PUT _transform/<transform_id>

If the Elasticsearch security features are enabled, you must have the following built-in roles and privileges:

For more information, see Security privileges and Built-in roles.

This API defines a transform, which copies data from source indices, transforms it, and persists it into an entity-centric destination index. The entities are defined by the set of group_by fields in the pivot object. You can also think of the destination index as a two-dimensional tabular data structure (known as a data frame). The ID for each document in the data frame is generated from a hash of the entity, so there is a unique row per entity. For more information, see Transforming data.

When the transform is created, a series of validations occur to ensure its success. For example, there is a check for the existence of the source indices and a check that the destination index is not part of the source index pattern. You can use the defer_validation parameter to skip these checks.

Deferred validations are always run when the transform is started, with the exception of privilege checks. When Elasticsearch security features are enabled, the transform remembers which roles the user that created it had at the time of creation and uses those same roles. If those roles do not have the required privileges on the source and destination indices, the transform fails when it attempts unauthorized operations.

PUT _transform/ecommerce_transform
{
  "source": {
    "index": "kibana_sample_data_ecommerce",
    "query": {
      "term": {
        "geoip.continent_name": {
          "value": "Asia"
        }
      }
    }
  },
  "pivot": {
    "group_by": {
      "customer_id": {
        "terms": {
          "field": "customer_id"
        }
      }
    },
    "aggregations": {
      "max_price": {
        "max": {
          "field": "taxful_total_price"
        }
      }
    }
  },
  "description": "Maximum priced ecommerce data by customer_id in Asia",
  "dest": {
    "index": "kibana_sample_data_ecommerce_transform",
    "pipeline": "add_timestamp_pipeline"
  },
  "frequency": "5m",
  "sync": {
    "time": {
      "field": "order_date",
      "delay": "60s"
    }
  }
}

When the transform is created, you receive the following results:

{
  "acknowledged" : true
}