Elastic Search — Query DSL

文章目录

Query DSL (Domain Specific Language)
- 一. 前置数据
- 二. query
- - 1. 查询所有
  - 2.带参数查询
  - 3.分页
  - 4.精准匹配
  - 5._all搜索（所有有索引的字段中检索）
- 三. _score
- 四. _source
- 五. match 全文检索-Fulltext query
- 六. Term
- 七. Range
- 八. Filter
- 九. Boolean查询

Query DSL (Domain Specific Language)

一. 前置数据

DELETE product
PUT /product/_doc/1
{"name" : "xiaomi phone","desc" :  "shouji zhong de zhandouji","date": "2021-06-01","price" :  3999,"tags": [ "xingjiabi", "fashao", "buka" ]
}
PUT /product/_doc/2
{"name" : "xiaomi nfc phone","desc" :  "zhichi quangongneng nfc,shouji zhong de jianjiji","date": "2021-06-02","price" :  4999,"tags": [ "xingjiabi", "fashao", "gongjiaoka" ]
}
PUT /product/_doc/3
{"name" : "nfc phone","desc" :  "shouji zhong de hongzhaji","date": "2021-06-03","price" :  2999,"tags": [ "xingjiabi", "fashao", "menjinka" ]
}
PUT /product/_doc/4
{"name" : "xiaomi erji","desc" :  "erji zhong de huangmenji","date": "2021-04-15","price" :  999,"tags": [ "low", "bufangshui", "yinzhicha" ]
}
PUT /product/_doc/5
{"name" : "hongmi erji","desc" :  "erji zhong de kendeji 2021-06-01","date": "2021-04-16","price" :  399,"tags": [ "lowbee", "xuhangduan", "zhiliangx" ]
}

二. query

使用query关键字进行检索，倾向于相关度搜索，故需要计算评分。搜索是Elasticsearch最关键和重要的部分。

1. 查询所有

GET /product/_search

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

2.带参数查询

 GET product/_search?q=partlist.name:adapterGET product/_search?q=name:xiaomi

3.分页

from:第几条开始

size:展示的数目大小

sort:排序

GET product/_search?from=0&size=5&sort=price:asc

4.精准匹配

 # 日期GET /product/_search?q=date:2021-06-01

5._all搜索（所有有索引的字段中检索）

DELETE product# 验证_all搜索
PUT product
{“mappings”: {“properties”: {“desc”: {“type”: “text”,“index”: false}}}
}# 先初始化数据
POST /product/_update/5
{“doc”: {“desc”: “erji zhong de kendeji 2021-06-01”}
}

三. _score

概念：相关度评分用于对搜索结果排序，评分越高则认为其结果和搜索的预期值相关度越高，即越符合搜索预期值。在7.x之前相关度评分默认使用TF/IDF算法计算而来，7.x之后默认为 BM25。在核心知识篇不必关心相关评分的具体原理，只需知晓其概念即可。

排序：相关度评分为搜索结果的排序依据，默认情况下评分越高，则结果越靠前。

四. _source

官方文档：https://www.elastic.co/guide/en/elasticsearch/reference/7.17/mapping-source-field.html

禁用_source：

好处：节省存储开销

坏处：

不支持update、update_by_query和reindex API。

不支持高亮。

不支持reindex、更改mapping分析器和版本升级。

通过查看索引时使用的原始文档来调试查询或聚合的功能。

将来有可能自动修复索引损坏。

总结：如果只是为了节省磁盘，可以压缩索引比禁用_source更好。

数据源过滤器：

Including：结果中返回哪些field

Excluding：结果中不要返回哪些field，不返回的field不代表不能通过该字段进行检索，因为元数据不存在不代表索引不存在

在mapping中定义过滤：支持通配符，但是这种方式不推荐，因为mapping不可变

常用过滤规则

“_source”: “false”,

“_source”: “obj.*”,

“_source”: [ “obj1.*”, “obj2.*” ],

“_source”: {
“includes”: [ “obj1.*”, “obj2.*” ],
“excludes”: [ “*.description” ]
}

