结尾|多种_ElasticSearch的使用

篇首语：本文由编程笔记#小编为大家整理，主要介绍了ElasticSearch的使用相关的知识，希望对你有一定的参考价值。

一、安装ElasticSearch

下载连接&＃xff1a;https://www.elastic.co/cn/elasticsearch/
之后解压文件&＃xff0c;通过命令cd到bin目录下,输入elasticsearch.bat&＃xff0c;启动服务

之后在浏览器中输入http://localhost:9200,当看到以下信息说明服务启动成功


"name" : "DESKTOP-1IK0UC3",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "fhhG4xtCT0mZ6ogsze66zA",
"version" :
"number" : "7.14.2",
"build_flavor" : "default",
"build_type" : "zip",
"build_hash" : "6bc13727ce758c0e943c3c21653b3da82f627f75",
"build_date" : "2021-09-15T10:18:09.722761972Z",
"build_snapshot" : false,
"lucene_version" : "8.9.0",
"minimum_wire_compatibility_version" : "6.8.0",
"minimum_index_compatibility_version" : "6.0.0-beta1"
,
"tagline" : "You Know, for Search"



需要注意的是elasticsearch是java编写的所以运行需要jdk的环境&＃xff0c;elasticsearch目录下有一个jdk的文件夹&＃xff0c;如果没有是需要自己配置jdk的环境。

二、Kibana

为了方便学习使用这里推荐使用Kibana&＃xff0c;在对应的官网上找到Kibana选项然后下载Kibana,Kibana与elasticsearch的版本要对应上。
同样的操作&＃xff0c;进入到bin文件夹内执行kibana.bat,一般Kibanna默认的端口号是5601
通过浏览器输入http://localhost:5601/&＃xff0c;会进入到一个图形界面选择菜单栏里的
Dev Tools

三、创建

Elasticsearch是一个基于Lucene的搜索服务器。它提供了一个分布式多用户能力的全文搜索引擎&＃xff0c;基于RESTful web接口。

//通过post方式直接创建数据
//创建索引为shopping的数据
POST /shopping/_doc

"title":"手机",
"name":"华为mate40",
"images":"http://www.xxx.com/xx.jpg",
"price":7999.00

//elasticsearch返回

"_index" : "shopping",
"_type" : "_doc",
"_id" : "AdU3aIABsHOWi0z2JXR6",//此id为elasticSearch生成的
"_version" : 1,
"result" : "created",
"_shards" :
"total" : 2,
"successful" : 1,
"failed" : 0
,
"_seq_no" : 10,
"_primary_term" : 2



不使用elasticsearch生成的id&＃xff0c;需要自行指定id

//里面的3就是指定的id
POST /shopping/_doc/3

"title":"数码产品",
"name":"金士顿32GU盘",
"images":"http://www.xxx.com/xx.jpg",
"price":45.00

//返回的数据

"_index" : "shopping",
"_type" : "_doc",
"_id" : "3",
"_version" : 1,
"result" : "created",
"_shards" :
"total" : 2,
"successful" : 1,
"failed" : 0
,
"_seq_no" : 11,
"_primary_term" : 2



当然指定了id也可以使用put方式过程类似

四、更新

1.覆盖更新&＃xff08;此方式不太推荐用于更新&＃xff09;
例如&＃xff1a;修改id为10的内容

PUT /shopping/_doc/10

"title":"生鲜水果",
"name":"苹果",
"images":"http://www.xxx.com/xx.jpg",
"price":10.00



2.局部更新&＃xff08;一般的更新只会更新某些字段的内容&＃xff0c;所以更新采用局部更新的方式比较合适&＃xff09;
例如更新id为10中name的内容

POST /shopping/_update/10

"doc":
"name":"芒果"




五、删除数据

例如删除id为2的数据

DELETE /shopping/_doc/2


六、查询

查讯采用GET的方式
1.查询索引的全部数据
通过GET方式索引名称&＃xff0c;_search

GET /shopping/_search


2.基于id查询&＃xff0c;例如查询id为3的数据

GET /shopping/_doc/3


3.条件查询
(1)、match方式

match查询属于全文查询&＃xff0c;在查询时&＃xff0c;ES会先分析查询字符串&＃xff0c;然后根据分词构建查询。

例如查询title为"红米"的数据

GET /shopping/_search

"query":
"match":
"title":"红米"





查询结果

"hits" : [

"_index" : "shopping",
"_type" : "_doc",
"_id" : "2",
"_score" : 2.3367887,
"_source" :
"title" : "红米手机",
"category" : "红米",
"images" : "http://www.xiaomi.com/xm.jpg",
"price" : 1999.0

,

"_index" : "shopping",
"_type" : "_doc",
"_id" : "10",
"_score" : 1.7820551,
"_source" :
"title" : "红米电视",
"name" : "红米max11",
"images" : "http://www.xxx.com/xx.jpg",
"price" : 3999.0

,

"_index" : "shopping",
"_type" : "_doc",
"_id" : "0kq9VYABBlS6ycwT5aie",
"_score" : 1.3246095,
"_source" :
"title" : "小米手机",
"category" : "小米",
"images" : "http://www.xiaomi.com/xm.jpg",
"price" : 3099.0

,

"_index" : "shopping",
"_type" : "_doc",
"_id" : "AdU3aIABsHOWi0z2JXR6",
"_score" : 0.70679253,
"_source" :
"title" : "手机",
"name" : "华为mate40",
"images" : "http://www.xxx.com/xx.jpg",
"price" : 7999.0


]


(2)、match_phrase方式

match_phrase在查询时也会先分析查询字符串&＃xff0c;然后对这些词项进行搜索&＃xff0c;不同的是match_phrase查询只会保留包含全部查询字符串的文档

