elasticsearch 7版本基础操作

首先我们浏览器http://localhost:5601/进入 kibana里的Console中输入

首先让我们在 Console 中输入:

PUT t1/type1/1
{
  "name":"春生",
  "age":16
}

返回结果（是以REST ful 风格返回的）：

{
  "_index" : "t1",
  "_type" : "type1",
  "_id" : "1",
  "_version" : 1,
  "result" : "created",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 0,
  "_primary_term" : 1
}

我们来简要的说一下命令栏和返回结果栏都是表示什么意思:

命令栏	描述	结果栏	描述
PUT	创建命令	_index	索引
t1	索引	_type	类型
type1	类型	_id	id
1	id	_version	版本
name	属性	result	操作类型
age	属性	_shards	分片信息

method	url地址	描述
PUT	localhost:9200/索引名称/类型名称/文档id	创建文档（指定文档id）
POST	localhost:9200/索引名称/类型名称	创建文档（随机文档id）
POST	localhost:9200/索引名称/类型名称/文档id/_update	修改文档
DELETE	localhost:9200/索引名称/类型名称/文档id	删除文档
GET	localhost:9200/索引名称/类型名称/文档id	查询文档通过文档id
POST	localhost:9200/索引名称/类型名称/_search	查询所有数据

字段类型指定：

PUT t1/type1/1
{
  "name":"春生",
  "age":16		
}

那么 name这个字段用不用指定类型呢。毕竟我们关系型数据库是需要指定类型的啊

字符串类型
text 、 keyword
数值类型
long, integer, short, byte, double, float, half_float, scaled_float
日期类型
date
te布尔值类型
boolean
二进制类型
binary
范围类型
integer_range , float_range, long_range, double_range, date_range

指定字段类型：

PUT db
{
  "mappings": {
  "properties": {
    "name":{
      "type":"text"
    },
    "age":{
      "type": "long"
    },
    "birthday":{
      "type":"date"
    }
  }
  }
}

查看一下索引字段：

GET db/

返回结果：

{
  "db" : {
    "aliases" : { },
    "mappings" : {
      "properties" : {
        "age" : {
          "type" : "long"
        },
        "birthday" : {
          "type" : "date"
        },
        "name" : {
          "type" : "text"
        }
      }
    },
    "settings" : {
      "index" : {
        "creation_date" : "1572247546224",
        "number_of_shards" : "1",
        "number_of_replicas" : "1",
        "uuid" : "g-QMzIELQL2bOU1d4pDaKA",
        "version" : {
          "created" : "7030299"
        },
        "provided_name" : "db"
      }
    }
  }
}

我们看上列中字段类型是我自己定义的那么我们不定义类型会是什么情况呢。

默认字段类型

PUT test3/_doc/1
{
  "name":"春生",
  "age":13,
  "ddd":"1997-3-3"
}

查看一下test3索引：

GET test3

返回结果：

{
  "test3" : {
    "aliases" : { },
    "mappings" : {
      "properties" : {
        "age" : {
          "type" : "long"
        },
        "ddd" : {
          "type" : "text",
          "fields" : {
            "keyword" : {
              "type" : "keyword",
              "ignore_above" : 256
            }
          }
        },
        "name" : {
          "type" : "text",
          "fields" : {
            "keyword" : {
              "type" : "keyword",
              "ignore_above" : 256
            }
          }
        }
      }
    },
    "settings" : {
      "index" : {
        "creation_date" : "1572248744742",
        "number_of_shards" : "1",
        "number_of_replicas" : "1",
        "uuid" : "ebwFzh6-R32SOhZSj1S0pQ",
        "version" : {
          "created" : "7030299"
        },
        "provided_name" : "test3"
      }
    }
  }
}

我们看上列没有给字段指定类型那么es就会默认给我配置如字段类型分片以及id 就会默认给我们配置。

对比关系型数据库：

PUT t1/type1/1 ：索引t1 相当于关系型数据库的库，类型type1就相当于表，1 代表数据中的主键id

补充(注意)：

这里需要补充的是，在elastisearch5版本前，一个索引下可以创建多个类型，但是在elastisearch5后，一个索引只能对应一个类型，而id相当于关系型数据库的主键id若果不指定就会默认生成一个20位的uuid，属性相当关系型数据库的column(列)。

