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Elasticsearch7.x DSL语法之查询

热度：12   发布时间：2023-12-03 19:30:56.0

程序员小强总结的 ElasticSearch专题超全总结篇在这里:传送门
结合官网资料，做了更详细的实际使用总结。
从单机版安装到集群高可用生产环境搭建、基本概念(索引,分片,节点,倒排索引…)、DSL语法实践、分词器(内置+中文)、SpringBoot整合实战、仿京东商品搜索实战实现。

1.前言

条件语句

  • match_all 查所有
  • match 匹配查询
  • bool联合查询
  • term 词条精确查询
  • range 范围查询

主要约束条件参数

  • must 多条件时必须都满足-相当于MySQL条件中的 AND
  • must_not 必须不匹配这些条件才可以
  • should 相当于MySQL条件中的 OR
  • filter 过滤条件-必须匹配

初始化测试数据

复杂查询之前，使用批量新增的方式，先初始化一些数据

  • 索引(index)：student_info

字段属性信息

  • student_no(学号)，name(名字),profession(专业)，
  • sex(性别1-男；2-女)，age(年龄),socre(考试分),birthday(生日),desc(备注)
# 使用批量新增
POST _bulk
{
    "index":{
    "_index":"student_info","_id":11001}}
{
    "id":11001,"student_no":"202011001","name":"张三","english_name":"zhangsan","profession":"计算机科学与技术","sex":1,"age":20,"score":601,"birthday":"2000-09-30","desc":"备注"}
{
    "index":{
    "_index":"student_info","_id":11002}}
{
    "id":11002,"student_no":"202011002","name":"李四","english_name":"lisi","profession":"计算机科学与技术","sex":1,"age":21,"score":591,"birthday":"1999-06-15","desc":"我是李四的备注"}
{
    "index":{
    "_index":"student_info","_id":11003}}
{
    "id":11003,"student_no":"202011003","name":"王五","english_name":"wangwu","profession":"计算机科学与技术","sex":1,"age":22,"score":599,"birthday":"1998-07-20","desc":"我是王五的备注"}
{
    "index":{
    "_index":"student_info","_id":11004}}
{
    "id":11004,"student_no":"202011004","name":"赵六","english_name":"zhaoliu","profession":"软件工程","sex":1,"age":19,"score":620,"birthday":"2001-09-20","desc":"我是赵六的备注"}
{
    "index":{
    "_index":"student_info","_id":11005}}
{
    "id":11005,"student_no":"202011005","name":"小七七","english_name":"xiaoqiqi","profession":"软件工程","sex":1,"age":20,"score":598,"birthday":"2000-09-11","desc":"小七七"}
{
    "index":{
    "_index":"student_info","_id":11006}}
{
    "id":11006,"student_no":"202011006","name":"小小薇","english_name":"xiaoxiaowei","profession":"酒店管理","sex":2,"age":20,"score":621,"birthday":"2000-08-10","desc":"小小薇"}
{
    "index":{
    "_index":"student_info","_id":11007}}
{
    "id":11007,"student_no":"202011007","name":"小芳芳","english_name":"xiaofangfang","profession":"酒店管理","sex":2,"age":19,"score":620,"birthday":"2001-09-10","desc":"小芳芳"}
{
    "index":{
    "_index":"student_info","_id":11008}}
{
    "id":11008,"student_no":"202011008","name":"小小芳","english_name":"xiaoxiaofang","profession":"酒店管理","sex":2,"age":19,"score":620,"birthday":"2001-10-10","desc":"小小芳"}

2.简单查询

2.1查询所有结果(match_all)

GET /my_index1/_search
{
    "query":{
    "match_all":{
    }}
}

2.2根据条件查询(query)

GET /my_index1/_search
{
    "query":{
    "match":{
    "name":"张三"}},"sort":[{
    "age":"desc"}]
}

2.3排序(sort)

添加 sort条件

GET /my_index1/_search
{
    "query":{
    "match":{
    "name":"张三"}},"sort":[{
    "age":"desc"}]
}

2.4指定查询返回结果字段(_source)

注：仅返回_source指定的字段

GET /my_index1/_search
{
    "query":{
    "match_all":{
    }},"_source":["name","age"]
}

3.批量查询

3.1多ID查询(query)

GET /my_index3/_search
{
    "query": {
    "ids": {
    "values":[ 1001, 1002, 1003 ]}}
}

3.2单索引批量查(mget)

# 批量查询my_index3索引数据
POST /my_index3/_mget
{
    "ids": ["1001","1002","1003"]
}

在这里插入图片描述

3.3跨索引批量查(mget)

# 同时查询my_index1与my_index3两个所以下的数据
GET /_mget
{
    "docs": [{
    "_index": "my_index1","_id": "1001"},{
    "_index": "my_index3","_id": "1002"},{
    "index":"my_index1"}{
    "query":{
    "match_all":{
    }},"from":0,"size":10}]
}

3.4跨索引批量查(msearch)

GET /_msearch
{
    "index":"my_index1"}
{
    "query":{
    "match_all":{
    }},"from":0,"size":10}
{
    "index":"my_index3"}
{
    "query":{
    "match_all":{
    }}}

3.匹配查询(match)

match原理是先分析文档，通过分词器进行解析，然后再去文档中查询。

3.1.关键字分词查询

先对match里面的字段值进行分词，然后进行查询

  • “profession”: “计算机技术” ：分词结果为 “计算机”、 “技术”，查询profession包含 "计算机"和 "技术"的记录
#关键字分词查询
GET /student_info/_search
{
    "query": {
    "match": {
    "profession": "计算机技术"}}
}

