目录
一、Elasticsearch之排序查询
1. 准备数据
PUT test1/doc/1
{
"name":"顾老二",
"age":30,
"from": "gu",
"desc": "皮肤黑、武器长、性格直",
"tags": ["黑", "长", "直"]
}
PUT test1/doc/2
{
"name":"大娘子",
"age":18,
"from":"sheng",
"desc":"肤白貌美，娇憨可爱",
"tags":["白", "富","美"]
}
PUT test1/doc/3
{
"name":"龙套偏房",
"age":22,
"from":"gu",
"desc":"mmp，没怎么看，不知道怎么形容",
"tags":["造数据", "真","难"]
}
PUT test1/doc/4
{
"name":"石头",
"age":29,
"from":"gu",
"desc":"粗中有细，狐假虎威",
"tags":["粗", "大","猛"]
}
PUT test1/doc/5
{
"name":"魏行首",
"age":25,
"from":"广云台",
"desc":"仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
"tags":["闭月","羞花"]
}
2. 排序查询：sort
2.1 降序：desc
- 想到排序，出现在脑海中的无非就是升（正）序和降（倒）序。比如我们查询顾府都有哪些人，并根据age字段按照降序，并且，我只想看
nmae和age字段：
GET test1/doc/_search
{
"query": {
"match": {
"from": "gu"
}
},
"sort": [
{
"age": {
"order": "desc"
}
}
]
}
-
上例，在条件查询的基础上，我们又通过
sort来做排序，根据age字段排序，是降序呢还是升序，由order字段控制，desc是降序。 -
结果如下：
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : null,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : null,
"_source" : {
"name" : "顾老二",
"age" : 30,
"from" : "gu",
"desc" : "皮肤黑、武器长、性格直",
"tags" : [
"黑",
"长",
"直"
]
},
"sort" : [
30
]
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "4",
"_score" : null,
"_source" : {
"name" : "石头",
"age" : 29,
"from" : "gu",
"desc" : "粗中有细，狐假虎威",
"tags" : [
"粗",
"大",
"猛"
]
},
"sort" : [
29
]
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : null,
"_source" : {
"name" : "龙套偏房",
"age" : 22,
"from" : "gu",
"desc" : "mmp，没怎么看，不知道怎么形容",
"tags" : [
"造数据",
"真",
"难"
]
},
"sort" : [
22
]
}
]
}
}
- 上例中，结果是以降序排列方式返回的。
2.2 升序：asc
- 那么想要升序怎么搞呢？
GET test1/doc/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"age": {
"order": "asc"
}
}
]
}
-
上例，想要以升序的方式排列，只需要将
order值换为asc就可以了。 -
结果如下：
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 5,
"max_score" : null,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "2",
"_score" : null,
"_source" : {
"name" : "大娘子",
"age" : 18,
"from" : "sheng",
"desc" : "肤白貌美，娇憨可爱",
"tags" : [
"白",
"富",
"美"
]
},
"sort" : [
18
]
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : null,
"_source" : {
"name" : "龙套偏房",
"age" : 22,
"from" : "gu",
"desc" : "mmp，没怎么看，不知道怎么形容",
"tags" : [
"造数据",
"真",
"难"
]
},
"sort" : [
22
]
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "5",
"_score" : null,
"_source" : {
"name" : "魏行首",
"age" : 25,
"from" : "广云台",
"desc" : "仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
"tags" : [
"闭月",
"羞花"
]
},
"sort" : [
25
]
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "4",
"_score" : null,
"_source" : {
"name" : "石头",
"age" : 29,
"from" : "gu",
"desc" : "粗中有细，狐假虎威",
"tags" : [
"粗",
"大",
"猛"
]
},
"sort" : [
29
]
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : null,
"_source" : {
"name" : "顾老二",
"age" : 30,
"from" : "gu",
"desc" : "皮肤黑、武器长、性格直",
"tags" : [
"黑",
"长",
"直"
]
},
"sort" : [
30
]
}
]
}
}
- 上例，可以看到结果是以
age从小到大的顺序返回结果。
3. 不是什么数据类型都能排序
- 那么，你可能会问，除了
age，能不能以别的属性作为排序条件啊？来试试：
GET test1/chengyuan/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"name": {
"order": "asc"
}
}
]
}
- 上例，我们以
name属性来排序，来看结果：
{
"error": {
"root_cause": [
{
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [name] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead."
