elasticsearch/docs/reference/ingest/enrich.asciidoc

[role="xpack"]
[testenv="basic"]
[[ingest-enriching-data]]
== Enrich your data

You can use the <<enrich-processor,enrich processor>> to add data from your
existing indices to incoming documents during ingest.

For example, you can use the enrich processor to:

* Identify web services or vendors based on known IP addresses
* Add product information to retail orders based on product IDs
* Supplement contact information based on an email address
* Add postal codes based on user coordinates

[discrete]
[[how-enrich-works]]
=== How the enrich processor works

Most processors are self-contained and only change _existing_ data in incoming
documents.

image::images/ingest/ingest-process.svg[align="center"]

The enrich processor adds _new_ data to incoming documents and requires a few
special components:

image::images/ingest/enrich/enrich-process.svg[align="center"]

[[enrich-policy]]
enrich policy::
+
--
A set of configuration options used to add the right enrich data to the right
incoming documents.

An enrich policy contains:

// tag::enrich-policy-fields[]
* A list of one or more _source indices_ which store enrich data as documents
* The _policy type_ which determines how the processor matches the enrich data
  to incoming documents
* A _match field_ from the source indices used to match incoming documents
* _Enrich fields_ containing enrich data from the source indices you want to add
  to incoming documents
// end::enrich-policy-fields[]

Before it can be used with an enrich processor, an enrich policy must be
<<execute-enrich-policy-api,executed>>. When executed, an enrich policy uses
enrich data from the policy's source indices to create a streamlined system
index called the _enrich index_. The processor uses this index to match and
enrich incoming documents.
--

[[source-index]]
source index::
An index which stores enrich data you'd like to add to incoming documents. You
can create and manage these indices just like a regular {es} index. You can use
multiple source indices in an enrich policy. You also can use the same source
index in multiple enrich policies.

[[enrich-index]]
enrich index::
+
--
A special system index tied to a specific enrich policy.

Directly matching incoming documents to documents in source indices could be
slow and resource intensive. To speed things up, the enrich processor uses an
enrich index.

Enrich indices contain enrich data from source indices but have a few special
properties to help streamline them:

* They are system indices, meaning they're managed internally by {es} and only
  intended for use with enrich processors.
* They always begin with `.enrich-*`.
* They are read-only, meaning you can't directly change them.
* They are <<indices-forcemerge,force merged>> for fast retrieval.
--

[role="xpack"]
[testenv="basic"]
[[enrich-setup]]
=== Set up an enrich processor

To set up an enrich processor, follow these steps:

. Check the <<enrich-prereqs, prerequisites>>.
. <<create-enrich-source-index>>.
. <<create-enrich-policy>>.
. <<execute-enrich-policy>>.
. <<add-enrich-processor>>.
. <<ingest-enrich-docs>>.

Once you have an enrich processor set up,
you can <<update-enrich-data,update your enrich data>>
and <<update-enrich-policies, update your enrich policies>>.

[IMPORTANT]
====
The enrich processor performs several operations and may impact the speed of
your ingest pipeline.

We strongly recommend testing and benchmarking your enrich processors
before deploying them in production.

We do not recommend using the enrich processor to append real-time data.
The enrich processor works best with reference data
that doesn't change frequently.
====

[discrete]
[[enrich-prereqs]]
==== Prerequisites

include::{es-repo-dir}/ingest/apis/enrich/put-enrich-policy.asciidoc[tag=enrich-policy-api-prereqs]

[[create-enrich-source-index]]
==== Add enrich data

To begin, add documents to one or more source indices. These documents should
contain the enrich data you eventually want to add to incoming documents.

You can manage source indices just like regular {es} indices using the
<<docs,document>> and <<indices,index>> APIs.

You also can set up {beats-ref}/getting-started.html[{beats}], such as a
{filebeat-ref}/filebeat-installation-configuration.html[{filebeat}], to
automatically send and index documents to your source indices. See
{beats-ref}/getting-started.html[Getting started with {beats}].