#关键字分词查询-多个-逗号分隔
GET /student_info/_search
{
    "query": {
    "match": {
    "profession": "计算机技术,酒店"}}
}

在这里插入图片描述

3.2.关联查询

“profession”: “计算机技术” ：分词结果为 “计算机”、 “技术”，查询条件"operator": “and”，必须满足全部分词结果。

#关联查询 "operator": "and"
GET /student_info/_search
{
    "query": {
    "match": {
    "profession": {
    "query": "计算机技术","operator": "and"}}}
}

“profession”: “计算机技术” ：分词结果为 “计算机”、 “技术”，查询条件"operator": “or”，任意满足其一。

#关联查询 "operator": "or"
GET /student_info/_search
{
    "query": {
    "match": {
    "profession": {
    "query": "计算机技术","operator": "or"}}}
}

3.3.多字段查询

检索内容"我计算机技术" , 会拆词为“我”，“计算机”，“技术”
匹配字段profession或desc字段中包含拆出来的词语的结果

#多字段查询
GET /student_info/_search
{
    "query": {
    "multi_match": {
    "query": "我计算机技术","fields": [ "profession", "desc" ]}}
}

3.4.短语查询

match_phrase短语搜索，要求所有的分词必须同时出现在文档中，同时位置必须紧邻一致。

#短语查询
GET /student_info/_search
{
    "query": {
    "match_phrase": {
    "profession": "计算机科"}}
}

3.5.高亮搜索(highlight)

  • highlight 高亮查找
  • pre_tags 标签前缀
  • post_tags 标签后缀
  • fields 规定的字段，支持多个

注意：如果不声明前缀和后缀，那边默认使用 <em></em>

GET /student_info/_search
{
    "query":{
    "match":{
    "name":"张三"}},"highlight": {
    "pre_tags":"<p class = \"text_high_light\">","post_tags":"</p>","fields": {
    "name": {
    }}}
}

在这里插入图片描述

3.6.前缀匹配

#前缀匹配查询
GET /student_info/_search
{
    "query": {
    "match_phrase_prefix": {
    "name": "小小"}}
}

在这里插入图片描述

4.分页查询专题

详见：传送门

5.聚合查询专题

详见：传送门

6.模糊查询(fuzzy)

#模糊查询
GET /student_info/_search
{
    "query": {
    "fuzzy": {
    "name": "张"}}
}

7.精确查询(trem)

term是关键词查询，参数类型type 一般都是是keyword , 精确查询，对查询的值不分词,直接进倒排索引去匹配。

  • term 精确查找（单个）
  • terms 精确查找（多个）
  • 在这里插入图片描述

由于新增测试索引没有指定mapping >> “name”: “张三” 使用的是 text类型匹配

#关键词查询
GET /student_info/_search
{
    "query": {
    "term": {
    "name.keyword": "张三"}}
}

terms表示多条件并列，用大括号 [ ] 涵盖所查内容，类似于MySql中in方法

# 多条件查询
GET /student_info/_search
{
    "query": {
    "terms": {
    "age": [19,20,21,22]}}
}

8.范围查询

8.1range

大于-gt，小于-lt，大于等于-gte，小于等于-lte

数字范围

查询年龄 19 ~ 21

#范围查询
GET /student_info/_search
{
    "query": {
    "range": {
    "age":{
    "gte": 19,"lte": 21}}}
}

时间范围

#范围查询
GET /student_info/_search
{
    "query": {
    "range": {
    "birthday":{
    "gte": "2001-06-15","lte": "2001-09-20"}}}
}

8.2from … to

包含边界

#范围查询
GET /student_info/_search
{
    "query": {
    "range": {
    "age":{
    "from": 19,"to": 21}}}
}

范围查询不包含边界

#范围查询不包含边界
GET /student_info/_search
{
    "query": {
    "range": {
    "age": {
    "from": 19,"to": 21,"include_lower": false,"include_upper": false}}}
}

9.通配符查询(wildcard)

注：?用来匹配任意字符，*用来匹配零个或者多个字符，主要用于-英文检索

#通配符查询（*用来匹配零个或者多个字符）
GET /student_info/_search
{
    "query": {
    "wildcard": {
    "english_name": "小*"}}
}

#通配符查询（?用来匹配任意字符）
GET /student_info/_search
{
    "query": {
    "wildcard": {
    "english_name": "li?i"}}
}

10.must查询

must的多条件都必须满足

  • must相当于MySQL条件中的 AND
GET /student_info/_search
{
    "query": {
    "bool": {
    "must": [{
    "match": {
    "name": "小小"}},{
    "range": {
    "age": {
    "gt": 19,"lte": 22}}}]}}
}

11.should查询

should的条件，至少满足一个就可以

  • should相当于MySQL条件中的 OR
GET /student_info/_search
{
    "query": {
    "bool": {
    "must": [{
    "match": {
    "name": "小小"}},{
    "range": {
    "age": {
    "gt": 19,"lte": 22}}}]}}
}

12.filter过滤查询

#过滤查询
GET /student_info/_search
{
    "query": {
    "bool": {
    "should": [{
    "match": {
    "name": "小小"}}],"filter": {
    "range": {
    "age": {
    "gt": 21,"lte": 22}}}}}
}

附录

ES7.3版官方聚合查询API

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