}
],
"type": "search_phase_execution_exception",
"reason": "all shards failed",
"phase": "query",
"grouped": true,
"failed_shards": [
{
"shard": 0,
"index": "test1",
"node": "wrtr435jSgi7_naKq2Y_zQ",
"reason": {
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [name] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead."
}
}
],
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [name] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead.",
"caused_by": {
"type": "illegal_argument_exception",
"reason": "Fielddata is disabled on text fields by default. Set fielddata=true on [name] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead."
}
}
},
"status": 400
}
-
结果跟我们想象的不一样，报错了！
-
注意：在排序的过程中，只能使用可排序的属性进行排序，其他的都不行！那么可以排序的属性有哪些呢？
-
数字
-
日期
-
二、Elasticsearch之分页查询
1. 准备数据
PUT test1/doc/1
{
"name":"顾老二",
"age":30,
"from": "gu",
"desc": "皮肤黑、武器长、性格直",
"tags": ["黑", "长", "直"]
}
PUT test1/doc/2
{
"name":"大娘子",
"age":18,
"from":"sheng",
"desc":"肤白貌美，娇憨可爱",
"tags":["白", "富","美"]
}
PUT test1/doc/3
{
"name":"龙套偏房",
"age":22,
"from":"gu",
"desc":"mmp，没怎么看，不知道怎么形容",
"tags":["造数据", "真","难"]
}
PUT test1/doc/4
{
"name":"石头",
"age":29,
"from":"gu",
"desc":"粗中有细，狐假虎威",
"tags":["粗", "大","猛"]
}
PUT test1/doc/5
{
"name":"魏行首",
"age":25,
"from":"广云台",
"desc":"仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
"tags":["闭月","羞花"]
}
2. 分页查询：from/size
- 我们来看看elasticsearch是怎么将结果分页的：
GET test1/doc/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"age": {
"order": "desc"
}
}
],
"from": 2,
"size": 1
}
-
上例，首先以
age降序排序，查询所有。并且在查询的时候，添加两个属性from和size来控制查询结果集hits中的数据条数（只对hits内的结果条数有影响，后面要介绍的聚合函数的结果不在size和from的控制内）。-
from参数定义了需要跳过的hits数，默认为0
-
size参数定义了需要返回的hits数目的最大值
-
-
如上例的结果：
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 5,
"max_score" : null,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "5",
"_score" : null,
"_source" : {
"name" : "魏行首",
"age" : 25,
"from" : "广云台",
"desc" : "仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
"tags" : [
"闭月",
"羞花"
]
},
"sort" : [
25
]
}
]
}
}
-
上例中，在返回的结果集中，从第2条开始，返回1条数据。
-
那如果想要从第2条开始，返回2条结果怎么做呢？
GET test1/doc/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"age": {
"order": "desc"
}
}
],
"from": 2,
"size": 2
}
-
上例中，我们指定
from为2，意为从第2条开始返回，返回多少呢？size意为2条。 -
还可以这样：
GET test1/doc/_search
{
"query": {
"match_all": {}
},
"sort": [
{
"age": {
"order": "desc"
}
}
],
"from": 4,
"size": 2
}
-
上例中，从第4条开始返回2条数据。
-
结果如下：
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 5,
"max_score" : null,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "2",
"_score" : null,
"_source" : {
"name" : "大娘子",
"age" : 18,
"from" : "sheng",
"desc" : "肤白貌美，娇憨可爱",
"tags" : [
"白",
"富",
"美"
]
},
"sort" : [
18
]
}
]
}
}
-
上例中仅有一条数据，那是为啥呢？因为我们现在只有5条数据，从第4条开始查询，就只有1条符合条件，所以，就返回了1条数据。
-
到这里，我们也可以看到，我们的查询条件越来越多，开始仅是简单查询，慢慢增加条件查询，增加排序，对返回结果进行限制。所以，我们可以说：对于
elasticsearch来说，所有的条件都是可插拔的，彼此之间用,分割。比如说，我们在查询中，仅对返回结果进行限制：
GET test1/doc/_search
{
"query": {
"match_all": {}
},
"from": 4,
"size": 2
}
- 上例中，在所有的返回结果中，结果从4开始返回2条数据。
