开发者

ElasticSearch查询文档基本操作实例

开发者 https://www.devze.com 2023-02-03 10:39 出处：网络 作者： 程序员皮卡秋
目录查询文档 & 基本操作按照ID单个按照ID批量查询文档是否存在 & 通过id判断查询部分字段内容查询文档 & 条件查询不附加任何条件相关字段解释基础分页查询url参数body 参数单字段全文索引查询单字段不分
相关专题：ElasticSearch文档操作ElasticSearch查询文档
目录
  • 查询文档 & 基本操作
    • 按照ID单个
    • 按照ID批量
    • 查询文档是否存在 & 通过id判断
    • 查询部分字段内容
  • 查询文档 & 条件查询
    • 不附加任何条件
    • 相关字段解释
    • 基础分页查询
    • url参数
    • body 参数
    • 单字段全文索引查询
    • 单字段不分词查询
    • match分词结果
    • match_phrase 不分词查询结果
    • 多字段全文索引查询
    • 范围查询
    • 单字段精确查询
    • 字段精确查询 & 多值
    • 文档包含字段查询
  • 结束语

    查询文档 & 基本操作

    为了方便学习, 本节中所有示例沿用上节的索引

    按照ID单个

    GET class_1/_doc/1

    查询结果:

    {
  "_index" : "class_1",
  "_type" : "_doc",
  "_id" : "1",
  "_version" : 4,
  "_seq_no" : 4,
  "_primary_term" : 3,
  "found" : true,
  "_source" : {
    "name" : "l",
    "num" : 6
  }
}

    按照ID批量

    GET class_1/_mget
{
"ids":[1,2,3]
}

    返回:

    {
  "docs" : [
  编程客栈  {
      "_index" : "class_1",
      "_type" : "_doc",
      "_id" : "1",
      "_version" : 4,
      "_seq_no" : 4,
      "_primary_term" : 3,
      "found" : true,
      "_source" : {
        "name" : "l",
        "num" : 6
      }
    },
    {
      "_index" : "class_1",
      "_type" : "_doc",
      "_id" : "2",
      "found" : false
    },
    {
      "_index" : "class_1",
      "_type" : "_doc",
      "_id" : "3",
      "_version" : 3,
      "_seq_no" : 10,
      "_primary_term" : 4,
      "found" : true,
      "_source" : {
        "num" : 9,
        "name" : "e",
        "age" : 9,
        "desc" : [
          "hhhh"
        ]
      }
    }
  ]
}

    查询文档是否存在 & 通过id判断

    HEAD class_1/_doc/1

    返回:

    200 - OK

    HEAD class_1/_doc/1000

    返回:

    404 - Not Found

    查询部分字段内容

    GET class_1/_doc/1?_source_includes=name

    返回:

    {
  "_index" : "class_1",
  "_type" : "_doc",
  "_id" : "1",
  "_version" : 4,
  "_seq_no" : 4,
  "_primary_term" : 3,
  "found" : true,
  "_source" : {
    "name" : "l"
  }
}

    可以看到只返回了name字段, 以上是一个基本的操作，下面给大家讲下条件查询~

    查询文档 & 条件查询

    查询的复杂度取决于它附加的条件约束，跟我们写sql一样。下面就带大家一步一步看一下ES中如何进行条件查询~

    不附加任何条件

    GET class_1/_search

    返回:

    {
  "took" : 15,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 8,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "h2Fg-4UBECmbBdQA6VLg",
        "_score" : 1.0,
        "_source" : {
          "name" : "b",
          "num" : 6
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "iGFt-4UBECmbBdQAnVJe",
        "_score" : 1.0,
        "_source" : {
          "name" : "g",
          "age" : 8
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "iWFt-4UBECmbBdQAnVJg",
        "_score" : 1.0,
        "_source" : {
          "name" : "h",
          "age" : 9
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "imFt-4UBECmbBdQAnVJg",
        "_score" : 1.0,
        "_source" : {
          "name" : "i",
          "age" : 10
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "num" : 9,
          "name" : "e",
          "age" : 9,
          "desc" : [
            "hhhh"
          ]
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "4",
        "_score" : 1.0,
        "_source" : {
          "name" :php "f",
          "age" : 10,
          "num" : 10
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "RWlfBIUBDuA8yW5cu9wu",
        "_score" : 1.0,
        "_source" : {
          "name" : "一年级",
          "num" : 20
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "l",
          "num" : 6
        }
      }
    ]
  }
}

