文章目录
- 搜索和查询
- 查询的上下文
- Query DSL(Domain Specific Language)
- 1 查询上下文
- 2 相关度评分:_score
- 3 元数据:_source
- 4 Query String
- 查询所有:
- 带参数:
- 分页:
- 精准匹配 exact value
- _all搜索 相当于在所有有索引的字段中检索
- 5 全文检索-Fulltext query
- match:匹配包含某个term的子句
- match_all:匹配所有结果的子句
- multi_match:多字段条件
- match_phrase:短语查询,
- 6 精准查询-Term query
- term:匹配和搜索词项完全相等的结果
- terms:匹配和搜索词项列表中任意项匹配的结果
- range:范围查找
- 7 过滤器-Filter
- 8 组合查询-Bool query
- 数据代码
搜索和查询
查询的上下文
{
#请求消耗的时间 ms
"took" : 722,
#是否超时
"timed_out" : false,
#当前请求的分片
"_shards" : {
#分片的总数
"total" : 1,
#成功的个数
"successful" : 1,
#跳过的个数
"skipped" : 0,
#失败的个数
"failed" : 0
},
#真正返回的结果
"hits" : {
#结果的总数
"total" : {
#查询到的结果个数,不是返回显示的个数
"value" : 2,
#查询关系
"relation" : "eq"
},
#当前最大的评分
"max_score" : 1.0,
#具体的结果
"hits" : [
{
#索引
"_index" : "product",
#类型
"_type" : "_doc",
#id
"_id" : "1",
#相关度评分
"_score" : 1.0,
#具体的结果详情,元数据
"_source" : {
"name" : "xiami phone",
"desc" : "shouji zhong de jianjiji",
"price" : 4999,
"tags" : [
"xingjiabi",
"fashao",
"buka"
]
}
},
{
"_index" : "product",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"name" : "xiami nfc phone",
"desc" : "zhichi quangongneng nfc,shouji zhong de jianjiji",
"price" : 49995,
"tags" : [
"xingjiabi",
"fashao",
"gongjiaoka"
]
}
}
]
}
}
Query DSL(Domain Specific Language)
1 查询上下文
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。
2 相关度评分:_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。
3 元数据:_source
- 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。
GET product2/_search
{
"_source": ["owner.name","owner.sex"],
"query": {
"match_all": {}
}
}
**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
PUT product
{
"mappings": {
"_source": {
"includes": [
"name",
"price"
],
"excludes": [
"desc",
"tags"
]
}
}
}
- 常用过滤规则
- “_source”: “false”,
- “_source”: “obj.*”,
- “_source”: [ “obj1.*”, “obj2.*” ],
- “_source”: {
“includes”: [ “obj1.*”, “obj2.*” ],
“excludes”: [ “*.description” ]
}
GET product2/_search
{
"_source": {
"includes": [
"owner.*",
"name"
],
"excludes": [
"name",
"desc",
"price"
]
},
"query": {
"match_all": {}
}
4 Query String
查询所有:
GET /product/_search
带参数:
GET /product/_search?q=name:xiaomi
分页:
GET /product/_search?from=0&size=2&sort=price:asc
精准匹配 exact value
GET /product/_search?q=date:2021-06-01
_all搜索 相当于在所有有索引的字段中检索
GET /product/_search?q=2021-06-01
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"
}
}
5 全文检索-Fulltext query
GET index/_search
{
"query": {
***
}
}
match:匹配包含某个term的子句
GET product/_search
{
"query": {
"match": {
"name": "xiaomi nfc phone"
}
}
}
match_all:匹配所有结果的子句
GET product/_search
{
"query": {
"match_all": {}
}
}
multi_match:多字段条件
GET product/_search
{
"query": {
"multi_match": {
"query": "phone huangmenji",
"fields": ["name","desc"]
}
}
}
match_phrase:短语查询,
{
"query": {
"match_phrase": {
"name": "xiaomi nfc"
}
}
}
6 精准查询-Term query
term:匹配和搜索词项完全相等的结果
- term和match_phrase区别:
GET product/_search
{
"query": {
"match": {
"name": "xiaomi phone"
}
}
}
GET product/_search
{
"query": {
"term": {
"name": "xiaomi phone"
}
}
}
GET product/_search
{
"query": {
"match_phrase": {
"name": "xiaomi phone"
}
}
}
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
GET product/_search
{
"query": {
"term": {
"name": "xiaomi phone"
}
}
}
GET product/_search