GET /shopping/_search

"query":
"match_phrase":
"title":"红米手机"





查询结果

"hits" : [

"_index" : "shopping",
"_type" : "_doc",
"_id" : "00q_VYABBlS6ycwTPKiV",
"_score" : 2.3367884,
"_source" :
"title" : "红米手机",
"category" : "红米",
"images" : "http://www.xiaomi.com/xm.jpg",
"price" : 1999.0


]


(3)、bool方式

1.must等同于and
2.must_not等同于NOT
3.should等同于OR
4.filter过滤

must的应用
例如有两行数据&＃xff0c;查询价格为45&＃xff0c;标题是"数码产品"的数据

[

"title" : "护肤产品",
"name" : "洗面奶",
"images" : "http://www.xxx.com/xx.jpg",
"price" : 45.0
,

"title" : "数码产品",
"name" : "金士顿32GU盘",
"images" : "http://www.xxx.com/xx.jpg",
"price" : 45.0

]


查询语法

GET /shopping/_search

"query":
"bool":
"must":[

"term":
"price":45

,

"match_phrase":
"title":"数码产品"


]





查询结果

"hits" : [

"_index" : "shopping",
"_type" : "_doc",
"_id" : "3",
"_score" : 7.725004,
"_source" :
"title" : "数码产品",
"name" : "金士顿32GU盘",
"images" : "http://www.xxx.com/xx.jpg",
"price" : 45.0


]


另外两种:must_not、should语法是类似的就不再这里展开了

query context&＃xff1a;会对搜索进行相关性算分值&＃xff0c;
而filter context :不需要相关性算分&＃xff0c;能够利用缓存来获得更好的性能
例如

must查询会有一个&＃xff1a;“max_score” : 7.725004&＃xff0c;
而换成filter&＃xff1a;“max_score” : 0.0

filter
(4)、范围查询

range范围查询支持多种范围类型
1.数值类型
2.日期类型(timestamp)
3.ip地址类型

range的表达式
gt&＃xff1a;大于
lt&＃xff1a;小于
gte&＃xff1a;大于等于
lte&＃xff1a;小于等于
例如查询价格大于1999小于5000的商品

GET /shopping/_search

"query":
"range":
"price":
"gt": 1999,
"lt": 5000






range也是可以搭配bool,和filter一块使用&＃xff0c;来满足不同的查询需求。

七、分页

from&＃xff1a;是启始位置
size&＃xff1a;是需要查询的行数

例如全查询标题为"手机",价格大于1999小于5000的商品,并分页(由于我没有填充太多数据这里按每页一行)。

GET /shopping/_search

"query":
"bool":
"must": [

"match":
"title":"手机"


],
"filter":
"range":
"price":
"gt": 1999,
"lt": 5000





,
"from":0,
"size":1



输出结果


"took" : 0,
"timed_out" : false,
"_shards" :
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
,
"hits" :
"total" :
"value" : 2, //总数据量
"relation" : "eq"
,
"max_score" : 0.83024156,
"hits" : [

"_index" : "shopping",
"_type" : "_doc",
"_id" : "4",
"_score" : 0.83024156,
"_source" :
"title" : "vivo手机",
"category" : "vivo",
"images" : "http://www.xiaomi.com/xm.jpg",
"price" : 4999.0


]



八、查询需要的字段内容

_source&＃xff1a;指定字段返回

GET /shopping/_search

"query":
"match_phrase":
"title": "数码产品"

,
"_source":["name","price"]



输出结果

"hits" : [

"_index" : "shopping",
"_type" : "_doc",
"_id" : "3",
"_score" : 6.725004,
"_source" :
"price" : 45.0,
"name" : "金士顿32GU盘"


]


九、排序

sort&＃xff1a;排序
order&＃xff1a;asc正序&＃xff0c;desc逆序

按照分值逆序_score

GET /shopping/_search

"query":
"match":
"title": "手机"

,
"sort":
"_score":
"order":"desc"





输出结果

"hits" : [

"_index" : "shopping",
"_type" : "_doc",
"_id" : "AdU3aIABsHOWi0z2JXR6",
"_score" : 0.943285,
"_source" :
"title" : "手机",
"name" : "华为mate40",
"images" : "http://www.xxx.com/xx.jpg",
"price" : 7999.0

,

"_index" : "shopping",
"_type" : "_doc",
"_id" : "4",
"_score" : 0.83024156,
"_source" :
"title" : "vivo手机",
"category" : "vivo",
"images" : "http://www.xiaomi.com/xm.jpg",
"price" : 4999.0


]


十、搜索内容高亮

给搜索的字段加粗
通过highlight指定字段
pre_tags:开头
post_tags:结尾

GET /shopping/_search

"query":
"match":
"title": "手机"

,
"highlight":
"fields":
"title":
"pre_tags": [
""
],
"post_tags": [
""
]






输出结果

"hits" : [

"_index" : "shopping",
"_type" : "_doc",
"_id" : "AdU3aIABsHOWi0z2JXR6",
"_score" : 0.943285,
"_source" :
"title" : "手机",
"name" : "华为mate40",
"images" : "http://www.xxx.com/xx.jpg",
"price" : 7999.0
,
"highlight" :
"title" : [
"手机"
]

,

"_index" : "shopping",
"_type" : "_doc",
"_id" : "4",
"_score" : 0.83024156,
"_source" :
"title" : "vivo手机",
"category" : "vivo",
"images" : "http://www.xiaomi.com/xm.jpg",
"price" : 4999.0
,
"highlight" :
"title" : [
"vivo手机"
]


]


扩展&＃xff1a;对于全文搜索可能还需要加入IK分词器插件。