0、ES6.X 一对多、多对多的数据该如何存储和实现呢？
引出问题：
“某头条新闻APP”新闻内容和新闻评论是1对多的关系？
在ES6.X该如何存储、如何进行高效检索、聚合操作呢？
相信阅读本文，你就能得到答案！
1、ES6.X 新类型Join 产生背景
Mysql中多表关联，我们可以通过left join 或者Join等实现；
ES5.X版本，借助父子文档实现多表关联，类似数据库中Join的功能；实现的核心是借助于ES5.X支持1个索引(index)下多个类型(type)。
ES6.X版本，由于每个索引下面只支持单一的类型（type）。
所以，ES6.X版本如何实现Join成为大家关注的问题。
幸好，ES6.X新推出了Join类型，主要解决类似Mysql中多表关联的问题。
2、ES6.X Join类型介绍
仍然是一个索引下，借助父子关系，实现类似Mysql中多表关联的操作。
3、ES6.X Join类型实战
3.1 ES6.X Join类型 Mapping定义
Join类型的Mapping如下:
核心
- 1） “my_join_field”为join的名称。
2）”question”: “answer” 指：qustion为answer的父类。
PUT my_join_index
{
"mappings": {
"_doc": {
"properties": {
"my_join_field": {
"type": "join",
"relations": {
"question": "answer"
}
}
}
}
}
}3.2 ES6.X join类型定义父文档
直接上以下简化的形式，更好理解些。
如下，定义了两篇父文档。
文档类型为父类型:”question”。
PUT my_join_index/_doc/1?refresh
{
"text": "This is a question",
"my_join_field": "question"
}
PUT my_join_index/_doc/2?refresh
{
"text": "This is another question",
"my_join_field": "question"
}3.3 ES6.X join类型定义子文档
路由值是强制性的，因为父文件和子文件必须在相同的分片上建立索引。
“answer”是此子文档的加入名称。
指定此子文档的父文档ID：1。
PUT my_join_index/_doc/3?routing=1&refresh
{
"text": "This is an answer",
"my_join_field": {
"name": "answer",
"parent": "1"
}
}
PUT my_join_index/_doc/4?routing=1&refresh
{
"text": "This is another answer",
"my_join_field": {
"name": "answer",
"parent": "1"
}
}4、ES6.X Join类型约束
每个索引只允许一个Join类型Mapping定义；
父文档和子文档必须在同一个分片上编入索引；这意味着，当进行删除、更新、查找子文档时候需要提供相同的路由值。
一个文档可以有多个子文档，但只能有一个父文档。
可以为已经存在的Join类型添加新的关系。
当一个文档已经成为父文档后，可以为该文档添加子文档。
5、ES6.X Join类型检索与聚合
5.1 ES6.X Join全量检索
GET my_join_index/_search
{
"query": {
"match_all": {}
},
"sort": ["_id"]
}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": null,
"hits": [
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "1",
"_score": null,
"_source": {
"text": "This is a question",
"my_join_field": "question"
},
"sort": [
"1"
]
},
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "2",
"_score": null,
"_source": {
"text": "This is another question",
"my_join_field": "question"
},
"sort": [
"2"
]
},
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "3",
"_score": null,
"_routing": "1",
"_source": {
"text": "This is an answer",
"my_join_field": {
"name": "answer",
"parent": "1" }
},
"sort": [
"3"
]
},
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "4",
"_score": null,
"_routing": "1",
"_source": {
"text": "This is another answer",
"my_join_field": {
"name": "answer",
"parent": "1" }
},
"sort": [
"4"
]
}
]
}
}5.2 ES6.X 基于父文档查找子文档
GET my_join_index/_search
{
"query": {
"has_parent" : {
"parent_type" : "question",
"query" : {
"match" : {
"text" : "This is"
}
}
}
}
}返回结果：
{
"took": 0,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 1,
"hits": [
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "3",
"_score": 1,
"_routing": "1",
"_source": {
"text": "This is an answer",
"my_join_field": {
"name": "answer",
"parent": "1" }
}
},
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "4",
"_score": 1,
"_routing": "1",
"_source": {
"text": "This is another answer",
"my_join_field": {
"name": "answer",
"parent": "1" }
}
}
]
}
}5.3 ES6.X 基于子文档查找父文档
GET my_join_index/_search
{
"query": {
"has_child" : {
"type" : "answer",
"query" : {
"match" : {
"text" : "This is question"
}
}
}
}
}返回结果：
{
"took": 0,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 1,
"hits": [
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "1",
"_score": 1,
"_source": {
"text": "This is a question",
"my_join_field": "question"
}
}
]
}
}5.4 ES6.X Join聚合操作实战
以下操作含义如下：
1）parent_id是特定的检索方式，用于检索属于特定父文档id=1的，子文档类型为answer的文档的个数。
2）基于父文档类型question进行聚合；
3）基于指定的field处理。
GET my_join_index/_search
{
"query": {
"parent_id": {
"type": "answer",
"id": "1"
}
},
"aggs": {
"parents": {
"terms": {
"field": "my_join_field#question",
"size": 10
}
}
},
"script_fields": {
"parent": {
"script": {
"source": "doc['my_join_field#question']"
}
}
}
}返回结果：
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0.13353139,
"hits": [
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "3",
"_score": 0.13353139,
"_routing": "1",
"fields": {
"parent": [
"1"
]
}
},
{
"_index": "my_join_index",
"_type": "_doc",
"_id": "4",
"_score": 0.13353139,
"_routing": "1",
"fields": {
"parent": [
"1"
]
}
}
]
},
"aggregations": {
"parents": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "1",
"doc_count": 2
}
]
}
}
}6、ES6.X Join 一对多实战
6.1 一对多定义
如下，一个父文档question与多个子文档answer，comment的映射定义。
PUT join_ext_index
{
"mappings": {
"_doc": {
"properties": {
"my_join_field": {
"type": "join",
"relations": {
"question": ["answer", "comment"]
}
}
}
}
}
}6.2 一对多对多定义
实现如下图的祖孙三代关联关系的定义。
question / \ / \ comment answer | | vote
PUT join_multi_index
{
"mappings": {
"_doc": {
"properties": {
"my_join_field": {
"type": "join",
"relations": {
"question": ["answer", "comment"],
"answer": "vote"
}
}
}
}
}
}孙子文档导入数据，如下所示：
PUT join_multi_index/_doc/3?routing=1&refresh
{
"text": "This is a vote",
"my_join_field": {
"name": "vote",
"parent": "2"
}
}注意：
- 孙子文档所在分片必须与其父母和祖父母相同 - 孙子文档的父代号（必须指向其父亲answer文档）
7、小结
虽然ES官方文档已经很详细了，详见：
https://www.elastic.co/guide/en/elasticsearch/reference/current/parent-join.html
但手敲一遍，翻译一遍，的的确确会更新认知，加深理解。
和你一起，死磕ELK Stack！
作者：铭毅天下
转载请标明出处，原文地址：
https://blog.csdn.net/laoyang360/article/details/79774481
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