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ES的安装部署以及基本操作

一、背景

像百度、Google的网页搜索，能根据我们输入的关键字模糊匹配返回相关搜索信息，并高亮显示我们的搜索关键字。这种大量的非结构化文本检索，关系型数据库并不能很好的支持（1、非结构化数据关系型数据库支持并不好 2、即便依据常用于搜索的和关键字建立索引，模糊查询的效率也是低下的因为压根走不到索引 3、支持搜索的灵活性很重要）。

全文搜索引擎，是对文章中的每个词进行扫描，并对每个词建立索引，存下来这些词在文章中所在的页码和次数，检索的时候根据建立的索引进行查找，并将查询结果进行反馈。

二、什么是ES

ElasticSearch是一个分布式、Restful风格的搜索和数据分析引擎，能够解决不断涌现的各种用例。ES 是一个开源的高扩展的分布式全文搜索引擎，它可以近乎实时的存储、检索数据；本身扩展性很好，可以扩展到上百台服务器，处理 PB 级别的数据。

三、下载安装

下载链接

Past Releases of Elastic Stack Software | Elastic

目前最新版本是 Elasticsearch 8.17.1 2025年1月22日。但不建议直接使用最新，使用一个靠近最新版本的的就可（这样稳定性会更好一些）

windows版本的解压即安装结束

然后添加环境变量 ES_HOME 值为ES的根目录。在path中添加 %ES_HOME%\bin

3.1 主要目录

目录	含义
bin	用于启动和管理Elasticsearch的脚本和工具
config	Elasticsearch的配置文件
jdk	内置 JDK 目录，如果本机配置了java_home使用的是本机的jdk
lib	依赖库目录
logs	日志文件目录
modules	核心模块目录
plugins	插件目录

9300端口为组件通讯窗口，9200为浏览器访问的http协议RESTful端口

localhpost:9200

打开网页访问上述url，能看到正常的回显信息

3.2 什么是RESTful

REST 指的是一组架构约束条件和原则。满足这些约束条件和原则的应用程序或设计就
是 RESTful。Web 应用程序最重要的 REST 原则是，客户端和服务器之间的交互在请求之
间是无状态的。从客户端到服务器的每个请求都必须包含理解请求所必需的信息。如果服务
器在请求之间的任何时间点重启，客户端不会得到通知。此外，无状态请求可以由任何可用
服务器回答，这十分适合云计算之类的环境。客户端可以缓存数据以改进性能。

（太具体的规则真没看明白，后续补充吧）

四 HTTP操作

4.1 索引

索引相当于关系型数据库中的schema。

（1）创建索引

用apipost向ES发起put请求

http://127.0.0.1:9200/test

返回结果如下

{"acknowledged": true,"shards_acknowledged": true,"index": "test"
}

索引test建立成功。重复建立索引则会失败并返回如下结果

{"error": {"root_cause": [{"type": "resource_already_exists_exception","reason": "index [test/M6Qd4rchT56iUlDJZWHWmA] already exists","index_uuid": "M6Qd4rchT56iUlDJZWHWmA","index": "test"}],"type": "resource_already_exists_exception","reason": "index [test/M6Qd4rchT56iUlDJZWHWmA] already exists","index_uuid": "M6Qd4rchT56iUlDJZWHWmA","index": "test"},"status": 400
}

索引test已经存在

（2）查看已有索引

发起get请求

http://127.0.0.1:9200/_cat/indices?v 

响应结果如下

health status index uuid                   pri rep docs.count docs.deleted store.size pri.store.size
yellow open   test  M6Qd4rchT56iUlDJZWHWmA   1   1          0            0       208b           208b

表头	说明	案例
health	当前服务器健康状态 green(集群完整) yellow(单点正常、集群不完整) red(单点不正常)	yellow
status	索引打开、关闭状态	open
index	索引名	test
uuid	索引统一编号	M6Qd4rchT56iUlDJZWHWmA
pri	主分片数量	1
rep	副本数量	1
docs.count	可用文档数量	0
docs.deleted	文档删除状态（逻辑删除）	0
store.size	主分片和副分片整体占空间大小	208b
pri.store.size	主分片占空间大小	208b

（3）查看单个索引

发起get请求

http://127.0.0.1:9200/test

响应结果如下

{"test": {"aliases": {},"mappings": {},"settings": {"index": {"creation_date": "1738905447076","number_of_shards": "1","number_of_replicas": "1","uuid": "M6Qd4rchT56iUlDJZWHWmA","version": {"created": "7080099"},"provided_name": "test"}}}
}