    可以看到索引class_1中的所有数据都是上节添加的。这里提一下，我们也可以添加多个索引一起查，然后返回,用,逗号隔开就可以了

    GET class_1,class_2,class_3/_search

    {
  "took" : 7,
  "timed_out" : false,
  "_shards" : {
    "total" : 开发者_开发学习5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 9,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "h2Fg-4UBECmbBdQA6VLg",
        "_score" : 1.0,
        "_source" : {
          "name" : "b",
          "num" : 6
        }
      },
      {
        "_index" : "class编程_2",
        "_type" : "_doc",
        "_id" : "RWlfBIUBDuA8yW5cu9wu",
        "_score" : 1.0,
        "_source" : {
          "name" : "一年级",
          "num" : 20
        }
      },
      ....
    ]
  }
}

    可以看到返回了索引class_2中的数据，并且合并到了一起。

    相关字段解释

    有的小伙伴可能对返回的字段有点陌生，这里给大家统一解释一下：

    {
    "took":"查询操作耗时，单位毫秒",
    "timed_out":"是否超时",
    "_shards":{
        "total":"分片总数",
        "successful":"执行成功分片数",
        "skipped":"执行忽略分片数",
        "failed":"执行失败分片数"
    },
    "hits":{
        "total":{
            "value":"条件查询命中数",
            "relation":"计数规则(eq计数准确/gte计数不准确)"
        },
        "max_score":"最大匹配度分值",
        "hits":[
            {
                "_index":"命中结果索引",
                "_id":"命中结果ID",
                "_score":"命中结果分数",
                "_source":"命中结果原文档信息"
            }
        ]
    }
}

    下面我们看下带条件的查询~

    基础分页查询

    基本语法: es中通过参数size和from来进行基础分页的控制

    • from：指定跳过多少条数据
    • size：指定返回多少条数据

    下面看下示例：

    url参数

    GET class_1/_search?from=2&size=2

    返回:

    {
  "took" : 5,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 8,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "iWFt-4UBECmbBdQAnVJg",
        "_score" : 1.0,
        "_source" : {
          "name" : "h",
          "age" : 9
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "imFt-4UBECmbBdQAnVJg",
        "_score" : 1.0,
        "_source" : {
          "name" : "i",
          "age" : 10
        }
      }
    ]
  }
}

    body 参数

    GET class_1/_search
{
    "from" : 2,
    "size" : 2
}

    返回结果和上面是一样的~

    单字段全文索引查询

    这个大家应该不陌生，前面几节都见过。使用query.match进行查询,match适用与对单个字段基于全文索引进行数据检索。对于全文字段，match使用特定的分词进行全文检索。而对于那些精确值，match同样可以进行精确匹配,match查询短语时，会对短语进行分词，再针对每个词条进行全文检索。

    GET class_1/_search
{
  "query": {
    "match": {
      "name":"i"
    }
  }
}

    返回:

    {
  "took" : 4,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.3862942,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "imFt-4UBECmbBdQAnVJg",
        "_score" : 1.3862942,
        "_source" : {
          "name" : "i",
          "age" : 10
        }
      }
    ]
  }
}

    单字段不分词查询

    使用query.match_phrase进行查询, 它与match的区别就是不进行分词,干说，可能有点抽象，下面我们通过一个例子给大家分清楚:

    先造点数据进去：

    PUT class_1/_bulk
{ "create":{  } }
{"name":"I eat apple so haochi1~","num": 1}
{ "create":{  } }
{ "name":"I eat apple so zhen haochi2~","num": 1}
{ "create":{  } }
{"name":"I eat apple so haochi3~","num": 1}

    假设有这么几个句子，现在我有一个需求我要把I eat apple so zhen haochi2~这句话匹配出来

    match分词结果

    GET class_1/_search
{
  "query": {
    "match": {
      "name": "apple so zhen"
    }
  }
}

    返回：

    {
  "took" : 15,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 2.2169428,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : 2.2169428,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : 1.505254,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : 1.505254,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        }
      }
    ]
  }
}

    从结果来看，刚刚的几句话都被查出来了，但是结果并大符合预期。从score来看，"_score" : 2.2169428得分最高，排在了第一，语句是I eat apple so zhen haochi2~,说明匹配度最高，这个句子正是我们想要的结果~

    match_phrase 不分词查询结果

    GET class_1/_search
{
  "query": {
    "match_phrase": {
      "name": "apple so zhen"
    }
  }
}

    结果:

    {
  "took" : 6,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 2.2169428,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : 2.2169428,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        }
      }
    ]
  }
}

    结果符合预期，只返回了我们想要的那句。那么match为什么都返回了，这就是前面讲到的分词,首先会对name: apple so zhen进行分词,也就是说存在apple的都会被返回。

    当然，真正业务中的需求比这个复杂多了，这里只是为了给大家做区分~ 下面接着看~

    多字段全文索引查询

    相当于对多个字段执行了match查询, 这里需要注意的是query的类型要和字段类型一致，不然会报类型异常

    GET class_1/_search
{
  "query": {
    "multi_match": {
      "query": "apple",
      "fields": ["name","desc"]
    }
  }
}

