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es-object vs nested vs has_child and has_parent
2022-06-22 01:35:00 【童小绿】
1.object类型
增加object类型的索引
PUT /joining_query_object_test/_doc/1
{
"obj1": {
"name": "blue",
"count": 5
},
"tags": [
"龙虎榜",
"金牛奖"
],
"comments": [
{
"name": "司马懿",
"comment": "智务其实,愚争虚名",
"age": 28,
"stars": 4,
"date": "2022-05-01"
},
{
"name": "刘伯温",
"comment": "平而后清,清而后明",
"age": 31,
"stars": 5,
"date": "2022-05-11"
}
],
"group" : "fans",
"user" : [
{
"first" : "John",
"last" : "Smith"
},
{
"first" : "Alice",
"last" : "White"
}
]
}
PUT /joining_query_object_test/_doc/2
{
"obj1": {
"name": "red",
"count": 3
},
"tags": [
"1h热股",
"24h热股"
],
"comments": [
{
"name": "刘基",
"comment": "有酒且尽欢，听我薤露歌",
"age": 42,
"stars": 3,
"date": "2022-05-02"
},
{
"name": "袁天罡",
"comment": "兴也洛水，衰也洛水",
"age": 32,
"stars": 4,
"date": "2022-05-12"
}
],
"group" : "fans",
"user" : [
{
"first" : "xiaoping",
"last" : "liu"
},
{
"first" : "tianji",
"last" : "li"
}
]
}
查看mapping
GET /joining_query_object_test/_mapping/
##查询年龄是32岁的刘基评论
##理论上应该hit 1，结果 hit 2
##刘基时42岁，32岁的是袁天罡，根本不是同一条评论
##原因：object类型底层数据结构，会将一个json数组中的数据，进行扁平化
GET /joining_query_object_test/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"comments.name": "刘基"
}
},
{
"match": {
"comments.age": 32
}
}
]
}
}
}
## 验证：
##+(+(comments.name:刘 comments.name:基) +comments.age:[32 TO 32]) #MatchNoDocsQuery("")
GET /joining_query_object_test/_mapping/_validate/query?explain
{
"query": {
"bool": {
"must": [
{
"match": {
"comments.name": "刘基"
}
},
{
"match": {
"comments.age": 32
}
}
]
}
}
}
##查询first=Alice and last=Smith 出现数据不准的问题
GET joining_query_object_test/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"user.first": "Alice" }},
{
"match": {
"user.last": "Smith" }}
]
}
}
}
2.nested query
- doc必须是nested类型。
- nested类型就是为了解决object类型在对象数组上丢失关联性的问题的
（1）nested query
##设置mapping
DELETE joining_query_nested_test
PUT /joining_query_nested_test
{
"mappings": {
"properties": {
"obj1": {
"type": "nested"
},
"comments": {
"type": "nested",
"properties": {
"name": {
"type": "text" },
"comment": {
"type": "text" },
"age": {
"type": "short" },
"stars": {
"type": "short" },
"date": {
"type": "date" }
}
},
"user": {
"type": "nested"
}
}
}
}
##增加doc
PUT /joining_query_nested_test/_doc/1
{
"obj1": {
"name": "blue",
"count": 5
},
"tags": [
"龙虎榜",
"金牛奖"
],
"comments": [
{
"name": "司马懿",
"comment": "智务其实,愚争虚名",
"age": 28,
"stars": 4,
"date": "2022-05-01"
},
{
"name": "刘伯温",
"comment": "平而后清,清而后明",
"age": 31,
"stars": 5,
"date": "2022-05-11"
}
],
"group" : "fans",
"user" : [
{
"first" : "John",
"last" : "Smith"
},
{
"first" : "Alice",
"last" : "White"
}
]
}
PUT /joining_query_nested_test/_doc/2
{
"obj1": {
"name": "red",
"count": 3
},
"tags": [
"1h热股",
"24h热股"
],
"comments": [
{
"name": "刘基",
"comment": "有酒且尽欢，听我薤露歌",
"age": 42,
"stars": 3,
"date": "2022-05-02"
},
{
"name": "袁天罡",
"comment": "兴也洛水，衰也洛水",
"age": 32,
"stars": 4,
"date": "2022-05-12"
}
],
"group" : "fans",
"user" : [
{
"first" : "xiaoping",
"last" : "liu"
},
{
"first" : "tianji",
"last" : "li"
}
]
}
##查询mapping(object nested)
GET /joining_query_object_test/_mapping/
GET /joining_query_nested_test/_mapping/
##查询年龄是32岁的刘基评论
##解决object的扁平化问题，刘基时42岁，32岁的是袁天罡，根本不是同一条评论
