Example: Enrich your data based on exact values

match enrich policies match enrich data to incoming documents based on an exact value, such as a email address or ID, using a term query.

The following example creates a match enrich policy that adds user name and contact information to incoming documents based on an email address. It then adds the match enrich policy to a processor in an ingest pipeline.

Use the create index API or index API to create a source index.

The following index API request creates a source index and indexes a new document to that index.

response = client.index(
  index: 'users',
  id: 1,
  refresh: 'wait_for',
  body: {
    email: 'mardy.brown@asciidocsmith.com',
    first_name: 'Mardy',
    last_name: 'Brown',
    city: 'New Orleans',
    county: 'Orleans',
    state: 'LA',
    zip: 70_116,
    web: 'mardy.asciidocsmith.com'
  }
)
puts response

PUT /users/_doc/1?refresh=wait_for
{
  "email": "mardy.brown@asciidocsmith.com",
  "first_name": "Mardy",
  "last_name": "Brown",
  "city": "New Orleans",
  "county": "Orleans",
  "state": "LA",
  "zip": 70116,
  "web": "mardy.asciidocsmith.com"
}

Use the create enrich policy API to create an enrich policy with the match policy type. This policy must include:

response = client.enrich.put_policy(
  name: 'users-policy',
  body: {
    match: {
      indices: 'users',
      match_field: 'email',
      enrich_fields: [
        'first_name',
        'last_name',
        'city',
        'zip',
        'state'
      ]
    }
  }
)
puts response

PUT /_enrich/policy/users-policy
{
  "match": {
    "indices": "users",
    "match_field": "email",
    "enrich_fields": ["first_name", "last_name", "city", "zip", "state"]
  }
}

Use the execute enrich policy API to create an enrich index for the policy.

POST /_enrich/policy/users-policy/_execute

Use the create or update pipeline API to create an ingest pipeline. In the pipeline, add an enrich processor that includes:

PUT /_ingest/pipeline/user_lookup
{
  "processors" : [
    {
      "enrich" : {
        "description": "Add 'user' data based on 'email'",
        "policy_name": "users-policy",
        "field" : "email",
        "target_field": "user",
        "max_matches": "1"
      }
    }
  ]
}

Use the ingest pipeline to index a document. The incoming document should include the field specified in your enrich processor.

PUT /my-index-000001/_doc/my_id?pipeline=user_lookup
{
  "email": "mardy.brown@asciidocsmith.com"
}

To verify the enrich processor matched and appended the appropriate field data, use the get API to view the indexed document.

response = client.get(
  index: 'my-index-000001',
  id: 'my_id'
)
puts response

GET /my-index-000001/_doc/my_id

The API returns the following response:

{
  "found": true,
  "_index": "my-index-000001",
  "_id": "my_id",
  "_version": 1,
  "_seq_no": 55,
  "_primary_term": 1,
  "_source": {
    "user": {
      "email": "mardy.brown@asciidocsmith.com",
      "first_name": "Mardy",
      "last_name": "Brown",
      "zip": 70116,
      "city": "New Orleans",
      "state": "LA"
    },
    "email": "mardy.brown@asciidocsmith.com"
  }
}