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 5,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 1.0,
"_source" : {
"name" : "龙套偏房",
"age" : 22,
"from" : "gu",
"desc" : "mmp，没怎么看，不知道怎么形容",
"tags" : [
"造数据",
"真",
"难"
]
}
}
]
}
}
- 但我们只有1条符合条件的数据。
三、Elasticsearch之布尔查询
1. 前言
-
布尔查询是最常用的组合查询，用到了
bool关键字。根据其内的子查询的规则，只有当文档满足所有子查询条件时，elasticsearch引擎才将结果返回。布尔查询支持的子查询条件共4种：-
must（and）
-
should（or）
-
must_not（not）
-
filter
-
-
下面我们来看看每个子查询条件都是怎么玩的。
2. 准备数据
PUT test1/doc/1
{
"name":"顾老二",
"age":30,
"from": "gu",
"desc": "皮肤黑、武器长、性格直",
"tags": ["黑", "长", "直"]
}
PUT test1/doc/2
{
"name":"大娘子",
"age":18,
"from":"sheng",
"desc":"肤白貌美，娇憨可爱",
"tags":["白", "富","美"]
}
PUT test1/doc/3
{
"name":"龙套偏房",
"age":22,
"from":"gu",
"desc":"mmp，没怎么看，不知道怎么形容",
"tags":["造数据", "真","难"]
}
PUT test1/doc/4
{
"name":"石头",
"age":29,
"from":"gu",
"desc":"粗中有细，狐假虎威",
"tags":["粗", "大","猛"]
}
PUT test1/doc/5
{
"name":"魏行首",
"age":25,
"from":"广云台",
"desc":"仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
"tags":["闭月","羞花"]
}
3. must
- 现在，我们用布尔查询所有
from属性为gu的数据：
GET test1/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"from": "gu"
}
}
]
}
}
}
-
上例中，我们通过在
bool属性（字段）内使用must来作为查询条件，那么条件是什么呢？条件同样被match包围，就是from为gu的所有数据。 -
这里需要注意的是
must字段对应的是个列表，也就是说可以有多个并列的查询条件，一个文档满足各个子条件后才最终返回。 -
结果如下：
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : 0.6931472,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "4",
"_score" : 0.6931472,
"_source" : {
"name" : "石头",
"age" : 29,
"from" : "gu",
"desc" : "粗中有细，狐假虎威",
"tags" : [
"粗",
"大",
"猛"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "顾老二",
"age" : 30,
"from" : "gu",
"desc" : "皮肤黑、武器长、性格直",
"tags" : [
"黑",
"长",
"直"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 0.2876821,
"_source" : {
"name" : "龙套偏房",
"age" : 22,
"from" : "gu",
"desc" : "mmp，没怎么看，不知道怎么形容",
"tags" : [
"造数据",
"真",
"难"
]
}
}
]
}
}
-
上例中，可以看到，所有
from属性为gu的数据查询出来了。 -
那么，我们想要查询
from为gu，并且age为30的数据怎么搞呢？
GET test1/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"from": "gu"
}
},
{
"match": {
"age": 30
}
}
]
}
}
}
-
上例中，在
must列表中，在增加一个age为30的条件。 -
结果如下：
{
"took" : 8,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 1.287682,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 1.287682,
"_source" : {
"name" : "顾老二",
"age" : 30,
"from" : "gu",
"desc" : "皮肤黑、武器长、性格直",
"tags" : [
"黑",
"长",
"直"
]
}
}
]
}
}
-
上例，符合条件的数据被成功查询出来了。
-
注意：现在你可能慢慢发现一个现象，所有属性值为列表的，都可以实现多个条件并列存在
4. should
- 那么，如果想查询只要是
from为gu或者tags为闭月的数据怎么搞？
GET test1/doc/_search
{
"query": {
"bool": {
"should": [
{
"match": {
"from": "gu"
}
},
{
"match": {
"tags": "闭月"
}
}
]
}
}
}
-
上例中，或关系的不能用
must的了，而是要用should，只要符合其中一个条件就返回。 -
结果如下：
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 4,
"max_score" : 0.6931472,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "4",
"_score" : 0.6931472,
"_source" : {
"name" : "石头",
"age" : 29,
"from" : "gu",
"desc" : "粗中有细，狐假虎威",
"tags" : [
"粗",
"大",
"猛"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "5",
"_score" : 0.5753642,
"_source" : {
"name" : "魏行首",
"age" : 25,
"from" : "广云台",
