a client instance
        client = Elasticsearch("http://localhost:9200")

        # Call an API, in this example `info()`
        # resp = client.info()
        # print(resp)



        # 创建索引（Index）
        # result = client.indices.create(index='user')
        # print(result)
        # 删除索引
        # result = client.indices.delete(index='user')


        # 插入数据
        # data = {'userid': '1', 'username': 'lqz','password':'123'}
        # result = client.create(index='news', doc_type='_doc', id=1, body=data)
        # print(result)
        # 更新数据
        '''
        不用doc包裹会报错
        ActionRequestValidationException[Validation Failed: 1: script or doc is missing
        '''
        # data ={'doc':{'userid': '1', 'username': 'lqz','password':'123ee','test':'test'}}
        # result = client.update(index='news', doc_type='_doc', body=data, id=1)
        # print(result)


        # 删除数据
        # result = client.delete(index='news',id=1)

        # 查询
        # 查找所有文档
        # query = {'query': {'match_all': {}}}
        # #  查找名字叫做jack的所有文档
        # query = {'query': {'term': {'username': 'lqz'}}}

        # 查找年龄大于11的所有文档
        query = {'query': {'range': {'age': {'gt': 28}}}}

        allDoc = client.search(index='lqz',  body=query)
        # print(allDoc['hits']['hits'][0]['_source'])
        print(allDoc)

        # python操作es的包---》类似于django的orm包



        #  用的最多的是查询

        # 写个脚本，把课程表的数据，同步到es中（建立索引---》插入数据）

        # High level Python client for Elasticsearch
        # https://github.com/elastic/elasticsearch-dsl-py
        from datetime import datetime
        from elasticsearch_dsl import Document, Date, Nested, Boolean,analyzer, InnerDoc, Completion, Keyword, Text,Integer

        from elasticsearch_dsl.connections import connections

        connections.create_connection(hosts=["localhost"])


        class Article(Document):
            title = Text(fields={'title': Keyword()})
            author = Text()

            class Index:
                name = 'myindex'  # 索引名

        if __name__ == '__main__':
            # Article.init()  # 创建映射
            # 保存数据
            # article = Article()
            # article.title = "测试测试"
            # article.author = "刘清政"
            # article.save()  # 数据就保存了

            #查询数据
            # s=Article.search()
            # s = s.filter('match', title="测试")
            # results = s.execute()
            # print(results)

            #删除数据
            # s = Article.search()
            # s = s.filter('match', title="测试").delete()
            #修改数据
            s = Article().search()
            s = s.filter('match', title="测试")
            results = s.execute()
            print(results[0])
            results[0].title="xxx"
            results[0].save()

        # es数据和mysql数据同步
            -方案一：第三方同步脚本，实时同步mysql和es数据,软件运行，配置一下就可以了，后台一直运行
            -https://github.com/go-mysql-org/go-mysql-elasticsearch
            -编译成可执行文件，启动就行----》linux上编译，go sdk---》跨平台编译

          -方案二：（简历里说---》es和mysql的同步工具）
            -自己用python写---》三个表，pymysql---》es中---》后台一直运行
            -三个表，删除数据呢？公司里的数据都不删，都是软删除
            -三个表增加---》记录每个表同步到的位置id号---》
            -pymysql  es
                -免费课表(id,name,price)，实战课表(id,name,price,teacher)
              id_1=0
              id_2=0
              pymyql打开免费课，查询id如果大于id_1，把大于id_1的取出来组装成字典，存入es
              pymyql打开实战课，查询id如果大于id_2，把大于id_2的取出来，存入es
              -同步到es中---》es中只存id,name,price
          -方案三：使用celery，只要mysql相应的表里插入一条数据，就使用celery的异步，把这条记录插入到es中去
          -方案三：信号---》监控到哪个表发生了变化---》只要xx表发生变化，就插入es

__EOF__

本文作者：向上
本文链接：https://www.cnblogs.com/ydy001/p/16352387.html
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