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ES（ElasticSearch）数据建模最佳实践之「一对多对多关系建模」

ES建模elasticsearch数据 实践 最佳 关系 一对
2023-06-13 09:16:46 时间

一、开门见山

关系型数据库 MySQL 的 join 关系如何在 ES 中实现。

官方文档链接介绍如下：

https://www.elastic.co/guide/en/elasticsearch/reference/6.3/joining-queries.html

  • Nested object：嵌套对象
  • Parent child：父子关系

二、商铺SPU模型

电商系统常见的一对多对多关系：

一个商铺下有多个商品，一个商品下有多个单品，如北京 iphone xxx 店铺，有 iphone 手机、mac 电脑，这些属于商品，而用户购买的 iphone13 128G 黑色国行手机，这个就属于售卖的单品。关系图如下所示：

下面以父子文档为例，介绍 ES 如何构建多表之间的复杂关联数据模型

可参考官方文档：

https://www.elastic.co/guide/en/elasticsearch/reference/current/parent-join.html

附：索引 Mapping Type 有：text, keyword, date, integer, long, double, Boolean 等

三、实战演练

从官网下载 elasticsearch 和对应版本的 kibana-win 版本的安装包，可以按下文一步步操作，效果更好：

（1）双击 elasticsearch.bat，启动本地 es 服务：

\elasticsearch-6.3.2\bin\elasticsearch.bat

（2）然后双击 kibana.bat 文件，启动对应版本的 kibana 服务：

\kibana-6.3.2-windows-x86_64\bin\ kibana.bat

（3）本地访问kibana：http://localhost:5601/。

（4）点击右侧菜单栏【Dev Tools】，如下所示：

（5）构建祖孙三层结构索引

// ①创建store_spu_sku_index索引并构建store_spu_sku类型PUT /store_spu_sku_index{ "mappings": { "store_spu_sku": { "properties": { "store_spu_sku_join": { "type": "join", "relations": { "store": "spu", "spu": "sku" } }, "storeId": { "type": "keyword" }, "storeName": { "type": "text" }, "spuId": { "type": "keyword" }, "spuName": { "type": "text" }, "skuId": { "type": "keyword" }, "skuName": { "type": "text" } } } }}

// ②查询索引类型的结构GET /store_spu_sku_index/store_spu_sku/_mapping或GET /store_spu_sku_index

// ③删除索引DELETE store_spu_sku_index

注（以下对ES6.x适用，其他版本可能不适宜，但是万变不离其宗）：

  • 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，路由设置相同；
  • 一个文档可以存在多个子文档，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；
  • 子文档不能独立存在，先有父文档，才能创建子文档。

（6）创建父文档：

// 插入父类PUT /store_spu_sku_index/store_spu_sku/s1?refresh{ "storeId":"s1", "storeName":"店铺名称s1", "store_spu_sku_join":"store"}

PUT /store_spu_sku_index/store_spu_sku/s2?refresh{ "storeId":"s2", "storeName":"店铺名称s2", "store_spu_sku_join":"store"}

（7）创建子文档：

// 插入子文档PUT /store_spu_sku_index/store_spu_sku/spu1?routing=s1&refresh{ "spuName":"spu名称1-s1", "spuId":"spu1", "store_spu_sku_join":{ "name":"spu", "parent":"s1" }}

PUT /store_spu_sku_index/store_spu_sku/spu2?routing=s1&refresh{ "spuName":"spu名称2-s1", "spuId":"spu2", "store_spu_sku_join":{ "name":"spu", "parent":"s1" }}

PUT /store_spu_sku_index/store_spu_sku/spu3?routing=s2&refresh{ "spuName":"spu名称3-s2", "spuId":"spu3", "store_spu_sku_join":{ "name":"spu", "parent":"s2" }}

PUT /store_spu_sku_index/store_spu_sku/spu4?routing=s2&refresh{ "spuName":"spu名称4-s2", "spuId":"spu4", "store_spu_sku_join":{ "name":"spu", "parent":"s2" }}

（8）创建孙子文档

即SPU的子文档（SKU文档）

// 插入孙子文档PUT /store_spu_sku_index/store_spu_sku/sku1?routing=s1&refresh{ "skuName":"sku名称1-spu1", "skuId":"sku1", "store_spu_sku_join":{ "name":"sku", "parent":"spu1" }}

PUT /store_spu_sku_index/store_spu_sku/sku2?routing=s1&refresh{ "skuName":"sku名称2-spu1", "skuId":"sku2", "store_spu_sku_join":{ "name":"sku", "parent":"spu1" }}