[[create-enrich-policy]]
==== Create an enrich policy

After adding enrich data to your source indices, use the
<<put-enrich-policy-api,create enrich policy API>> to create an enrich policy.

[WARNING]
====
Once created, you can't update or change an enrich policy.
See <<update-enrich-policies>>.
====

[[execute-enrich-policy]]
==== Execute the enrich policy

Once the enrich policy is created, you can execute it using the
<<execute-enrich-policy-api,execute enrich policy API>> to create an
<<enrich-index,enrich index>>.

image::images/ingest/enrich/enrich-policy-index.svg[align="center"]

include::apis/enrich/execute-enrich-policy.asciidoc[tag=execute-enrich-policy-def]

[[add-enrich-processor]]
==== Add an enrich processor to an ingest pipeline

Once you have source indices, an enrich policy, and the related enrich index in
place, you can set up an ingest pipeline that includes an enrich processor for
your policy.

image::images/ingest/enrich/enrich-processor.svg[align="center"]

Define an <<enrich-processor,enrich processor>> and add it to an ingest
pipeline using the <<put-pipeline-api,create or update pipeline API>>.

When defining the enrich processor, you must include at least the following:

* The enrich policy to use.
* The field used to match incoming documents to the documents in your enrich index.
* The target field to add to incoming documents. This target field contains the
match and enrich fields specified in your enrich policy.

You also can use the `max_matches` option to set the number of enrich documents
an incoming document can match. If set to the default of `1`, data is added to
an incoming document's target field as a JSON object. Otherwise, the data is
added as an array.

See <<enrich-processor>> for a full list of configuration options.

You also can add other <<processors,processors>> to your ingest pipeline.

[[ingest-enrich-docs]]
==== Ingest and enrich documents

You can now use your ingest pipeline to enrich and index documents.

image::images/ingest/enrich/enrich-process.svg[align="center"]

Before implementing the pipeline in production, we recommend indexing a few test
documents first and verifying enrich data was added correctly using the
<<docs-get,get API>>.

[[update-enrich-data]]
==== Update an enrich index

include::{es-repo-dir}/ingest/apis/enrich/execute-enrich-policy.asciidoc[tag=update-enrich-index]

If wanted, you can <<docs-reindex,reindex>>
or <<docs-update-by-query,update>> any already ingested documents
using your ingest pipeline.

[[update-enrich-policies]]
==== Update an enrich policy

// tag::update-enrich-policy[]
Once created, you can't update or change an enrich policy.
Instead, you can:

.   Create and <<execute-enrich-policy-api,execute>> a new enrich policy.

.   Replace the previous enrich policy
    with the new enrich policy
    in any in-use enrich processors.

.   Use the <<delete-enrich-policy-api, delete enrich policy>> API
    to delete the previous enrich policy.
// end::update-enrich-policy[]

[role="xpack"]
[testenv="basic"]
[[geo-match-enrich-policy-type]]
=== Example: Enrich your data based on geolocation

`geo_match` <<enrich-policy,enrich policies>> match enrich data to incoming
documents based on a geographic location, using a
<<query-dsl-geo-shape-query,`geo_shape` query>>.

The following example creates a `geo_match` enrich policy that adds postal
codes to incoming documents based on a set of coordinates. It then adds the
`geo_match` enrich policy to a processor in an ingest pipeline.

Use the <<indices-create-index,create index API>> to create a source index
containing at least one `geo_shape` field.

[source,console]
----
PUT /postal_codes
{
  "mappings": {
    "properties": {
      "location": {
        "type": "geo_shape"
      },
      "postal_code": {
        "type": "keyword"
      }
    }
  }
}
----

Use the <<docs-index_,index API>> to index enrich data to this source index.