（4）删除索引

发起DELETE请求

http://127.0.0.1:9200/test

响应结果如下

{"acknowledged": true
}

4.2 文档

（1）创建文档

文档可以类比为关系型数据库中的 table

发起POST请求

http://127.0.0.1:9200/test/_doc 

在body中选择 raw，body类型为json，body内容如下

{ "title":"天选之子", "category":"老司机", "images":"", "price":100 
} 

响应结果如下

{"_index": "test","_type": "_doc","_id": "0usM35QBJ6wHPuS349Jo","_version": 1,"result": "created","_shards": {"total": 2,"successful": 1,"failed": 0},"_seq_no": 0,"_primary_term": 1
}

也可以执行文档id。比如指定文档的id为 123

http://127.0.0.1:9200/test/_doc/123

（2）查看文档

可以根据文档的id查看指定的文档

发起GET请求

http://127.0.0.1:9200/test/_doc/123

响应信息如下

{"_index": "test","_type": "_doc","_id": "123","_version": 1,"_seq_no": 1,"_primary_term": 1,"found": true,"_source": {"title": "天选之子","category": "老司机","images": "","price": 100}
}

（3）修改文档

发起POST请求，修改id为 123 的文档

http://127.0.0.1:9200/test/_doc/123

body内容为

{ "title":"天选之子123", "category":"老司机", "images":"", "price":100 
} 

响应信息如下

{"_index": "test","_type": "_doc","_id": "123","_version": 2,"result": "updated","_shards": {"total": 2,"successful": 1,"failed": 0},"_seq_no": 2,"_primary_term": 1
}

（4）修改字段

发起POST请求，修改id为 123 的文档

http://127.0.0.1:9200/test/_update/123

body内容为

{ "doc":{"price":111  }
} 

相应内容如下

{"_index": "test","_type": "_doc","_id": "123","_version": 3,"result": "updated","_shards": {"total": 2,"successful": 1,"failed": 0},"_seq_no": 3,"_primary_term": 1
}

（5）删除文档

发起DELETE请求，删除id为 123 的文档

http://127.0.0.1:9200/test/_doc/123

响应信息如下

{"_index": "test","_type": "_doc","_id": "123","_version": 4,"result": "deleted","_shards": {"total": 2,"successful": 1,"failed": 0},"_seq_no": 4,"_primary_term": 1
}

也可以按照条件进行删除（不建议，保险起见还是按照id删除比较好）

发起 POST 请求，删除price字段为 111 的文档

http://127.0.0.1:9200/test/_delete_by_query

请求体内容为

{ "query":{ "match":{ "price":111 } } 
}

响应结果如下

{"took": 1033,"timed_out": false,"total": 1,"deleted": 1,"batches": 1,"version_conflicts": 0,"noops": 0,"retries": {"bulk": 0,"search": 0},"throttled_millis": 0,"requests_per_second": -1,"throttled_until_millis": 0,"failures": []
}

4.3 映射

映射笔者理解其实就是文档的描述。文档类似于二维数据库中的二维表。而映射类似于二维表的元数据。

（1）创建映射

发起PUT请求

http://127.0.0.1:9200/test/_mapping

body

{"properties": {"name": {"type": "text","index": true,"store": false},"sex": {"type": "text","index": false,"store": false},"age": {"type": "long","index": false,"store": false}}
}

type类型

类型	描述
String	text：可分词 keyword：不可分词，数据会作为完整字段进行匹配
Numerical	基本数据类型：long、integer、short、byte、double、float、half_float 浮点数的高精度类型：scaled_float
Date	日期类型
Array	数组类型
Object	对象

index是否索引，默认为true。true可以用来搜索。

store是否独立存储。默认为false，获取独立存储的字段会更快一些，但存储会占用更多的空间。

analyzer分词器

响应结果如下

{"acknowledged": true
}

（2）查看映射

发送GET请求

http://127.0.0.1:9200/test/_mapping 

响应结果如下

{"test": {"mappings": {"properties": {"age": {"type": "long","index": false},"category": {"type": "text","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"images": {"type": "text","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"name": {"type": "text"},"price": {"type": "long"},"sex": {"type": "text","index": false},"title": {"type": "text","fields": {"keyword": {"type": "keyword","ignore_above": 256}}}}}}
}

（3）索引和映射关联

建立索引并关联映射

发起PUT请求

http://127.0.0.1:9200/test1

body

{"settings": {},"mappings": {"properties": {"name": {"type": "text","index": true},"sex": {"type": "text","index": false},"age": {"type": "long","index": false}}}
}