    {
  "took" : 5,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 0.752627,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : 0.752627,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : 0.752627,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090miyjed7YE",
        "_score" : 0.7389809,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        }
      }
    ]
  }
}

    范围查询

    使用range来进行范围查询，适用于数组，时间等字段

    GET class_1/_search
{
  "query": {
    "range": {
      "num": {
        "gt": 5,
        "lt": 10
      }
    }
  }
}

    返回:

    {
  "took" : 6,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 3,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "h2Fg-4UBECmbBdQA6VLg",
        "_score" : 1.0,
        "_source" : {
          "name" : "b",
          "num" : 6
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "num" : 9,
          "name" : "e",
          "age" : 9,
          "desc" : [
            "hhhh"
          ]
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
     编程客栈   "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "l",
          "num" : 6
        }
      }
    ]
  }
}

    单字段精确查询

    使用term进行非分词字段的精确查询。需要注意的是，对于那些分词的字段，即使查询的value是一个完全匹配的短语，也无法完成查询

    GET class_1/_search
{
 "query": {
   "term": {
     "num": {
       "value": "9"
     }
   }
 }
}

    返回:

    {
  "took" : 4,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "num" : 9,
          "name" : "e",
          "age" : 9,
          "desc" : [
            "hhhh"
          ]
        }
      }
    ]
  }
}

    字段精确查询 & 多值

    与term一样, 区别在于可以匹配一个字段的多个值，满足一个即检索成功

    GET class_1/_search
{
 "query": {
   "terms": {
     "num": [
      9,
      1
     ]
   }
 }
}

    返回:

    {
  "took" : 8,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 4,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "num" : 9,
          "name" : "e",
          "age" : 9,
          "desc" : [
            "hhhh"
          ]
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "b8fcCoYB090miyjed7YE",
        "_score" : 1.0,
        "_source" : {
          "name" : "I eat apple so haochi1~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "ccfcCoYB090miyjed7YE",
        "_score" : 1.0,
        "_source" : {
          "name" : "I eat apple so haochi3~",
          "num" : 1
        }
      },
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "cMfcCoYB090http://www.devze.commiyjed7YE",
        "_score" : 1.0,
        "_source" : {
          "name" : "I eat apple so zhen haochi2~",
          "num" : 1
        }
      }
    ]
  }
}

    文档包含字段查询

    为了确定当前索引有哪些文档包含了对应的字段，es中使用exists来实现

    GET class_1/_search
{
  "query": {
    "exists": {
      "field": "desc"
    }
  }
}

    返回:

    {
  "took" : 8,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "class_1",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "num" : 9,
          "name" : "e",
          "age" : 9,
          "desc" : [
            "hhhh"
          ]
        }
      }
    ]
  }
}

    结束语

    本节主要讲了ES中的文档查询API操作，该部分内容较多, 下节继续给大家讲，就先消化这么多~API大家都不要去背，多敲几遍就记住了，关键是多用，多总结 。

    以上就是ElasticSearch查询文档基本操作实例的详细内容，更多关于ElasticSearch查询文档的资料请关注我们其它相关文章！

    0

    上一篇:

    :下一篇

    更多 开发 相关资讯：

    精彩评论

    暂无评论...
    登录 注册
    Qedev.com
    验证码 换一张
    取 消

    关注公众号

    热门标签

    图文推荐

    SpringBoot整合Liquibase实现对数据库管理和迁移

    SpringBoot整合Liquibase实现对数据库管理和迁移
    javacv ffmpeg使用原生ffmpeg命令方式

    javacv ffmpeg使用原生ffmpeg命令方式
    Linux管道揭秘之匿名管道连接进程世界的方法

    Linux管道揭秘之匿名管道连接进程世界的方法
    SpringBoot配置文件启动加载顺序的方法步骤

    SpringBoot配置文件启动加载顺序的方法步骤
    SpringBoot前后端传输加密设计实现方案

    SpringBoot前后端传输加密设计实现方案
    SpringBoot参数校验的一些实战应用

    SpringBoot参数校验的一些实战应用
    Springboot3集成Knife4j的步骤以及使用(最完整版)

    Springboot3集成Knife4j的步骤以及使用(最完整版)
    SpringBoot中的@Configuration、@MapperScan注解

    SpringBoot中的@Configuration、@MapperScan注解

    开发者开发者网给大家分享系统运维,大数据运维,云计算,编程开发技巧,路由交换,运维和开发相关的资讯及技术文章，同时StackOverflow中文社区，知识经验交流分享。

    法律声明：本站内容均为网友上传，网站举办方负责审核和监督，如存在版权或非法内容，欢迎举报，我们将尽快予以删除。邮箱：devze@qq.com

    Copyright © 2018-2020 开发者. All rights reserved. Powered by 开发者ICP备案号: 京ICP备10032868号-9