PUT people
{
"query": {
"match": {
"name": "lisi"
}
}
}
{
"query": {
"match_all": {}
}
}
# "query":这里的 query 代表一个查询对象,里面可以有不同的查询属性
# "match_all":查询类型,例如:match_all(代表查询所有),match,term,range 等等
# {查询条件}:查询条件会根据类型的不同,写法也有差异
{
"took": 0,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 6,
"relation": "eq"
},
"max_score": 1,
"hits": [
{
"_index": "people",
"_id": "1001",
"_score": 1,
"_source": {
"name": "zhangsan",
"nickname": "zhangsan",
"sex": "男",
"age": 30
}
},
{
"_index": "people",
"_id": "1002",
"_score": 1,
"_source": {
"name": "lisi",
"nickname": "lisi",
"sex": "男",
"age": 20
}
},
{
"_index": "people",
"_id": "1003",
"_score": 1,
"_source": {
"name": "wangwu",
"nickname": "wangwu",
"sex": "女",
"age": 40
}
},
{
"_index": "people",
"_id": "1004",
"_score": 1,
"_source": {
"name": "zhangsan1",
"nickname": "zhangsan1",
"sex": "女",
"age": 50
}
},
{
"_index": "people",
"_id": "1005",
"_score": 1,
"_source": {
"name": "zhangsan2",
"nickname": "zhangsan2",
"sex": "女",
"age": 30
}
},
{
"_index": "people",
"_id": "1006",
"_score": 1,
"_source": {
"name": "zhangsan222",
"nickname": "zhangsan222",
"sex": "女",
"age": 30
}
}
]
}
}
multi_match
与 match
类似,不同的是它可以在多个字段中查询。{
"query": {
"multi_match": {
"query": "zhangsan",
"fields": ["name","nickname"]
}
}
}
查询 key 为 name
和 nickname
,value 为 zhangsan
的数据
term
查询,精确的关键词匹配查询,不对查询条件进行分词,即只能单关键字精确查询。{
"query": {
"term": {
"name": {
"value": "zhangsan"
}
}
}
}
{
"query": {
"terms": {
"name": ["zhangsan","lisi"]
}
}
}
_source
的所有字段都返回。_source
的过滤{
"_source": ["name","nickname"],
"query": {
"terms": {
"nickname": ["zhangsan"]
}
}
}
{
"_source": {
"includes": ["name","nickname"]
},
"query": {
"terms": {
"nickname": ["zhangsan"]
}
}
}
bool
把各种其它查询通过 must
(必须,类似 and)、must_not
(必须不,类似 not)、should
(应该 类似 or)的方式进行组合{
"query": {
"bool": {
"must": [
{
"match": {
"name": "zhangsan"
}
}
],
"must_not": [
{
"match": {
"age": "40"
}
}
],
"should": [
{
"match": {
"sex": "男"
}
}
]
}
}
}
range
查询找出那些落在指定区间内的数字或者时间。range
查询允许以下字符操作符 | 说明 |
---|---|
gt | > |
gte | >= |
lt | < |
lte | <= |
{
"query": {
"range": {
"age": {
"gte": 30,
"lte": 35
}
}
}
}
fuzzy
:返回包含与搜索字词相似的字词的文档,更多fuzzy
有关解释请查看官方文档 (opens new window) -编辑距离是将一个术语转换为另一个术语所需的一个字符更改的次数。这些更改可以包括:fuzziness
修改编辑距离。一般使用默认值 AUTO
,根据术语的长度生成编辑距离。{
"query": {
"fuzzy": {
"name": {
"value": "zhangsan"
}
}
}
}
{
"took": 15,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 3,
"relation": "eq"
},
"max_score": 1.540445,
"hits": [
{
"_index": "people",
"_id": "1001",
"_score": 1.540445,
"_source": {
"name": "zhangsan",
"nickname": "zhangsan",
"sex": "男",
"age": 30
}
},
{
"_index": "people",
"_id": "1004",
"_score": 1.3478894,
"_source": {
"name": "zhangsan1",
"nickname": "zhangsan1",
"sex": "女",
"age": 50
}
},
{
"_index": "people",
"_id": "1005",
"_score": 1.3478894,
"_source": {
"name": "zhangsan2",
"nickname": "zhangsan2",
"sex": "女",
"age": 30
}
}
]
}
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 3,
"relation": "eq"
},
"max_score": 1.540445,
"hits": [
{
"_index": "people",
"_id": "1001",
"_score": 1.540445,
"_source": {
"name": "zhangsan",
"nickname": "zhangsan",
"sex": "男",
"age": 30
}
},
{
"_index": "people",
"_id": "1004",
"_score": 1.3478894,
"_source": {
"name": "zhangsan1",
"nickname": "zhangsan1",
"sex": "女",
"age": 50
}
},
{
"_index": "people",
"_id": "1005",
"_score": 1.3478894,
"_source": {
"name": "zhangsan2",
"nickname": "zhangsan2",
"sex": "女",
"age": 30
}
}
]
}
}
{
"query": {
"ids" : {
"values" : ["1001", "1004", "1006"]
}
}
}
{
"query": {
"prefix": {
"name": {
"value": "zhangsan"
}
}
}
}
sort
可以让我们按照不同的字段进行排序,并且通过 order
指定排序的方式。desc
降序,asc
升序{
"query": {
"match": {
"name":"zhangsan"
}
},
"sort": [{
"age": {
"order":"desc"
}
}]
}
{
"query": {
"match_all": {}