"desc" : "仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
"tags" : [
"闭月",
"羞花"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "顾老二",
"age" : 30,
"from" : "gu",
"desc" : "皮肤黑、武器长、性格直",
"tags" : [
"黑",
"长",
"直"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 0.2876821,
"_source" : {
"name" : "龙套偏房",
"age" : 22,
"from" : "gu",
"desc" : "mmp，没怎么看，不知道怎么形容",
"tags" : [
"造数据",
"真",
"难"
]
}
}
]
}
}
- 返回了所有符合条件的结果。
5. must_not
- 那么，如果我想要查询
from既不是gu并且tags也不是可爱，还有age不是18的数据怎么办？
GET test1/doc/_search
{
"query": {
"bool": {
"must_not": [
{
"match": {
"from": "gu"
}
},
{
"match": {
"tags": "可爱"
}
},
{
"match": {
"age": 18
}
}
]
}
}
}
- 上例中，
must和should都不能使用，而是使用must_not，又在内增加了一个age为18的条件。
结果如下：
{
"took" : 9,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 1.0,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "5",
"_score" : 1.0,
"_source" : {
"name" : "魏行首",
"age" : 25,
"from" : "广云台",
"desc" : "仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
"tags" : [
"闭月",
"羞花"
]
}
}
]
}
}
- 上例中，只有魏行首这一条数据，因为只有魏行首既不是顾家的人，标签没有可爱那一项，年龄也不等于18
- 这里有点需要补充，条件中
age对应的18你写成整形还是字符串都没啥区别……
6. filter
- 那么，如果要查询
from为gu，age大于25的数据怎么查？ - 范围查询用到了关键字
range，其内部可以跟多个条件
GET test1/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"from": "gu"
}
}
],
"filter": {
"range": {
"age": {
"gt": 25
}
}
}
}
}
}
-
这里就用到了
filter条件过滤查询，过滤条件的范围用range表示，gt表示大于，大于多少呢？是25。 -
结果如下：
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.6931472,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "4",
"_score" : 0.6931472,
"_source" : {
"name" : "石头",
"age" : 29,
"from" : "gu",
"desc" : "粗中有细，狐假虎威",
"tags" : [
"粗",
"大",
"猛"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "顾老二",
"age" : 30,
"from" : "gu",
"desc" : "皮肤黑、武器长、性格直",
"tags" : [
"黑",
"长",
"直"
]
}
}
]
}
}
-
上例中，
age大于25的条件都已经筛选出来了。 -
那么要查询
from是gu，age大于等于30的数据呢？
GET test1/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"from": "gu"
}
}
],
"filter": {
"range": {
"age": {
"gte": 30
}
}
}
}
}
}
-
上例中，大于等于用
gte表示。 -
结果如下：
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "顾老二",
"age" : 30,
"from" : "gu",
"desc" : "皮肤黑、武器长、性格直",
"tags" : [
"黑",
"长",
"直"
]
}
}
]
}
}
- 那么，要查询
age小于25的呢？
GET test1/doc/_search
{
"query": {
"bool": {
"filter": {
"range": {
"age": {
"lt": 25
}
}
}
}
}
}
- 上例中，小于用
lt表示，结果如下：
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.0,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "2",
"_score" : 0.0,
"_source" : {
"name" : "大娘子",
"age" : 18,
"from" : "sheng",
"desc" : "肤白貌美，娇憨可爱",
"tags" : [
"白",
"富",
"美"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 0.0,
"_source" : {
"name" : "龙套偏房",
"age" : 22,
"from" : "gu",
"desc" : "mmp，没怎么看，不知道怎么形容",
"tags" : [
"造数据",
"真",
"难"
]
}
}
]
}
}
- 在查询一个
age小于等于18的怎么办呢？
GET test1/doc/_search
{
"query": {
"bool": {
"filter": {
"range": {
"age": {
"lte": 18
}
}
}
}
}
}
- 上例中，小于等于用
lte表示。结果如下：
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.0,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "2",
"_score" : 0.0,
"_source" : {
"name" : "大娘子",
"age" : 18,
