Elastic Search的简单操作

前言

启动一个节点和kibana

接下来的一切操作都在kiana中Dev Tools下的Console完成。

创建一篇文档。

现在，我们试图插入插入数据。

PUT zhifou/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 zhifou/doc/2
{
  "name":"大娘子",
  "age":18,
  "from":"sheng",
  "desc":"貌美肤白、娇憨可爱",
  "tags":["白","富","美"]
}

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

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

PUT zhifou/doc/5
{
  "name":"魏行者",
  "age":25,
  "from":"广云台",
  "desc":"后悔没能嫁给顾老二~",
  "tags":["闭月","羞花"]
}

PUT表示创建命令，虽然命令可以小写，但我们推荐大写。以RESTFul 风格返回结果。

返回结果的信息如下：

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

查询所有索引

现在学习一条命令

GET _cat/indices?v

展示当前集群中索引情况，包括索引的健康状态、UUID、主副分片个数、大小等信息。

查询指定的索引信息

单独查看zhifu索引：

GET zhifou	

返回的结果如下：

{
  "zhifou" : {
    "aliases" : { },
    "mappings" : {
      "properties" : {
        "age" : {
          "type" : "long"
        },
        "desc" : {
          "type" : "text",
          "fields" : {
            "keyword" : {
              "type" : "keyword",
              "ignore_above" : 256
            }
          }
        },
        "from" : {
          "type" : "text",
          "fields" : {
            "keyword" : {
              "type" : "keyword",
              "ignore_above" : 256
            }
          }
        },
        "name" : {
          "type" : "text",
          "fields" : {
            "keyword" : {
              "type" : "keyword",
              "ignore_above" : 256
            }
          }
        },
        "tags" : {
          "type" : "text",
          "fields" : {
            "keyword" : {
              "type" : "keyword",
              "ignore_above" : 256
            }
          }
        }
      }
    },
    "settings" : {
      "index" : {
        "creation_date" : "1579267138792",
        "number_of_shards" : "1",
        "number_of_replicas" : "1",
        "uuid" : "thVUwigXSNu__npB0NM9Gg",
        "version" : {
          "created" : "7030099"
        },
        "provided_name" : "zhifou"
      }
    }
  }
}

返回了zhifou索引的创建信心。

查询文档信息

查看某个特定的文档信息

GET zhifou/doc/1

返回的文档信息如下：

{
  "_index" : "zhifou",
  "_type" : "doc",
  "_id" : "1",
  "_version" : 1,
  "_seq_no" : 0,
  "_primary_term" : 1,
  "found" : true,
  "_source" : {
    "name" : "顾老二",
    "age" : 30,
    "from" : "gu",
    "desc" : "皮肤黑、武器长、性格直",
    "tags" : [
      "黑",
      "长",
      "直"
    ]
  }
}

查询所有文档信息

GET zhifou/doc/_search

返回的信息如下：

{
  "took" : 116,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 5,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "顾老二",
          "age" : 30,
          "from" : "gu",
          "desc" : "皮肤黑、武器长、性格直",
          "tags" : [
            "黑",
            "长",
            "直"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "貌美肤白、娇憨可爱",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp,没怎么看清，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "4",
        "_score" : 1.0,
        "_source" : {
          "name" : "石头",
          "age" : 29,
          "from" : "gu",
          "desc" : "粗中有细、狐假虎威",
          "tags" : [
            "粗",
            "大",
            "猛"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "5",
        "_score" : 1.0,
        "_source" : {
          "name" : "魏行者",
          "age" : 25,
          "from" : "广云台",
          "desc" : "后悔没能嫁给顾老二~",
          "tags" : [
            "闭月",
            "羞花"
          ]
        }
      }
    ]
  }
}
	

删除指定索引

DELETE zhifou

DELETE zhifou/doc/5	

删除指定的文档

{
  "_index" : "zhifou",
  "_type" : "doc",
  "_id" : "5",
  "_version" : 2,
  "result" : "deleted",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 5,
  "_primary_term" : 1
}