##结果:hit 0 符合预期
GET /joining_query_nested_test/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"comments.name": "刘基"
}
},
{
"match": {
"comments.age": 32
}
}
]
}
}
}
##_validate验证一下
##+(+(comments.name:刘 comments.name:基) +comments.age:[32 TO 32]) #MatchNoDocsQuery("") #DocValuesFieldExistsQuery [field=_primary_term]
GET /joining_query_nested_test/_mapping/_validate/query?explain
{
"query": {
"bool": {
"must": [
{
"match": {
"comments.name": "刘基"
}
},
{
"match": {
"comments.age": 32
}
}
]
}
}
}
##查询first=Alice and last=Smith
##hit: 0 符合预期
GET joining_query_nested_test/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"user.first": "Alice" }},
{
"match": {
"user.last": "Smith" }}
]
}
}
}
##查询name=blue，count>4的记录
## hit:1
GET /joining_query_object_test/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"obj1.name": "blue" } },
{
"range": {
"obj1.count": {
"gt": 4 } } }
]
}
}
}
（2）查询+聚合
## 查询name=blue，count>4的记录，并聚合求avg
## hit:1
GET /joining_query_nested_test/_search
{
"query": {
"nested": {
"path": "obj1",
"query": {
"bool": {
"must": [
{
"match": {
"obj1.name": "blue" } },
{
"range": {
"obj1.count": {
"gt": 4 } } }
]
}
},
"score_mode": "avg"
}
}
}
（3） Multi-level nested queries 多级嵌套查询
PUT /drivers
{
"mappings": {
"properties": {
"driver": {
"type": "nested",
"properties": {
"last_name": {
"type": "text"
},
"vehicle": {
"type": "nested",
"properties": {
"make": {
"type": "text"
},
"model": {
"type": "text"
}
}
}
}
}
}
}
}
PUT /drivers/_doc/1
{
"driver" : {
"last_name" : "McQueen",
"vehicle" : [
{
"make" : "Powell Motors",
"model" : "Canyonero"
},
{
"make" : "Miller-Meteor",
"model" : "Ecto-1"
}
]
}
}
PUT /drivers/_doc/2?refresh
{
"driver" : {
"last_name" : "Hudson",
"vehicle" : [
{
"make" : "Mifune",
"model" : "Mach Five"
},
{
"make" : "Miller-Meteor",
"model" : "Ecto-1"
}
]
}
}
##使用多级嵌套查询根据 make 和 model 字段匹配文档
GET /drivers/_search
{
"query": {
"nested": {
"path": "driver",
"query": {
"nested": {
"path": "driver.vehicle",
"query": {
"bool": {
"must": [
{
"match": {
"driver.vehicle.make": "Powell Motors" } },
{
"match": {
"driver.vehicle.model": "Canyonero" } }
]
}
}
}
}
}
}
}
3.has_child and has_parent
##单个索引内的文档之间可以存在连接字段关系。
##插入子文档注意：子文档必须和父文档在同一分片上，父文档，有路由存在时，插入子文档必须也填上和父文档相同的路由。
##查询文档的时候注意：
##has_child 查询返回其子文档与指定查询匹配的父文档，
##has_parent 查询返回其父文档与指定查询匹配的子文档。
Parent/child VS nested
父-子关系文档 在实质上类似于 nested model ：允许将一个对象实体和另外一个对象实体关联起来。
（1）nested objects ，所有对象都是在同一个文档中，读取性能高
（2）Parent/child，父对象和子对象都是完全独立的文档，父子更新互不影响
- 修改索引的时候的影响范围(场景)
- （1）nested，更新父子文档的时候需要更新整个文档
- （2）Parent/child，创建，修改或删除子文档时，不会影响父文档或其他子文档，但是为了维护join的关系，需要占用部分内存，读取性能较差
##设置父子结构的mapping ，join + relations
PUT /joining_query_child_test
{
"mappings": {
"properties": {
"my-join-field": {
"type": "join",
"relations": {
"parent": "child"
}
},
"tag": {
"type": "keyword"
}
}
}
}
##使用has_child查询
GET /joining_query_child_test/_search
{
"query": {
"has_child": {
"type": "child",
"query": {
"match_all": {
}
},
"max_children": 10,
"min_children": 2,
"score_mode": "min"
}
}
}
PUT /joining_query_father_test
{
"mappings": {
"father":{
"properties": {
"id":{
"type": "integer"
},
"name":{
"type": "keyword"
}
}
},
"childers":{
"_parent": {
"type": "father"
},
"properties": {
"age":{
"type": "integer"
},
"name":{