"from" : "sheng",
"desc" : "肤白貌美，娇憨可爱",
"tags" : [
"白",
"富",
"美"
]
}
}
]
}
}
- 要查询
from是gu，age在25~30之间的怎么查？
GET test1/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"from": "gu"
}
}
],
"filter": {
"range": {
"age": {
"gte": 25,
"lte": 30
}
}
}
}
}
}
- 上例中，使用
lte和gte来限定范围。结果如下：
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 2,
"max_score" : 0.6931472,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "4",
"_score" : 0.6931472,
"_source" : {
"name" : "石头",
"age" : 29,
"from" : "gu",
"desc" : "粗中有细，狐假虎威",
"tags" : [
"粗",
"大",
"猛"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"name" : "顾老二",
"age" : 30,
"from" : "gu",
"desc" : "皮肤黑、武器长、性格直",
"tags" : [
"黑",
"长",
"直"
]
}
}
]
}
}
- 那么，要查询
from是sheng，age小于等于25的怎么查呢？其实结果，我们可能已经想到了，只有一条，因为只有盛家小六符合结果。
GET test1/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"from": "sheng"
}
}
],
"filter": {
"range": {
"age": {
"lte": 25
}
}
}
}
}
}
- 结果果然不出洒家所料！
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.6931472,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "2",
"_score" : 0.6931472,
"_source" : {
"name" : "大娘子",
"age" : 18,
"from" : "sheng",
"desc" : "肤白貌美，娇憨可爱",
"tags" : [
"白",
"富",
"美"
]
}
}
]
}
}
- 但是，洒家手一抖，将
must换为should看看会发生什么？
GET test1/doc/_search
{
"query": {
"bool": {
"should": [
{
"match": {
"from": "sheng"
}
}
],
"filter": {
"range": {
"age": {
"lte": 25
}
}
}
}
}
}
- 结果如下：
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : 0.6931472,
"hits" : [
{
"_index" : "test1",
"_type" : "doc",
"_id" : "2",
"_score" : 0.6931472,
"_source" : {
"name" : "大娘子",
"age" : 18,
"from" : "sheng",
"desc" : "肤白貌美，娇憨可爱",
"tags" : [
"白",
"富",
"美"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "5",
"_score" : 0.0,
"_source" : {
"name" : "魏行首",
"age" : 25,
"from" : "广云台",
"desc" : "仿佛兮若轻云之蔽月,飘飘兮若流风之回雪,mmp，最后竟然没有嫁给顾老二！",
"tags" : [
"闭月",
"羞花"
]
}
},
{
"_index" : "test1",
"_type" : "doc",
"_id" : "3",
"_score" : 0.0,
"_source" : {
"name" : "龙套偏房",
"age" : 22,
"from" : "gu",
"desc" : "mmp，没怎么看，不知道怎么形容",
"tags" : [
"造数据",
"真",
"难"
]
}
}
]
}
}
-
结果有点出乎意料，因为龙套偏房和魏行首不属于盛家，但也被查询出来了。那你要问了，怎么肥四？小老弟！这是因为在查询过程中，优先经过
filter过滤，因为should是或关系，龙套偏房和魏行首的年龄符合了filter过滤条件，也就被放行了！所以，如果在filter过滤条件中使用should的话，结果可能不会尽如人意！建议使用must代替。 -
注意：
filter工作于bool查询内。比如我们将刚才的查询条件改一下，把filter从bool中挪出来。
GET test1/doc/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"from": "sheng"
}
}
]
},
"filter": {
"range"： {
"age": {
"lte": 25
}
}
}
}
}
- 如上例所示，我们将
filter与bool平级，看查询结果：
{
"error": {
"root_cause": [
{
"type": "parsing_exception",
"reason": "[bool] malformed query, expected [END_OBJECT] but found [FIELD_NAME]",
"line": 12,
"col": 5
}
],
"type": "parsing_exception",
"reason": "[bool] malformed query, expected [END_OBJECT] but found [FIELD_NAME]",
"line": 12,
"col": 5
},
"status": 400
}
- 结果报错了！所以，
filter工作位置很重要。
7. 小结：
-
must：与关系，相当于关系型数据库中的and。 -
should：或关系，相当于关系型数据库中的or。 -
must_not：非关系，相当于关系型数据库中的not。 -
filter：过滤条件。 -
range：条件筛选范围。 -
gt：大于，相当于关系型数据库中的>。 -
gte：大于等于，相当于关系型数据库中的>=。 -
lt：小于，相当于关系型数据库中的<。 -
lte：小于等于，相当于关系型数据库中的<=。