此时在存储文档，会发现5已经不存在了。

{
  "took" : 297,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 4,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "顾老二",
          "age" : 30,
          "from" : "gu",
          "desc" : "皮肤黑、武器长、性格直",
          "tags" : [
            "黑",
            "长",
            "直"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "貌美肤白、娇憨可爱",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp,没怎么看清，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "4",
        "_score" : 1.0,
        "_source" : {
          "name" : "石头",
          "age" : 29,
          "from" : "gu",
          "desc" : "粗中有细、狐假虎威",
          "tags" : [
            "粗",
            "大",
            "猛"
          ]
        }
      }
    ]
  }
}

match查询

match系列之match(按照条件查询)

查看来自顾家的都有那些人。

GET zhifou/doc/_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。

返回结果如下：

{
  "took" : 82,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.82876295,
    "hits" : [
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.82876295,
        "_source" : {
          "name" : "顾老二",
          "age" : 30,
          "from" : "gu",
          "desc" : "皮肤黑、武器长、性格直",
          "tags" : [
            "黑",
            "长",
            "直"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 0.82876295,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp,没怎么看清，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "4",
        "_score" : 0.82876295,
        "_source" : {
          "name" : "石头",
          "age" : 29,
          "from" : "gu",
          "desc" : "粗中有细、狐假虎威",
          "tags" : [
            "粗",
            "大",
            "猛"
          ]
        }
      }
    ]
  }
}

match系列之match_all（查询全部）

GET zhifou/doc/_search
{
  "query":{
    "match_all": {}
  }
}

match_all条件为空，表示没有查询条件，那就是查询全部。就像select * from table_name一样。

查询结果如下:

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 5,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "顾老二",
          "age" : 30,
          "from" : "gu",
          "desc" : "皮肤黑、武器长、性格直",
          "tags" : [
            "黑",
            "长",
            "直"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "大娘子",
          "age" : 18,
          "from" : "sheng",
          "desc" : "貌美肤白、娇憨可爱",
          "tags" : [
            "白",
            "富",
            "美"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "name" : "龙套偏房",
          "age" : 22,
          "from" : "gu",
          "desc" : "mmp,没怎么看清，不知道怎么形容",
          "tags" : [
            "造数据",
            "真",
            "难"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "4",
        "_score" : 1.0,
        "_source" : {
          "name" : "石头",
          "age" : 29,
          "from" : "gu",
          "desc" : "粗中有细、狐假虎威",
          "tags" : [
            "粗",
            "大",
            "猛"
          ]
        }
      },
      {
        "_index" : "zhifou",
        "_type" : "doc",
        "_id" : "5",
        "_score" : 1.0,
        "_source" : {
          "name" : "魏行者",
          "age" : 25,
          "from" : "广云台",
          "desc" : "后悔没能嫁给顾老二~",
          "tags" : [
            "闭月",
            "羞花"
          ]
        }
      }
    ]
  }
}

match系列之match_phrase(短语查询)

我们现在已经对match有了基础的了解。match查询的是散列映射，包含了我们希望搜索的字段和字符串。但也带来了一些问题。

首先来创建一些数据

PUT t1/doc/1
{
  "title":"中国是世界上人口最多的国家"
}

PUT t1/doc/2
{
  "title":"美国是世界上军事实力最强大的国家"
}

PUT t1/doc/3
{
  "title":"北京市中国的首都"
}

现在，当我们以中国作为搜索条件，我们希望只返回和中国相关的文档。我们首先使用match进行查询：

GET t1/doc/_search
{
  "query":{
    "match": {
      "title": "中国"
    }
  }
}

结果如下：

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.7048458,
    "hits" : [
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 0.7048458,
        "_source" : {
          "title" : "北京市中国的首都"
        }
      },
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.6406914,
        "_source" : {
          "title" : "中国是世界上人口最多的国家"
        }
      },
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 0.16943811,
        "_source" : {
          "title" : "美国是世界上军事实力最强大的国家"
        }
      }
    ]
  }
}

