Getting ready

You need a working ElasticSearch cluster.

How to do it...

We can modify the order example indexing the items as separated child documents.

We need to extract the item object and create a new type document item with the _parent property set.

{
  "order": {
    "properties": {
      "id": {
        "type": "string",
        "store": "yes",
        "index": "not_analyzed"
      },
    "date": {
      "type": "date",
      "store": "no",
      "index": "not_analyzed"
    },
    "customer_id": {
      "type": "string",
      "store": "yes",
      "index": "not_analyzed"
    },
    "sent": {
      "type": "boolean",
      "store": "no",
      "index": "not_analyzed"
    }
  }
},
  "item": {
    "_parent": {
 "type": "order"
 },
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "store": "no",
      "index": "analyzed"
    },
  "quantity": {
    "type": "integer",
    "store": "no",
    "index": "not_analyzed"
  },
  "vat": {
    "type": "double",
    "store": "no",
    "index": "not_analyzed"
  }
  }
  }
}

The above mapping is similar to the ones in the previous recipe. The item object is extracted from the order (in the previous example it was nested) and added as a new mapping. The only difference is that "type": "nested" has become "type": "object" (it can be omitted), and the new special field, _parent that defines the parent/child relation.

How it works...

The child object is a standard root object (document) with an extra _parent property defined.

The type property of _parent refers to the type of the parent document.

The child document must be indexed in the same shard of parent, so that when indexed, an extra parameter must be passed: the parent ID. (We'll see how to do it in the next chapter.)

A child document doesn't require reindexing the parent document when we want to change its values. So it's fast in indexing, reindexing (updating), and deleting.

There's more...

In ElasticSearch we have different ways to manage relations between objects:

Choosing how to model the relation from objects depends on your application scenario.

Also, there is another approach that can be used, but on big data documents, bringing poor performances—its decoupling join relation. You do the join query in two steps: first you collect the ID of the children/other documents and then you search them in a field of their parent.

See also