那是一个很好的开始！
我一定会把所有内容弄平（例如，反规范化），并拿出如下产品文档。这样，您只需flags为每个产品创建一个数组即可摆脱产品和标志之间的N：M关系。因此，查询这些标志将更加容易。
{
"id": "00c8234d71c4e94f725cd432ebc04",
"title": "Alpha",
"price": 589.0,
"flags": ["Sellout", "Top Product"]
}
{
"id": "018357657529fef056cf396626812",
"title": "Beta",
"price": 355.0,
"flags": ["Discount"]
}
{
"id": "01a2c32ceeff0fc6b7dd4fc4302ab",
"title": "Gamma",
"price": 0.0,
"flags": ["Discount"]
}
产品映射类型如下所示：
PUT products
{
"mappings": {
"product": {
"properties": {
"id": {
"type": "string",
"index": "not_analyzed"
},
"title": {
"type": "string"
},
"price": {
"type": "double",
"null_value": 0.0
},
"flags": {
"type": "string",
"index": "not_analyzed"
}
}
}
}
}
由于已经有logstash jdbc输入，因此您所缺少的只是用于提取产品和相关标志的正确SQL查询。
SELECT p.Id as id, p.Title as title, p.Price as price, GROUP_CONCAT(f.Title) as flags
FROM Products p
JOIN flagsProducts fp ON fp.ProductId = p.Id
JOIN Flags f ON fp.FlagId = f.id
GROUP BY p.Id
这将使您像这样的行：
+-------------------------------+-------+-------+---------------------+
| id | title | price | flags |
+-------------------------------+-------+-------+---------------------+
| 00c8234d71c4e94f725cd432ebc04 | Alpha | 589 | Sellout,Top product |
| 018357657529fef056cf396626812 | Beta | 355 | Discount |
| 01a2c32ceeff0fc6b7dd4fc4302ab | Gamma | 0 | Discount |
+-------------------------------+-------+-------+---------------------+
然后，您可以使用Logstash过滤器将拆分flags为一个数组，然后开始使用。
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