虽然如期返回了中国的文档,但是把美国的文档也返回了。主要是由于Elastic Search在内部对文档进行分词的时候，对于中文来说，是一个字一个字进行切分的。

可以使用短语查询：

GET t1/doc/_search
{
  "query":{
    "match_phrase": {
      "title": "中国"
    }
  }
}

返回结果：

{
  "took" : 7,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 0.70484585,
    "hits" : [
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 0.70484585,
        "_source" : {
          "title" : "北京市中国的首都"
        }
      },
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.59047776,
        "_source" : {
          "title" : "中国是世界上人口最多的国家"
        }
      }
    ]
  }
}
		

这里match_pharse是在文档中搜索指定的词组，而中国正是一个词组，可以返回。

那么，现在想搜索中国和世界相关的文档，但是有忘记其余部分内容，就可以使用slop来解决了。

GET t1/doc/_search
{
  "query":{
    "match_phrase": {
      "title": {
        "query": "中国世界",
        "slop": 2
      }
    }
  }
}

在两个词组之间有了2个词的间隔，这个时候，就可以查询到结果了：

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.9709763,
    "hits" : [
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.9709763,
        "_source" : {
          "title" : "中国是世界上人口最多的国家"
        }
      }
    ]
  }
}

slop间隔可以根据需要进行适当的改动。

match系列之match_pharse_prefix（最左前缀查询）

如果遇到拼写beautiful拼到bea就不知道该往下怎么拼写了。这个时候，搜索引擎就看自己的词库有啥以bea开头的词。

PUT t3/doc/1
{
  "title":"maggie",
  "desc":"beautiful girl you are beautiful so "
}

PUT t3/doc/2
{
  "title":"sun and beach",
  "desc":"I like basking on the beach"
}

在这里用match和match_phrase都不太合适，因为输入的是不完整的词，可以用match_phrase_prefix

GET t3/doc/_search
{
  "query":{
    "match_phrase_prefix": {
      "desc": "bea"
    }
  }
}

结果如下：

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 0.9530774,
    "hits" : [
      {
        "_index" : "t3",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.9530774,
        "_source" : {
          "title" : "maggie",
          "desc" : "beautiful girl you are beautiful so "
        }
      },
      {
        "_index" : "t3",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 0.6931472,
        "_source" : {
          "title" : "sun and beach",
          "desc" : "I like basking on the beach"
        }
      }
    ]
  }
}

前缀查询与短语查询类似，但前缀查询可以进一步的搜索词组，只不过它是和词组中的最后一个词进行匹配，当使用这种行为进行搜索的时候，最好通过max_expansions来设置最大前缀扩展数量，因为产生的结果可能是一个很大的集合，不加限制的话，影响查询性能。

GET t3/doc/_search
{
  "query":{
    "match_phrase_prefix": {
      "desc": {
        "query": "bea",
        "max_expansions": 1
      }
    }
  }
}

结果返回：

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.9530774,
    "hits" : [
      {
        "_index" : "t3",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.9530774,
        "_source" : {
          "title" : "maggie",
          "desc" : "beautiful girl you are beautiful so "
        }
      }
    ]
  }
}

如果设置2，则两篇都返回。

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 0.9530774,
    "hits" : [
      {
        "_index" : "t3",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.9530774,
        "_source" : {
          "title" : "maggie",
          "desc" : "beautiful girl you are beautiful so "
        }
      },
      {
        "_index" : "t3",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 0.6931472,
        "_source" : {
          "title" : "sun and beach",
          "desc" : "I like basking on the beach"
        }
      }
    ]
  }
}

match 系列之multi_match(多字段查询)

现在我们有一个50个字段的索引，我们需要在多个字段中查询同一个关键字。

GET t3/doc/_search
{
  "query":{
    "multi_match": {
      "query": "beach"
      , "fields": ["title","desc"]
      
    } 
  }
}

我们可以将多个字段放到field列表中即可。以达到匹配多个字段的目的。