【Elasticsearch】Elasticsearch检索方式全解析：从基础到实战（一）

引言

在大数据时代，高效的数据检索能力是众多应用系统的关键需求。Elasticsearch作为一款强大的开源分布式搜索和分析引擎，提供了两种基本的检索方式，帮助开发者从海量数据中精准获取所需信息。这两种检索方式各有特点，适用于不同的业务场景和查询需求。本文将深入探讨这两种检索方式，并通过丰富的示例和详细的解释，帮助读者全面掌握Elasticsearch的检索技巧。

数据准备：数据JSON

Elasticsearch检索方式概述

两种检索方式介绍

Elasticsearch支持通过REST request uri发送搜索参数和通过REST request body发送搜索参数这两种基本检索方式。理解这两种方式的差异和适用场景，是高效使用Elasticsearch的基础。

方式一：通过REST request uri发送搜索参数

1. 原理：将搜索参数以查询字符串的形式直接附加在URI后面，传递给Elasticsearch服务器。这种方式简单直观，适用于简单的搜索场景。
2. 示例：

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

3. 参数解释：
   • q=*：q代表查询条件，*是通配符，表示查询所有文档。
   • sort=account_number:asc：sort用于指定排序规则，这里表示按照account_number字段进行升序排列，asc表示升序，desc表示降序。
4. 返回结果分析：

{"took" : 235,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1000,"relation" : "eq"},"max_score" : null,"hits" : [{"_index" : "bank","_type" : "account","_id" : "0","_score" : null,"_source" : {"account_number" : 0,"balance" : 16623,"firstname" : "Bradshaw","lastname" : "Mckenzie","age" : 29,"gender" : "F","address" : "244 Columbus Place","employer" : "Euron","email" : "[e-mail]","city" : "Hobucken","state" : "CO"},"sort" : [0]},// 此处省略其他文档数据]}
}

- `took`：表示Elasticsearch执行查询所花费的时间，单位为毫秒，这里是235毫秒，反映了查询的执行效率。
- `timed_out`：表示搜索请求是否超时，`false`表示未超时，说明查询在规定时间内顺利完成。
- `_shards`：包含搜索的分片信息，`total`表示总分片数，`successful`表示成功搜索的分片数，`skipped`表示跳过的分片数，`failed`表示搜索失败的分片数。这里总分片数为1，且成功搜索了1个分片，说明搜索过程顺利。
- `hits.total.value`：表示找到的匹配文档数量，这里是1000，说明在`bank`索引中共有1000个文档符合查询条件（因为这里是查询所有文档）。
- `max_score`：表示文档的最高相关性得分，由于使用`match_all`查询所有文档，没有相关性得分的概念，所以为`null`。
- `hits.sort`：表示文档的排序位置（当不按相关性得分排序时），这里按照`account_number`升序排列，所以每个文档的`sort`值就是其`account_number`的值。
- `hits._score`：表示文档的相关性得分（使用`match_all`时不适用），这里为`null`。

方式二：通过REST request body发送搜索参数

原理：将搜索参数放在HTTP请求的消息体中发送给Elasticsearch服务器，使用的是一种领域对象语言（DSL），以JSON格式来定义复杂的查询条件、排序规则、分页设置等。这种方式灵活性高，能够满足复杂的搜索需求。

（1）基本语法格式

Elasticsearch提供了一个可以执行查询的Json风格的DSL。这个被称为Query DSL，该查询语言非常全面。

一个查询语句的典型结构

QUERY_NAME:{ARGUMENT:VALUE,ARGUMENT:VALUE,...
}

如果针对于某个字段，那么它的结构如下：

{QUERY_NAME:{FIELD_NAME:{ARGUMENT:VALUE,ARGUMENT:VALUE,...}   }
}

GET bank/_search
{"query": {"match_all": {}},"from": 0,"size": 5,"sort": [{"account_number": {"order": "desc"}}]
}
//match_al查询所有，从第0个数据拿5个数据

query定义如何查询；

• match_all查询类型【代表查询所有的所有】，es中可以在query中组合非常多的查询类型完成复杂查询；
• 除了query参数之外，我们可也传递其他的参数以改变查询结果，如sort，size；
• from+size限定，完成分页功能；
• sort排序，多字段排序，会在前序字段相等时后续字段内部排序，否则以前序为准；