PUT /store_spu_sku_index/store_spu_sku/sku3?routing=s1&refresh{ "skuName":"sku名称3-spu2", "skuId":"sku3", "store_spu_sku_join":{ "name":"sku", "parent":"spu2" }}

PUT /store_spu_sku_index/store_spu_sku/sku4?routing=s1&refresh{ "skuName":"sku名称4-spu2", "skuId":"sku4", "store_spu_sku_join":{ "name":"sku", "parent":"spu2" }}

PUT /store_spu_sku_index/store_spu_sku/sku5?routing=s2&refresh{ "skuName":"sku名称5-spu3", "skuId":"sku5", "store_spu_sku_join":{ "name":"sku", "parent":"spu3" }}

PUT /store_spu_sku_index/store_spu_sku/sku6?routing=s2&refresh{ "skuName":"sku名称6-spu3", "skuId":"sku6", "store_spu_sku_join":{ "name":"sku", "parent":"spu3" }}

PUT /store_spu_sku_index/store_spu_sku/sku7?routing=s2&refresh{ "skuName":"sku名称7-spu4", "skuId":"sku7", "store_spu_sku_join":{ "name":"sku", "parent":"spu4" }}

PUT /store_spu_sku_index/store_spu_sku/sku8?routing=s2&refresh{ "skuName":"sku名称8-spu4", "skuId":"sku8", "store_spu_sku_join":{ "name":"sku", "parent":"spu4" }}

注意：

  • 孙子文档 sku 所在分片必须与其父母 spu 和祖父母 store 相同
  • 孙子文档 sku 的父文档 id 必须指向其父亲 spu 文档

四、搜索实践

（1）父查子实践

// 父查子GET store_spu_sku_index/_search{ "query":{ "has_parent":{ "parent_type": "store", "query": { "match": { "storeId": "s1" } } } }}

// 执行结果{ "took": 3, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 2, "max_score": 1, "hits": [ { "_index": "store_spu_sku_index", "_type": "store_spu_sku", "_id": "spu2", "_score": 1, "_routing": "s1", "_source": { "spuName": "spu名称2-s1", "spuId": "spu2", "store_spu_sku_join": { "name": "spu", "parent": "s1" } } }, { "_index": "store_spu_sku_index", "_type": "store_spu_sku", "_id": "spu1", "_score": 1, "_routing": "s1", "_source": { "spuName": "spu名称1-s1", "spuId": "spu1", "store_spu_sku_join": { "name": "spu", "parent": "s1" } } } ] }}

（2）子查父实践

// 子查父GET store_spu_sku_index/_search{ "query":{ "has_child":{ "type": "spu", "query": { "match": { "spuName": "spu" } } } }}

（3）子查孙实践

// 子查孙GET store_spu_sku_index/_search{ "query":{ "has_parent":{ "parent_type": "spu", "query": { "match": { "spuId": "spu1" } } } }}

// 执行结果{ "took": 16, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 2, "max_score": 1, "hits": [ { "_index": "store_spu_sku_index", "_type": "store_spu_sku", "_id": "sku2", "_score": 1, "_routing": "s1", "_source": { "skuName": "sku名称2-spu1", "skuId": "sku2", "store_spu_sku_join": { "name": "sku", "parent": "spu1" } } }, { "_index": "store_spu_sku_index", "_type": "store_spu_sku", "_id": "sku1", "_score": 1, "_routing": "s1", "_source": { "skuName": "sku名称1-spu1", "skuId": "sku1", "store_spu_sku_join": { "name": "sku", "parent": "spu1" } } } ] }}

（4）子查孙加过滤条件实践

// 子查孙并过滤GET store_spu_sku_index/_search{"query": {"bool": {"should": {"has_parent": {"parent_type": "spu","query": {"match": {"spuId": "spu1"}}}},"filter": {"term": {"skuId": "sku1"}}}}}

// 执行结果{ "took": 28, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 1, "max_score": 1, "hits": [ { "_index": "store_spu_sku_index", "_type": "store_spu_sku", "_id": "sku1", "_score": 1, "_routing": "s1", "_source": { "skuName": "sku名称1-spu1", "skuId": "sku1", "store_spu_sku_join": { "name": "sku", "parent": "spu1" } } } ] }}

五、小结

通过以上实战演示，相信大家对 ES 父子文档有了一定初步的了解。继而在项目实践中，将一对多、一对多对多的关系按实际搜索场景应用并设计出合理的 ES 索引结构，以满足业务需求。

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