而结果中的 result 则是操作类型，现在是 created ，表示第一次创建。如果我们再次点击执行该命令，那么result 则会是 updated 。我们细心则会发现 _version 开始是1，现在你每点击一次就会增加一次。表示第几次更改。

我们在来学一条命令(elasticsearch 中的索引的情况)：

GET _cat/indices?v

返回结果：

![image-20191021193649302](/Users/jiangchunsheng/Library/Application Support/typora-user-images/image-20191021193649302.png)

查看我们所有索引的状态健康情况分片，数据储存大小等等。

那么怎么删除一条索引呢(库)呢?

DELETE /t1

返回结果：

{
  "acknowledged" : true
}
# 表示删除成功了

基础增删改查

创建数据PUT

第一条数据：

PUT test/chunsheng/1
{
  "name":"春生",
  "age":18,
  "from":"gu",
  "desc":"皮肤黑,武器长，性格直",
  "tags":["黑","长","直"]
}
# 注意 逗号 一定是英文的 ,

第二条数据:

PUT test/chunsheng/2
{
  "name":"大娘子",
  "age":18,
  "from":"sheng",
  "desc":"肤白貌美,就是腿长",
  "tags":["白","富","美"]
}

第三条数据：

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

注意⚠️：当执行命令时，如果数据不存在，则新增该条数据，如果数据存在则修改该条数据。

咱们通过 GET 命令查询一下:

GET test/chunsheng/1

返回结果：

{
  "_index" : "test",
  "_type" : "chunsheng",
  "_id" : "1",
  "_version" : 1,
  "_seq_no" : 0,
  "_primary_term" : 1,
  "found" : true,
  "_source" : {
    "name" : "春生",
    "age" : 18,
    "from" : "gu",
    "desc" : "皮肤黑,武器长，性格直",
    "tags" : [
      "黑",
      "长",
      "直"
    ]
  }
}

如果你想更新数据可以覆盖这条数据:

PUT test/chunsheng/1
{
  "name":"春生",
  "age":18,
  "from":"gu",
  "desc":"皮肤黄,武器长，性格直",
  "tags":["黄","长","直"]
}

返回结果：

{
  "_index" : "test",
  "_type" : "chunsheng",
  "_id" : "1",
  "_version" : 2,
  "result" : "updated",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 3,
  "_primary_term" : 1
}

查看结果：

{
  "_index" : "test",
  "_type" : "chunsheng",
  "_id" : "1",
  "_version" : 2,
  "_seq_no" : 3,
  "_primary_term" : 1,
  "found" : true,
  "_source" : {
    "name" : "春生",
    "age" : 18,
    "from" : "gu",
    "desc" : "皮肤黄,武器长，性格直",
    "tags" : [
      "黄",
      "长",
      "直"
    ]
  }
}

已经修改了那么 PUT 可以更新数据但是。麻烦的是原数据你还要重写一遍要这不符合我们规矩。

更新数据POST：

POST test/chunsheng/1/_update # 加了个_update
{
  "doc": {
    "desc":"皮肤黄,富二代，就有钱",
    "tags":["黄","富","钱"]
  }
}

返回结果：

{
  "_index" : "test",
  "_type" : "chunsheng",
  "_id" : "1",
  "_version" : 3,
  "_seq_no" : 4,
  "_primary_term" : 1,
  "found" : true,
  "_source" : {
    "name" : "春生",
    "age" : 18,
    "from" : "gu",
    "desc" : "皮肤黄,富二代，就有钱",
    "tags" : [
      "黄",
      "富",
      "钱"
    ]
  }
}

上例中，我们使用 POST 命令，在 id 后面跟 _update ，要修改的内容放到 doc 文档(属性)中即可。

查询GET

简单的查询，我们上面已经不知不觉的使用熟悉了:

GEt test/chunsheng/1

条件查询 _search?q=

GET test/chunsheng/_search?q=from:gu

通过 _serarch?q = from:gu 查询条件是from属性是gu有那些数据。

别忘了 _search 和 from 属性中间的分隔符 ? 。

返回结果：

{
  "took" : 19,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {     
    "total" : {
      "value" : 2,               # 一共两条数据
      "relation" : "eq"
    },
    "max_score" : 0.35667494,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : 0.35667494,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",                                         
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 0.35667494,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黄,富二代，就有钱",
          "tags" : [
            "黄",
            "富",
            "钱"
          ]
        }
      }
    ]
  }
}

我们看一下结果返回并不是数据本身，是给我们了一个 hits ，还有 _score得分，就是根据算法算出和查询条件匹配度高得分就搞。后面我们单独机会讲这个算法。

构建查询

GET test/chunsheng/_search
{
  "query": {
    "match": {
      "from": "gu"
    }
  }
}

上例，查询条件是一步步构建出来的，将查询条件添加到 match 中即可。

返回结果还是一样的：

{
  "took" : 19,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {     
    "total" : {
      "value" : 2,               # 一共两条数据
      "relation" : "eq"
    },
    "max_score" : 0.35667494,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : 0.35667494,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",                                         
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 0.35667494,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黄,富二代，就有钱",
          "tags" : [
            "黄",
            "富",
            "钱"
          ]
        }
      }
    ]
  }
}

除此之外，我们还可以查询跟顾老二相关的所有数据，那就是查询全部:

GET test/chunsheng/_search #这是一个 但是没有条件

GET test/chunsheng/_search #查询所有的数据
{
  "query": {
    "match_all": {}
  }
}

match_all的值为空，表示没有查询条件，就像select * from table_name一样。

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "肤白貌美,就是腿长",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黄,富二代，就有钱",
          "tags" : [
            "黄",
            "富",
            "钱"
          ]
        }
      }
    ]
  }
}

如果有个需求，我们仅是需要查看 name 和 desc 两个属性，其他的不要怎么办?

GET test/chunsheng/_search
{
  "query": {
    "match_all": {}
  },
  "_source": ["name","age"]
}

如上例所示，在查询中，通过 _source 来控制仅返回 name 和 age 属性。

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "大娘子",
          "age" : 18
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "春生",
          "age" : 18
        }
      }
    ]
  }
}

Python推荐

一般的，我们推荐使用构建查询，以后在与Python交互时的查询等也是使用构建查询方式处理查询条件，因为该方 式可以构建更加复杂的查询条件，也更加一目了然

排序查询

我们说到排序有人就会想到：正序或倒序那么我们先来倒序：

倒序

GET test/chunsheng/_search
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "age": {
        "order": "desc"
      }
    }
  ]
}

上例，在条件查询的基础上，我们又通过 sort 来做排序，排序对象是 age ， order 是 desc 降序。

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 21,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : null,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        },
        "sort" : [
          22
        ]
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : null,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "肤白貌美,就是腿长",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        },
        "sort" : [
          18
        ]
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : null,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黄,富二代，就有钱",
          "tags" : [
            "黄",
            "富",
            "钱"
          ]
        },
        "sort" : [
          18
        ]
      }
    ]
  }
}

正序

就是 desc 换成了 asc

GET test/chunsheng/_search
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "age": {
        "order": "asc"
      }
    }
  ]
}

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : null,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "肤白貌美,就是腿长",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        },
        "sort" : [
          18
        ]
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : null,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黄,富二代，就有钱",
          "tags" : [
            "黄",
            "富",
            "钱"
          ]
        },
        "sort" : [
          18
        ]
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : null,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        },
        "sort" : [
          22
        ]
      }
    ]
  }
}

注意:在排序的过程中，只能使用可排序的属性进行排序。那么可以排序的属性有哪些呢?