（2）返回部分字段

GET bank/_search
{"query": {"match_all": {}},"from": 0,"size": 5,"sort": [{"account_number": {"order": "desc"}}],"_source": ["balance","firstname"]}

查询结果：

{"took" : 18,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1000,"relation" : "eq"},"max_score" : null,"hits" : [{"_index" : "bank","_type" : "account","_id" : "999","_score" : null,"_source" : {"firstname" : "Dorothy","balance" : 6087},"sort" : [999]},{"_index" : "bank","_type" : "account","_id" : "998","_score" : null,"_source" : {"firstname" : "Letha","balance" : 16869},"sort" : [998]},{"_index" : "bank","_type" : "account","_id" : "997","_score" : null,"_source" : {"firstname" : "Combs","balance" : 25311},"sort" : [997]},{"_index" : "bank","_type" : "account","_id" : "996","_score" : null,"_source" : {"firstname" : "Andrews","balance" : 17541},"sort" : [996]},{"_index" : "bank","_type" : "account","_id" : "995","_score" : null,"_source" : {"firstname" : "Phelps","balance" : 21153},"sort" : [995]}]}
}

（3）match匹配查询

• 基本类型（非字符串），“account_number”: 20 可加可不加“ ” 不加就是精确匹配

GET bank/_search
{"query": {"match": {"account_number": "20"}}
}

match返回account_number=20的数据。

查询结果：

{"took" : 1,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1,"relation" : "eq"},"max_score" : 1.0,"hits" : [{"_index" : "bank","_type" : "account","_id" : "20","_score" : 1.0,"_source" : {"account_number" : 20,"balance" : 16418,"firstname" : "Elinor","lastname" : "Ratliff","age" : 36,"gender" : "M","address" : "282 Kings Place","employer" : "Scentric","email" : "[e-mail]","city" : "Ribera","state" : "WA"}}]}
}

• 字符串，全文检索“ ” 模糊查询

GET bank/_search
{"query": {"match": {"address": "kings"}}
}

全文检索，最终会按照评分进行排序，会对检索条件进行分词匹配。

查询结果：

{"took" : 30,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 2,"relation" : "eq"},"max_score" : 5.990829,"hits" : [{"_index" : "bank","_type" : "account","_id" : "20","_score" : 5.990829,"_source" : {"account_number" : 20,"balance" : 16418,"firstname" : "Elinor","lastname" : "Ratliff","age" : 36,"gender" : "M","address" : "282 Kings Place","employer" : "Scentric","email" : "[e-mail]","city" : "Ribera","state" : "WA"}},{"_index" : "bank","_type" : "account","_id" : "722","_score" : 5.990829,"_source" : {"account_number" : 722,"balance" : 27256,"firstname" : "Roberts","lastname" : "Beasley","age" : 34,"gender" : "F","address" : "305 Kings Hwy","employer" : "Quintity","email" : "[e-mail]","city" : "Hayden","state" : "PA"}}]}
}

（4） match_phrase [短句匹配]