响应结果如下

{"acknowledged": true,"shards_acknowledged": true,"index": "test1"
}

4.4 查询操作

（1）查询所有文档

查询索引 test1 下的所有文档

发起GET请求

http://127.0.0.1:9200/test1/_search

body

{"query": {"match_all": {}}
}

响应结果如下

{"took": 181,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 3,"relation": "eq"},"max_score": 1,"hits": [{"_index": "test1","_type": "_doc","_id": "1001","_score": 1,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 30}},{"_index": "test1","_type": "_doc","_id": "1002","_score": 1,"_source": {"name": "lisi","nickname": "lisi","sex": "男","age": 20}},{"_index": "test1","_type": "_doc","_id": "1003","_score": 1,"_source": {"name": "wangwu","nickname": "wangwu","sex": "女","age": 40}}]}
}

（2）按照字段进行查询

查询name为张三的文档（此处因为name是映射索引，其他字段不可用于此查询）

发起GET请求

http://127.0.0.1:9200/test1/_search

body

{"query": {"match": {"name":"zhangsan" }}
}

响应结果如下

{"took": 360,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 1,"relation": "eq"},"max_score": 0.9808291,"hits": [{"_index": "test1","_type": "_doc","_id": "1001","_score": 0.9808291,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 30}}]}
}

（3）按照多个字段进行查询

查询name和nickname都是zhangsan的文档

发起GET请求

http://127.0.0.1:9200/test1/_search

body

{"query": {"multi_match": {"query": "zhangsan","fields": ["name","nickname"]}}
}

返回结果如下

{"took": 116,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 1,"relation": "eq"},"max_score": 0.9808291,"hits": [{"_index": "test1","_type": "_doc","_id": "1001","_score": 0.9808291,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 30}}]}
}

（4）字段精确查询

（此处因为name是映射索引，其他字段不可用于此查询）

发起GET请求

http://127.0.0.1:9200/test1/_search

body

{"query": {"term": {"name": {"value": "zhangsan"}}}
}

（5）多字段精确查询

发起GET请求

http://127.0.0.1:9200/test1/_search

body

{"query": {"terms": {"name": ["zhangsan","lisi"]}}
}

（6）查询部分字段

一般的查询回将保存在 _source 中的字段全部返回，如果返回个别则需要进行如下操作

发起GET请求

http://127.0.0.1:9200/test1/_search

body

{"_source": ["name","nickname"],"query": {"terms": {"name": ["zhangsan"]}}
}

也可以通过includes来指定需要显示的字段，或者用excludes指定不需要显示的字段

body

{"_source": {"includes": ["name","nickname"]},"query": {"terms": {"name": ["zhangsan"]}}
}

{"_source": {"excludes": ["age","sex"]},"query": {"terms": {"name": ["zhangsan"]}}
}

（7）组合查询

通过must（必须 ）、must_not（必须不）、should（应该）的方式进行组合

should选项不会影响响应结果，但是满足should条件的文档评分会更高，可以通过 minimum_should_match参数指定至少需要满足的 should`条件的数量。如果未指定，则默认为 0

{"query": {"bool": {"must": [{"match": {"name": "zhangsan"}}],"must_not": [{"match": {"age": "40"}}],"should": [{"match": {"sex": "男"}}]}}
}

（8）范围查询

操作	说明
gt	>
lt	<
gte	>=
lte	<=

body

{"query": {"range": {"age": {"gte": 30,"lte": 35}}}
} 

此处笔者查询出错，因为我的age在映射中不是index

（9）模糊查询

当一个词变更为另一个词需要的变更次数叫做编辑距离

fuzzy 查询可以指定编辑距离内模糊匹配满足条件的结果

查询name包含 zhangsan 字符串的文档（所有编辑距离）

{"query": {"fuzzy": {"name": {"value": "zhangsan"}}}
}

响应结果

{"took": 365,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 2,"relation": "eq"},"max_score": 1.2039728,"hits": [{"_index": "test1","_type": "_doc","_id": "1001","_score": 1.2039728,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 30}},{"_index": "test1","_type": "_doc","_id": "1004","_score": 1.0534762,"_source": {"name": "zhangsan1","nickname": "zhangsan1","sex": "女","age": 50}}]}
}

查询name包含 zhangsan 字符串的文档（编辑距离为2）

{"query": {"fuzzy": {"name": {"value": "zhangsan","fuzziness": 1}}}
}

响应结果

{"took": 365,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 2,"relation": "eq"},"max_score": 1.2039728,"hits": [{"_index": "test1","_type": "_doc","_id": "1001","_score": 1.2039728,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 30}},{"_index": "test1","_type": "_doc","_id": "1004","_score": 1.0534762,"_source": {"name": "zhangsan1","nickname": "zhangsan1","sex": "女","age": 50}}]}
}