},
"sort": [
{
"age": {
"order": "desc"
}
},
{
"_score":{
"order": "desc"
}
}
]
}
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 6,
"relation": "eq"
},
"max_score": null,
"hits": [
{
"_index": "people",
"_id": "1004",
"_score": 1,
"_source": {
"name": "zhangsan1",
"nickname": "zhangsan1",
"sex": "女",
"age": 50
},
"sort": [
50,
1
]
},
{
"_index": "people",
"_id": "1003",
"_score": 1,
"_source": {
"name": "wangwu",
"nickname": "wangwu",
"sex": "女",
"age": 40
},
"sort": [
40,
1
]
},
{
"_index": "people",
"_id": "1001",
"_score": 1,
"_source": {
"name": "zhangsan",
"nickname": "zhangsan",
"sex": "男",
"age": 30
},
"sort": [
30,
1
]
},
{
"_index": "people",
"_id": "1005",
"_score": 1,
"_source": {
"name": "zhangsan2",
"nickname": "zhangsan2",
"sex": "女",
"age": 30
},
"sort": [
30,
1
]
},
{
"_index": "people",
"_id": "1006",
"_score": 1,
"_source": {
"name": "zhangsan222",
"nickname": "zhangsan222",
"sex": "女",
"age": 30
},
"sort": [
30,
1
]
},
{
"_index": "people",
"_id": "1002",
"_score": 1,
"_source": {
"name": "lisi",
"nickname": "lisi",
"sex": "男",
"age": 20
},
"sort": [
20,
1
]
}
]
}
}
Elasticsearch
可以对查询内容中的关键字部分,进行标签和样式(高亮)的设置。在使用 match
查询的同时,加上一个 highlight
属性:
pre_tags
:前置标签post_tags
:后置标签fields
:需要高亮的字段title
:这里声明 title
字段需要高亮,后面可以为这个字段设置特有配置,也可以为空{
"query": {
"match": {
"name": "zhangsan"
}
},
"highlight": {
"pre_tags": "<font color='red'>",
"post_tags": "</font>",
"fields": {
"name": {}
}
}
}
from
:当前页的起始索引,默认从 0 开始。 from = (pageNum - 1) * sizesize
:每页显示多少条{
"query": {
"match_all": {}
},
"sort": [
{
"age": {
"order": "desc"
}
}
],
"from": 0,
"size": 2
}
聚合允许使用者对 es 文档进行统计分析,类似与关系型数据库中的 group by,当然还有很多其他的聚合,例如取最大值、平均值等等。
聚合查询 aggs
字段,该字段里的第一个字段是自定义名字,一个聚合/分组需要另一个聚合/分组需要用到自定义名字(嵌套查询)。第二个字段是聚合查询类型。查询结果不仅有聚合结果,也有设计到的详细数据。
结果长度 size
字段和 aggs
字段同级,代表只获取聚合结果,不获取涉及到的详细数据。
{
"aggs" : {//聚合操作
"price_group":{ //名称,随意起名
"terms":{ //分组操作
"field":"age" //分组字段
}
}
},
"size":0
}
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 6,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"price_group": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 30,
"doc_count": 3
},
{
"key": 20,
"doc_count": 1
},
{
"key": 40,
"doc_count": 1
},
{
"key": 50,
"doc_count": 1
}
]
}
}
}
price
的平均值,将terms
改为avg
{
"took": 0,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 6,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"price_group": {
"value": 33.333333333333336
}
}
}
请求体内容
{
"aggs":{
"max_age":{ // 自定义名字
"max":{"field":"age"}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}
请求体内容
{
"aggs":{
"min_age":{ // 自定义名字
"min":{"field":"age"}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}
请求体内容
{
"aggs":{
"sum_age":{ // 自定义名字
"sum":{"field":"age"}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}
请求体内容
{
"aggs":{
"avg_age":{ // 自定义名字
"avg":{"field":"age"}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}
请求体内容
{
"aggs":{
"distinct_age":{ // 自定义名字
"cardinality":{"field":"age"}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}
stats
聚合,对某个字段一次性返回 count
,max
,min
,avg
和 sum
五个指标
请求体内容
{
"aggs":{
"stats_age":{ // 自定义名字a
"stats":{"field":"age"}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}
桶聚和相当于 sql
中的 group by
语句
terms
聚合,分组统计请求体内容
{
"aggs":{
"age_groupby":{ // 自定义名字
"terms":{"field":"age"}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}
请求体内容
{
"aggs":{
"age_groupby":{ // 自定义名字
"terms":{
"field": "age",
},
"aggs": {
"average_age": {
"avg": {
"field": "age"
}
}
}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}
terms
分组下再进行聚合和排序请求体内容
{
"aggs":{
"age_groupby":{ // 自定义名字
"terms":{
"field": "age",
"order": {
"average_age": "desc"
}
},
"aggs": {
"average_age": {
"avg": {
"field": "age"
}
}
}
}
},
"size":0 // 只获取聚合结果,不获取每一个数据
}