将需要匹配的值当成一整个单词（不分词）进行检索

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

查处address中包含mill_road的所有记录，并给出相关性得分

查看结果：

{"took" : 32,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1,"relation" : "eq"},"max_score" : 8.926605,"hits" : [{"_index" : "bank","_type" : "account","_id" : "970","_score" : 8.926605,"_source" : {"account_number" : 970,"balance" : 19648,"firstname" : "Forbes","lastname" : "Wallace","age" : 28,"gender" : "M","address" : "990 Mill Road","employer" : "Pheast","email" : "[e-mail]","city" : "Lopezo","state" : "AK"}}]}
}

match_phrase和match的区别，观察如下实例：

match_phrase是做短语匹配

match是分词匹配，例如990 Mill匹配含有990或者Mill的结果

GET bank/_search
{"query": {"match_phrase": {"address": "990 Mill"}}
}

查询结果：

{"took" : 0,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1,"relation" : "eq"},"max_score" : 10.806405,"hits" : [{"_index" : "bank","_type" : "account","_id" : "970","_score" : 10.806405,"_source" : {"account_number" : 970,"balance" : 19648,"firstname" : "Forbes","lastname" : "Wallace","age" : 28,"gender" : "M","address" : "990 Mill Road","employer" : "Pheast","email" : "[e-mail]","city" : "Lopezo","state" : "AK"}}]}
}

使用match的keyword

GET bank/_search
{"query": {"match": {"address.keyword": "990 Mill"}}
}

查询结果，一条也未匹配到

{"took" : 0,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 0,"relation" : "eq"},"max_score" : null,"hits" : [ ]}
}

修改匹配条件为“990 Mill Road”

GET bank/_search
{"query": {"match": {"address.keyword": "990 Mill Road"}}
}

查询出一条数据

{"took" : 1,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 1,"relation" : "eq"},"max_score" : 6.5032897,"hits" : [{"_index" : "bank","_type" : "account","_id" : "970","_score" : 6.5032897,"_source" : {"account_number" : 970,"balance" : 19648,"firstname" : "Forbes","lastname" : "Wallace","age" : 28,"gender" : "M","address" : "990 Mill Road","employer" : "Pheast","email" : "[e-mail]","city" : "Lopezo","state" : "AK"}}]}
}

文本字段的匹配，使用keyword，匹配的条件就是要显示字段的全部值，要进行精确匹配的。

match_phrase是做短语匹配，只要文本中包含匹配条件既包含这个短语，就能匹配到。

（5）multi_math【多字段匹配】

GET bank/_search
{"query": {"multi_match": {"query": "mill","fields": ["state","address"]}}
}

state或者address中包含mill，并且在查询过程中，会对于查询条件进行分词。

查询结果：

{"took" : 28,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 4,"relation" : "eq"},"max_score" : 5.4032025,"hits" : [{"_index" : "bank","_type" : "account","_id" : "970","_score" : 5.4032025,"_source" : {"account_number" : 970,"balance" : 19648,"firstname" : "Forbes","lastname" : "Wallace","age" : 28,"gender" : "M","address" : "990 Mill Road","employer" : "Pheast","email" : "[e-mail]","city" : "Lopezo","state" : "AK"}},{"_index" : "bank","_type" : "account","_id" : "136","_score" : 5.4032025,"_source" : {"account_number" : 136,"balance" : 45801,"firstname" : "Winnie","lastname" : "Holland","age" : 38,"gender" : "M","address" : "198 Mill Lane","employer" : "Neteria","email" : "[e-mail]","city" : "Urie","state" : "IL"}},{"_index" : "bank","_type" : "account","_id" : "345","_score" : 5.4032025,"_source" : {"account_number" : 345,"balance" : 9812,"firstname" : "Parker","lastname" : "Hines","age" : 38,"gender" : "M","address" : "715 Mill Avenue","employer" : "Baluba","email" : "[e-mail]","city" : "Blackgum","state" : "KY"}},{"_index" : "bank","_type" : "account","_id" : "472","_score" : 5.4032025,"_source" : {"account_number" : 472,"balance" : 25571,"firstname" : "Lee","lastname" : "Long","age" : 32,"gender" : "F","address" : "288 Mill Street","employer" : "Comverges","email" : "[e-mail]","city" : "Movico","state" : "MT"}}]}
}