数字
日期
ID

其他都不行

分页查询

GET test/chunsheng/_search
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "age": {
        "order": "asc"
      }
    }
  ],
  "from": 0, # 从第n条开始
  "size": 1  # 返回n条数据
  
}

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : null,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "肤白貌美,就是腿长",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        },
        "sort" : [
          18
        ]
      }
    ]
  }
}

就返回了一条数据是从第0条开始的返回一条数据。

学到这里，我们也可以看到，我们的查询条件越来越多，开始仅是简单查询，慢慢增加条件查询，增加排序，对返回结果进行限制。所以，我们可以说:对elasticsearch于来说，所有的查询条件都是可插拔的，彼此之间用分割。比如说，我们在查询中，仅对返回结果进行限制:

GET test/chunsheng/_search
{
  "query": {
    "match_all": {}
  },
 
  "from": 0,
  "size": 2
}

返回结果:

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "肤白貌美,就是腿长",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      }
    ]
  }
}

布尔查询

must (and)

我要查询所有from属性为“gu“的数据：must

GET test/chunsheng/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "from": "gu"
          }
        },
        {
          "match": {
            "age": 18
          }
        }
      ]
    }
  }
}

我们通过在 bool 属性内使用 must 来作为查询条件，那么条件是什么呢 age :18 ，from:gu 结果就有一条数据。

是不是有点像 and 的感觉

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.3566749,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 1.3566749,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黄,富二代，就有钱",
          "tags" : [
            "黄",
            "富",
            "钱"
          ]
        }
      }
    ]
  }
}

should (or)

那么我要查询from为gu，和 age 为18的的条件

GET test/chunsheng/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "match": {
            "from": "gu"
          }
        },
        {
          "match": {
            "age": 18
          }
        }
      ]
    }
  }
}

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 1.3566749,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 1.3566749,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黄,富二代，就有钱",
          "tags" : [
            "黄",
            "富",
            "钱"
          ]
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "肤白貌美,就是腿长",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : 0.35667494,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      }
    ]
  }
}

我们的返回结果是不是出现了一个 age :22的说明我们查出了。符合age 是18 和 from 是gu的都行了

是不是有点像 **or ** 呢

must_not (not)

我想要查询年龄不是 18 的数据

GET test/chunsheng/_search
{
  "query": {
    "bool": {
      "must_not": [
        {
          "match": {
            "age": 18
          }
        }
      ]
    }
  }
}

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 8,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.0,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : 0.0,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      }
    ]
  }
}

Fitter

我要查询 from为gu的，age大于18的数据

GET test/chunsheng/_search
{
  "query":{
    "bool": {
      "must": [
        {
          "match": {
            "from": "gu"
          }
        }
      ],
      "filter": {
        "range": {
          "age": {
            "gt": 18
          
          }
        }
      }
    }
  }
}

这里就用到了 filter 条件过滤查询，过滤条件的范围用 range 表示， gt 表示大于，大于多少呢?是18。结果如下:

gt 表示大于
gte 表示大于等于
lt 表示小于
lte 表示小于等于

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.47000363,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "3",
        "_score" : 0.47000363,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp，没看怎么看，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      }
    ]
  }
}

要查询 from 是 gu ， age 在 25~30 之间的怎么查?

GET test/chunsheng/_search
{
  "query":{
    "bool": {
      "must": [
        {
          "match": {
            "from": "gu"
          }
        }
      ],
      "filter": {
        "range": {
          "age": {
            "gte": 25,
            "lte": 30
          }
        }
      }
    }
  }
}

*如果在filter过滤条件中建议用must代替

短语检索

我要查询 tags为黑的数据

GET test/chunsheng/_search
{
  "query":{
    "match": {
      "tags": "黑"
    }
  }
}

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.0596458,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 1.0596458,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黑,武器长，性格直",
          "tags" : [
            "黑",
            "长",
            "直"
          ]
        }
      }
    ]
  }
}

既然按照标签检索，那么，能不能写多个标签呢?又该怎么写呢?

