是否有与Elasticsearch中的联接类似的查询? [英] Is there a query similar to joins in Elasticsearch?

问题描述

我知道在Elasticsearch中使用"JOIN"效率不高，但是我需要使用它. 我必须通过找到索引A和索引B的相同字段来提取值. 下面有一个例子.

I know its not efficient to use "JOIN" in Elasticsearch, but I need to use it. I have to extract values by find same field of index A and index B. there is an example below.

A/type1/1
{
"serial":"abc",
"member":"jack"
}

A/type1/2
{
"serial":"def",
"member":"jack"
}

B/type2/1
{
"serial":"abc",
"temp":1
}

B/type3/2
{
"serial":"abc",
"water":0
}

B/type2/3
{
"serial":"def",
"temp":10
}

我需要过滤A索引的'member'字段的值以找到对应的serial，然后我想获取B中temp和water字段的值指数. 例如)过滤器:{member:jack} ===> temp:1, water:0, temp:10

I need to filter the value of the ‘member’ field of the A index to find the corresponding serial, and then I want to get the values ​​of the temp and water fields in the B index. ex) filter: {"member":"jack"} ===> temp:1, water:0, temp:10

我想知道是否可以得到这个结果，如果可以的话，如何建立数据结构(索引结构).

I wonder if I can get this result, and if so, how do i establish the data structure (index structure).

推荐答案

如果可能的话，您绝对应该执行注释者Val的建议，对数据进行非规范化(扁平化).我建议，例如，您可以使用这样的文档(基本上，在索引之前进行连接 之前):

You should definitely do what the commenter Val suggests, denormalize (flatten) your data, if it is at all possible. I would suggest, for example, you could use documents like this (basically, do the join before indexing):

B/type2/1 {"serial": "abc", "temp": 1, "member": "jack"}
B/type2/2 {"serial": "abc", "water": 0, "member": "jack"}
B/type2/3 {"serial": "def", "temp": 10, "member": "jack"}

然后，如果您搜索{"match": {"member": "jack"}}，则将获得所有这些文档.在Elasticsearch中，有两种方法可以完成类似"joins"的操作，嵌套对象.这是如何使用嵌套对象创建映射的示例:

Then if you search {"match": {"member": "jack"}}, you'll get all those documents. There are two ways of doing something like "joins" in Elasticsearch, parent-child relationships and nested objects. Here's the example of how you could create your mapping with nested objects:

{
  "type1": {
    "properties": {
      "serial": {"type": "keyword"},
      "member": {"type": "keyword"},
      "type2s": {
        "type": "nested",
        "properties": {
          "temp": {"type": "integer"},
          "water": {"type": "integer"}
        }
      }
    }
  }
}

然后，您将存储如下记录:

Then you would store a record like this:

{
  "serial": "abc",
  "member": "jack",
  "type2s": [
    {
      "temp": 1
    },
    {
      "water": 0
    }
  }
}

但是，我强烈敦促您不要这样做，除非您绝对必须这样做！一个好主意的用例很少见.它使查询数据变得更加复杂，并且效率低下(因此，随着数据规模的扩大，您将更快地遇到问题).

However, I would strongly urge you not to do this unless you absolutely have to! Use cases where this is a good idea are rare. It makes querying your data more complex, and it's inefficient (so as your data scales, you are going to have issues much sooner).

我知道复制"数据感觉不对.在关系数据库中，这将是一个可怕的实践.为了在Elasticsearch中进行有效的数据建模，您实际上必须开发一种不同的思维方式，其中的区别之一是您不必为复制数据而过分担心.

I know it feels wrong to "duplicate" data. It would be a terrible practice in a relational database. You really have to develop a different way of thinking, for effective and efficient data modeling in Elasticsearch, and one of the differences is that you shouldn't worry too much about duplicating data.

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