（10）排序

查询name为 zhangsan， age 降序，评分降序

{"query": {"match": {"name": "zhangsan"}},"sort": [{"age": {"order": "desc"}},{"_score": {"order": "desc"}}]
}

响应结果

{"took": 3,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 2,"relation": "eq"},"max_score": null,"hits": [{"_index": "test1","_type": "_doc","_id": "1005","_score": 0.87546873,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 40},"sort": [40,0.87546873]},{"_index": "test1","_type": "_doc","_id": "1001","_score": 0.87546873,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 30},"sort": [30,0.87546873]}]}
}

（11）高亮查询

在使用 match 查询的同时，加上一个 highlight 属性，可以设置高亮显示（高亮显示字段需要是索引字段）

标签	说明
pre_tags	前置标签
post_tags	后置标签
fields	需要高亮的字段
title	这里声明 title 字段需要高亮，后面可以为这个字段设置特有配置，也可以空

{"query": {"match": {"name": "zhangsan"}},"highlight": {"pre_tags": "<font color='red'>","post_tags": "</font>","fields": {"name": {}}}
}

响应结果如下

{"took": 2,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 2,"relation": "eq"},"max_score": 0.87546873,"hits": [{"_index": "test1","_type": "_doc","_id": "1001","_score": 0.87546873,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 30},"highlight": {"name": ["<font color='red'>zhangsan</font>"]}},{"_index": "test1","_type": "_doc","_id": "1005","_score": 0.87546873,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 40},"highlight": {"name": ["<font color='red'>zhangsan</font>"]}}]}
}

（12）分页查询

当返回的文档数据量较多时，可以使用分页查询

from：当前页的起始索引，默认从 0 开始。
size：每页显示多少条

当 from 值较大时，性能会显著下降，因为 Elasticsearch 需要处理大量数据来跳过前面的记录。

Elasticsearch 默认限制了 from + size的最大值为10,000（index.max_result_window），超过此限制会导致查询失败

（分页查询一般都会结合排序使用）

{"query": {"match_all": {}},"sort": [{"age": {"order": "desc"}}],"from": 1,"size": 2
} 

响应结果如下

{"took": 2,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 5,"relation": "eq"},"max_score": null,"hits": [{"_index": "test1","_type": "_doc","_id": "1003","_score": null,"_source": {"name": "wangwu","nickname": "wangwu","sex": "女","age": 40},"sort": [40]},{"_index": "test1","_type": "_doc","_id": "1005","_score": null,"_source": {"name": "zhangsan","nickname": "zhangsan","sex": "男","age": 40},"sort": [40]}]}
}

（13）聚合查询

ES也支持最大最小平均等的聚合，关键字分别为（max、min、avg、sum）

求平均年龄（这里的avg_age也可以是其他，仅代表一个结果返回值接收属性的叫法）

{"aggs": {"avg_age": {"avg": {"field": "age"}}},"size": 0
} 

响应结果

{"took": 20,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 5,"relation": "eq"},"max_score": null,"hits": []},"aggregations": {"avg_age": {"value": 36}}
}

去重计数

{"aggs": {"distinct_age": {"cardinality": {"field": "age"}}},"size": 0
}

响应结果

{"took": 112,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 5,"relation": "eq"},"max_score": null,"hits": []},"aggregations": {"distinct_age": {"value": 4}}
}

stats 聚合，对某个字段一次性返回 count，max，min，avg 和 sum 五个指标

{"aggs": {"stats_age": {"stats": {"field": "age"}}},"size": 0
} 

响应结果

{"took": 3,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 5,"relation": "eq"},"max_score": null,"hits": []},"aggregations": {"stats_age": {"count": 5,"min": 20,"max": 50,"avg": 36,"sum": 180}}
}

（14）桶聚合查询（分组查询）

按年龄分组统计

{"aggs": {"age_groupby": {"terms": {"field": "age"}}},"size": 0
}

响应结果

{"took": 8,"timed_out": false,"_shards": {"total": 1,"successful": 1,"skipped": 0,"failed": 0},"hits": {"total": {"value": 5,"relation": "eq"},"max_score": null,"hits": []},"aggregations": {"age_groupby": {"doc_count_error_upper_bound": 0,"sum_other_doc_count": 0,"buckets": [{"key": 40,"doc_count": 2},{"key": 20,"doc_count": 1},{"key": 30,"doc_count": 1},{"key": 50,"doc_count": 1}]}}
}