GET test/chunsheng/_search
{
  "query":{
    "match": {
      "tags": "黑 白"
    }
  }
}

多个标签要空格分开

返回结果:

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 1.0596458,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 1.0596458,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黑,武器长，性格直",
          "tags" : [
            "黑",
            "长",
            "直"
          ]
        }
      },
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : 1.0596458,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "肤白貌美,就是腿长",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        }
      }
    ]
  }
}

上列中我发现只要含有这个标签就给我返回这个数据了。

那现在我要查询。如 “腿长” 有就直接返回没有不要了不需要包含

match_phrase

GET test/chunsheng/_search
{
  "query":{
    "match_phrase": {
      "desc": "腿 长"
    }
  }
}

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.580115,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "2",
        "_score" : 1.580115,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "肤白貌美,就是腿长",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        }
      }
    ]
  }
}

term查询精确查询

term查询是直接通过倒排索引指定的词条，也就是精确查找。

term和match的区别:

match是经过分析(analyer)的，也就是说，文档是先被分析器处理了，根据不同的分析器，分析出的结果也会不同，在会根据分词结果进行匹配。
term是不经过分词的，直接去倒排索引查找精确的值。

term与match的区别

注意 ⚠️：我们现在用的es7版本所以我们用 mappings properties 去给多个字段(fields)指定类型的时候不能给我们的索引制定类型：

PUT db_test
{
  "mappings": {
    "properties": {
      "name":{
        "type":"text"
      },
      "hoy":{
        "type": "keyword"
      }
    }
  }
}
# 插入数据
PUT db_test/_doc/1
{
  "name":"我是 name",
  "hoy":"我是 hoy"
}

上述中db_test索引中,字段name在被查询时会被分析器进行分析后匹配查询。而属于keyword类型不会被分析器处理。

我们来验证一下：

GET _analyze
{
  "analyzer": "keyword",
  "text": "我是 name"
}

结果:

{
  "tokens" : [
    {
      "token" : "我是 name",
      "start_offset" : 0,
      "end_offset" : 7,
      "type" : "word",
      "position" : 0
    }
  ]
}

是不是没有被分析啊。就是简单的一个字符串啊。

GET _analyze
{
  "analyzer": "standard",
  "text": "我是 name"
}

结果:

{
  "tokens" : [
    {
      "token" : "我",
      "start_offset" : 0,
      "end_offset" : 1,
      "type" : "<IDEOGRAPHIC>",
      "position" : 0
    },
    {
      "token" : "是",
      "start_offset" : 1,
      "end_offset" : 2,
      "type" : "<IDEOGRAPHIC>",
      "position" : 1
    },
    {
      "token" : "name",
      "start_offset" : 3,
      "end_offset" : 7,
      "type" : "<ALPHANUM>",
      "position" : 2
    }
  ]
}

那么我们看一下们字符串是不是被分析了啊。

总结：

keyword 字段类型不会被分析器分析

现在我们来查询一下：

GET db_test/_search # 是通过 被分析器分析 查询
{
  "query": {
    "term": {
      "name":"我" 
    }
  }
}

GET db_test/_search  # keyword 不回被分析所以直接查询
{
  "query": {
    "match": {
      "hoy":"我是 hoy" 
    }
  }
}

查找多个精确值(terms)

PUT db_test/_doc/2
{
  "t1": "20",
  "t2": "2019-4-16"
}
PUT db_test/_doc/3
{
"t1": "30",
  "t2": "2019-4-17"
}
# 查询  精确查找多个值
GET db_test/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "term": {
            "t1": "20"
          }
        },
        {
          "term": {
            "t1": "30"
          }
        }
      ]
    }
  }
}

除了bool查询之外

GET db_test/_doc/_search
{
  "query": {
    "terms": {
      "t1": ["20", "30"]
    }
} }
GET db_test/_doc/_search
{
  "query": {
    "terms": {
      "t2": ["2019-4-16", "2019-4-17"]
    }
} }

官网：see also:Term Query | 查找多个精确值

高亮显示

GET test/chunsheng/_search
{
  "query":{
    "match": {
      "name": "春生"
    }
  },
  "highlight" :{
    "fields": {
      "name":{}
    }
  }
}