{
"query": {
"term": {
"name.keyword": "xiaomi phone"
}
}
}
terms:匹配和搜索词项列表中任意项匹配的结果
GET product/_search
{
"query": {
"terms": {
"tags": [ "lowbee", "gongjiaoka" ],
"boost": 1.0
}
}
}
range:范围查找
GET /_search
{
"query": {
"range": {
"age": {
"gte": 10,
"lte": 20,
"boost": 2.0
}
}
}
}
GET product/_search
{
"query": {
"range": {
"date": {
"gte": "2021-04-15",
"lt": "2021-04-16"
}
}
}
}
7 过滤器-Filter
GET _search
{
"query": {
"constant_score": {
"filter": {
"term": {
"status": "active"
}
}
}
}
}
- filter:query和filter的主要区别在: filter是结果导向的而query是过程导向。query倾向于“当前文档和查询的语句的相关度”而filter倾向于“当前文档和查询的条件是不是相符”。即在查询过程中,query是要对查询的每个结果计算相关性得分的,而filter不会。另外filter有相应的缓存机制,可以提高查询效率。
GET product/_search
{
"query": {
"constant_score": {
"filter": {
"term": {
"name": "phone"
}
},
"boost": 1.2
}
}
}
GET product/_search
{
"query": {
"bool": {
"filter": {
"term": {
"name": "phone"
}
}
}
}
}
8 组合查询-Bool query
bool:可以组合多个查询条件,bool查询也是采用more_matches_is_better的机制,因此满足must和should子句的文档将会合并起来计算分值
- 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。
# bool query 组合查询
#must 计算相关度得分
#条件1:包含"xiaomi"或"phone"
#条件2:包含"shouji zhong"
GET product/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"name": "xiaomi phone"
}
},
{
"match_phrase": {
"desc": "shouji zhong"
}
}
]
}
}
}
- 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。
#filter 不计算相关度得分
GET product/_search
{
"query": {
"bool": {
"filter": [
{
"match": {
"name": "xiaomi phone"
}
},
{
"match_phrase": {
"desc": "shouji zhong"
}
}
]
}
}
}
- should:可能满足 or子句(查询)应出现在匹配的文档中。
#should
GET product/_search
{
"query": {
"bool": {
"should": [
{
"match_phrase": {
"name": "xiaomi nfc"
}
},
{
"range": {
"price": {
"lte": "500"
}
}
}
]
}
}
}
- 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。
#must not 不计算相关度得分
#条件1: 排除包含xiaomi的和包含nfc的(不能包含xiaomi和nfc中的任意一个)
#条件2: 排除价格大于等于500的
GET product/_search
{
"query": {
"bool": {
"must_not": [
{
"match": {
"name": "xiaomi nfc"
}
},
{
"range": {
"price": {
"gte": "500"
}
}
}
]
}
}
}
minimum_should_match:参数指定should返回的文档必须匹配的子句的数量或百分比。如果bool查询包含至少一个should子句,而没有must或 filter子句,则默认值为1。否则,默认值为0
#filter和must组合
GET product/_search
{
"_source": false,
"query": {
"bool": {
"filter": [
{
"range": {
"price": {
"lte": "1000"
}
}
}
],
"must": [
{
"match": {
"name": "xiaomi"
}
}
]
}
}
}
GET product/_search
{
"_source": false,
"query": {
"bool": {
"must": [
{
"match": {
"name": "xiaomi"
}
},
{
"range": {
"price": {
"lte": "1000"
}
}
}
]
}
}
}
#(must或者filter)和should组合
#条件1:价格小于10000
#条件2:name中包含"hongmi"或者"xiaomi nfc phone"
GET product/_search
{
"_source": false,
"query": {
"bool": {
"filter": [
{
"range": {
"price": {
"lte": "10000"
}
}
}
],
"should": [
{
"match_phrase": {
"name": "nfc phone"
}
},
{
"match": {
"name": "erji"
}
},
{
"bool": {
"must": [
{
"range": {
"price": {
"gte": 900,
"lte": 3000
}
}
}
]
}
}
],
"minimum_should_match": 2
}
}
}
数据代码
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" ]
}
PUT /product2/_doc/1
{
"owner":{
"name":"zhangsan",
"sex":"男",
"age":18
},
"name": "hongmi erji",
"desc": "erji zhong de kendeji",
"price": 399,
"tags": [
"lowbee",
"xuhangduan",
"zhiliangx"
]
}
PUT product2
{
"mappings": {
"_source": {
"includes": [
"name",
"price"
],
"excludes": [
"desc",
"tags"
]
}
}
}