"type": "keyword"
}
}
}
}
}
PUT three_tree_index
{
"mappings": {
"properties": {
"name": {
"type": "text"
},
"age": {
"type": "keyword"
},
"my_join_field": {
"type": "join",
"relations": {
"user_base": "article",
"article": "vote"
}
},
"stars": {
"type": "short"
},
"article_desc": {
"type": "text"
}
}
}
}
#插入6条数据
PUT three_tree_index/_doc/1?routing=1&refresh
{
"name":"xiaoming",
"age":29,
"my_join_field":"user_base"
}
PUT three_tree_index/_doc/2?routing=2&refresh
{
"name":"xiaohong",
"age":32,
"my_join_field":"user_base"
}
PUT three_tree_index/_doc/3?routing=1&refresh
{
"article_desc":"xiaoming,article_desc_1",
"my_join_field":{
"name":"article",
"parent":"1"
}
}
PUT three_tree_index/_doc/4?routing=2&refresh
{
"article_desc":"xiaohong,article_desc_1",
"my_join_field":{
"name":"article",
"parent":"2"
}
}
PUT three_tree_index/_doc/5?routing=1&refresh
{
"stars":5,
"my_join_field":{
"name":"vote",
"parent":"3"
}
}
PUT three_tree_index/_doc/6?routing=2&refresh
{
"stars":3,
"my_join_field":{
"name":"vote",
"parent":"4"
}
}
## three_tree_index
## hits : 6
GET /three_tree_index/_search
##查询文章内容有“xiaoming”的用户信息
##通过查询has_child查询到parent信息
GET three_tree_index/_search
{
"query": {
"has_child": {
"type": "article",
"query": {
"match": {
"article_desc": "xiaoming"
}
}
}
}
}
##可以通过添加"inner_hits":{
}，将父和子文档都返回出来
##_source：父
##inner_hits：子
GET three_tree_index/_search
{
"query": {
"has_child": {
"type": "article",
"query": {
"match": {
"article_desc": "xiaoming"
}
},
"inner_hits": {
}
}
}
}
##查询有五星评价的文章对应的用户（嵌套两层has_child查询）
GET three_tree_index/_search
{
"query": {
"bool": {
"must": [
{
"has_child": {
"type": "article",
"query": {
"has_child": {
"type": "vote",
"query": {
"bool": {
"should": [
{
"term": {
"stars": 5
}
}
]
}
}
}
}
}
}
]
}
}
}
##has_parent的功能正好相反，比如我想搜索所有包含“xiaoming”的文章的平均星级
GET three_tree_index/_search
{
"query": {
"has_parent": {
"parent_type": "article",
"query": {
"bool": {
"should": [
{
"match": {
"article_desc": "xiaoming"
}
}
]
}
},
"inner_hits": {
}
}
},
"aggs": {
"avg_star": {
"avg": {
"field": "stars"
}
}
}
}
## 使用 has _ father 查询，索引必须包含连接字段映射
DELETE joining_parent_test_02
PUT /joining_parent_test_02
{
"mappings": {
"properties": {
"my-join-field": {
"type": "join",
"relations": {
"parent": "child"
}
},
"tag": {
"type": "keyword"
}
}
}
}
GET /joining_parent_test_02/_search
{
"query": {
"has_parent": {
"parent_type": "parent",
"query": {
"term": {
"tag": {
"value": "Elasticsearch"
}
}
}
}
}
}
##Parent ID query 父母身份查询===================================================================================
##1.Create an index with a join field mapping.join + relations
DELETE my-index-000001
PUT /my-index-000001
{
"mappings": {
"properties": {
"my-join-field": {
"type": "join",
"relations": {
"my-parent": "my-child"
}
}
}
}
}
##2.父文档索引
PUT /my-index-000001/_doc/1?refresh
{
"text": "This is a parent document.",
"my-join-field": "my-parent"
}
##3.子文档索引
PUT /my-index-000001/_doc/2?routing=1&refresh
{
"text": "This is a child document.",
"my-join-field": {
"name": "my-child",
"parent": "1"
}
}
##4.搜索返回 ID 为1的父文档的子文档。
## hit :1
GET /my-index-000001/_search
{
"query": {
"parent_id": {
"type": "my-child",
"id": "1"
}
}
}
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