返回结果：

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 41,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 2.271394,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 2.271394,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黑,武器长，性格直",
          "tags" : [
            "黑",
            "长",
            "直"
          ]
        },
        "highlight" : {
          "name" : [
            "<em>春</em><em>生</em>"
          ]
        }
      }
    ]
  }
}

我们可以看到 "春生"已经帮我们加上了一个标签

这是es帮我们加的标签。那我·也可以自己自定义样式

自定义高亮显示

GET test/chunsheng/_search
{
  "query":{
    "match": {
      "name": "春生"
    }
  },
  "highlight" :{
    "pre_tags": "<b class='key' style='color:red'>", 
    "post_tags": "</b>", 
    "fields": {
      "name":{}
    }
  }
}

返回结果:

#! Deprecation: [types removal] Specifying types in search requests is deprecated.
{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 2.271394,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "chunsheng",
        "_id" : "1",
        "_score" : 2.271394,
        "_source" : {
          "name" : "春生",
          "age" : 18,
          "from" : "gu",
          "desc" : "皮肤黑,武器长，性格直",
          "tags" : [
            "黑",
            "长",
            "直"
          ]
        },
        "highlight" : {
          "name" : [
            "<b class='key' style='color:red'>春</b><b class='key' style='color:red'>生</b>"
          ]
        }
      }
    ]
  }
}

需要注意的是:自定义标签中属性或样式中的逗号一律用英文状态的单引号表示，应该与外部 es 语法的双引号区分开。

Deprecation

注意 elasticsearch 在第一个版本的开始每个文档都储存在一个索引中，并分配一个映射类型，映射类型用于表示被索引的文档或者实体的类型，这样带来了一些问题（详情：https://www.cnblogs.com/Neeo/articles/10393961.html#important）导致后来在 elasticsearch6.0.0 版本中一个文档只能包含一个映射类型，而在 7.0.0 中，映射类型则将被弃用，到了 8.0.0 中则将完全被删除。

解释一下警告信息：

#! Deprecation: [types removal] Specifying types in document index requests is deprecated, use the typeless endpoints instead (/{index}/_doc/{id}, /{index}/_doc, or /{index}/_create/{id}).

#!Deprecation: [types removal]不支持在文档索引请求中指定类型，而是使用无类型的端点(/{index}/_doc/{id}， /{index}/_doc，或/{index}/_create/{id})。

#! Deprecation: [types removal] Specifying types in search requests is deprecated.

#!Deprecation: [types removal]不赞成在搜索请求中指定类型

我们 7 版本兼容了 6版本但是已经被弃用了我们的类型还是能用的。在8版本就完全删除了。

posted @ 2019-10-28 22:34 PythonAV 阅读(11356) 评论(4) 编辑收藏举报

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春生

Be humble, communicate clearly, and respect others.

PythonAV

elasticsearch 7版本基础操作

elasticsearch 7版本基础操作

字段类型指定：

指定字段类型：

默认字段类型

基础增删改查

创建数据PUT

更新数据POST：

查询GET

条件查询 _search?q=

构建查询

Python推荐

排序查询

倒序

正序

分页查询

布尔查询

must (and)

should (or)

must_not (not)

Fitter

短语检索

term查询精确查询

term与match的区别

查找多个精确值(terms)

高亮显示

自定义高亮显示

Deprecation

公告

春生

Be humble, communicate clearly, and respect others.

PythonAV

elasticsearch 7版本 基础操作

elasticsearch 7版本 基础操作

字段类型指定：

指定字段类型：

默认字段类型

基础增删改查

创建数据PUT

更新数据POST：

查询GET

条件查询 _search?q=

构建查询

Python推荐

排序查询

倒序

正序

分页查询

布尔查询

must (and)

should (or)

must_not (not)

Fitter

短语检索

term查询精确查询

term与match的区别

查找多个精确值(terms)

高亮显示

自定义高亮显示

Deprecation

公告

elasticsearch 7版本基础操作

elasticsearch 7版本基础操作