# source 回显的include 和 exclue
DELETE product2
PUT product2
{"mappings": {"_source": {"includes": ["name","price"],"excludes": ["desc","tags"]}}
}PUT product2/_doc/1
{"owner": {"name": "zhangsan","sex": "男","age": 18},"name": "hongmi erji","desc": "erji zhong dekendeji","price": 399,"tags": ["lowbee","xuhangduan","zhiliangx"]
}GET product2/_search# source 返回指定
DELETE product2PUT product2
{"mappings": {"_source": ["owner.name", "owner.sex"],"query":{"match_all": {}}}
}# 不查询数据
GET product/_search
{"_source": false,"query": {"match_all": {}}
}

五. match 全文检索-Fulltext query

match_phrase

# multi_match 根据指定字段查询对应的分词
GET product/_search
{"query": {"multi_match": {"query": "phone huangmenji","fields": ["name", "desc"]}}
}
# match_all
GET product/_search
{"query": {"match_all": {}}
}
# math 分词查询
GET product/_search
{"query": {"match": {"name": "xiaomi phone"}}
}# math_phrase 段落匹配
GET product/_search
{"query": {"match_phrase": {"name": "nfc phone"}}
}

六. Term

官方文档：https://www.elastic.co/guide/en/elasticsearch/reference/7.17/query-dsl-term-query.html

# term 精确匹配
GET product/_search
{"query": {"term": {"name": "xiaomi phone"}}
}# term 和 match_phrase
GET product/_search
{"query": {"match_phrase": {"name": "xiaomi phone"}}
}# term
GET product/_search
{"query": {"term": {"name": {"value": "xiaomi phone" }}}
}# term和keyword区别
GET product/_mapping
GET product/_search
{"query": {"term": {"name": "xiaomi phone"}}
}GET product/_search
{"query": {"term": {"name.keyword": "xiaomi phone"}}
}# terms
GET product/_search
{"query": {"terms": {"tags": ["xingjiabi","buka"],"boost": 1.2}}
}

match和term区别

原理解析

term和match_phrase区别:

match_phrase 会将检索关键词分词, match_phrase的分词结果必须在被检索字段的分词中都包含，而且顺序必须相同，而且默认必须都是连续的

term搜索不会将搜索词分词

term和keyword区别

term是对于搜索词不分词,

keyword是字段类型,是对于source data中的字段值不分词

七. Range

官方文档：https://www.elastic.co/guide/en/elasticsearch/reference/7.17/query-dsl-range-query.html

# range
GET /product/_search?sort=price:desc
# [3999, 4999]
GET /_search
{"query": {"range": {"price": {"gte": 3999,"lte": 4999}}}
}# (3000, 4000)
GET /_search
{"query": {"range": {"price": {"gt": 3000,"lt": 4000}}}
}# [2021-06-01, 2021-06-02]
GET product/_search
{"query": {"range": {"date": {"gte": "2021-06-01","lte": "2021-06-02"}}}
}# [前一天, 今天]
GET product/_search
{"query": {"range": {"date": {"gte": "now-1d/d","lte": "now/d"}}}
}GET product/_search
{"query": {"range": {"date": {"time_zone": "+08:00", "gte": "2021-06-01","lte": "2021-06-02"}}}
}

八. Filter

官方文档：https://www.elastic.co/guide/en/elasticsearch/reference/7.17/query-filter-context.html

filter: 不需要计算相关度分数，不需要按照相关度分数进行排序，同时还有内置的自动cache最常使用的filter的数据，性能好

query：要计算相关度分数，按照分数进行排序，而且无法cache结果

GET product/_search
{"query": {"constant_score": {"filter": {"term": {"name": "phone"}},"boost": 1.2}}
}

九. Boolean查询

官方文档：https://www.elastic.co/guide/en/elasticsearch/reference/7.17/query-dsl-bool-query.html

bool查询是最常用的组合查询，根据子查询的规划，只有当满足其所有的子查询条件时，Elasitcsearch引擎回显结果

bool支持的子查询

must：必须满足子句（查询）必须出现在匹配的文档中，并将有助于得分。
filter：过滤器不计算相关度分数，cache☆子句（查询）必须出现在匹配的文档中。但是不像 must查询的分数将被忽略。Filter子句在filter上下文中执行，这意味着计分被忽略，并且子句被考虑用于缓存。
should：可能满足 or子句（查询）应出现在匹配的文档中。
must_not：必须不满足不计算相关度分数 not子句（查询）不得出现在匹配的文档中。子句在过滤器上下文中执行，这意味着计分被忽略，并且子句被视为用于缓存。由于忽略计分，0因此将返回所有文档的分数。