[source,console]
----
PUT /postal_codes/_doc/1?refresh=wait_for
{
  "location": {
    "type": "envelope",
    "coordinates": [ [ 13.0, 53.0 ], [ 14.0, 52.0 ] ]
  },
  "postal_code": "96598"
}
----
// TEST[continued]

Use the <<put-enrich-policy-api,create or update enrich policy API>> to create
an enrich policy with the `geo_match` policy type. This policy must include:

* One or more source indices
* A `match_field`,
  the `geo_shape` field from the source indices used to match incoming documents
* Enrich fields from the source indices you'd like to append to incoming
  documents

[source,console]
----
PUT /_enrich/policy/postal_policy
{
  "geo_match": {
    "indices": "postal_codes",
    "match_field": "location",
    "enrich_fields": [ "location", "postal_code" ]
  }
}
----
// TEST[continued]

Use the <<execute-enrich-policy-api,execute enrich policy API>> to create an
enrich index for the policy.

[source,console]
----
POST /_enrich/policy/postal_policy/_execute
----
// TEST[continued]

Use the <<put-pipeline-api,create or update pipeline API>> to create an ingest
pipeline. In the pipeline, add an <<enrich-processor,enrich processor>> that
includes:

* Your enrich policy.
* The `field` of incoming documents used to match the geo_shape of documents
  from the enrich index.
* The `target_field` used to store appended enrich data for incoming documents.
  This field contains the `match_field` and `enrich_fields` specified in your
  enrich policy.
* The `shape_relation`, which indicates how the processor matches geo_shapes in
  incoming documents to geo_shapes in documents from the enrich index. See
  <<_spatial_relations>> for valid options and more information.

[source,console]
----
PUT /_ingest/pipeline/postal_lookup
{
  "processors": [
    {
      "enrich": {
        "description": "Add 'geo_data' based on 'geo_location'",
        "policy_name": "postal_policy",
        "field": "geo_location",
        "target_field": "geo_data",
        "shape_relation": "INTERSECTS"
      }
    }
  ]
}
----
// TEST[continued]

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

[source,console]
----
PUT /users/_doc/0?pipeline=postal_lookup
{
  "first_name": "Mardy",
  "last_name": "Brown",
  "geo_location": "POINT (13.5 52.5)"
}
----
// TEST[continued]

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

[source,console]
----
GET /users/_doc/0
----
// TEST[continued]

The API returns the following response:

[source,console-result]
----
{
  "found": true,
  "_index": "users",
  "_id": "0",
  "_version": 1,
  "_seq_no": 55,
  "_primary_term": 1,
  "_source": {
    "geo_data": {
      "location": {
        "type": "envelope",
        "coordinates": [[13.0, 53.0], [14.0, 52.0]]
      },
      "postal_code": "96598"
    },
    "first_name": "Mardy",
    "last_name": "Brown",
    "geo_location": "POINT (13.5 52.5)"
  }
}
----
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term":1/"_primary_term" : $body._primary_term/]

////
[source,console]
--------------------------------------------------
DELETE /_ingest/pipeline/postal_lookup
DELETE /_enrich/policy/postal_policy
--------------------------------------------------
// TEST[continued]
////

[role="xpack"]
[testenv="basic"]
[[match-enrich-policy-type]]
=== Example: Enrich your data based on exact values

`match` <<enrich-policy,enrich policies>> match enrich data to incoming
documents based on an exact value, such as a email address or ID, using a
<<query-dsl-term-query,`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 <<indices-create-index, create index API>> or <<docs-index_,index
API>> to create a source index.

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

[source,console]
----
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 or update enrich policy API to create an enrich policy with the
`match` policy type. This policy must include:

* One or more source indices
* A `match_field`,
  the field from the source indices used to match incoming documents
* Enrich fields from the source indices you'd like to append to incoming
  documents

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

Use the <<execute-enrich-policy-api,execute enrich policy API>> to create an
enrich index for the policy.

[source,console]
----
POST /_enrich/policy/users-policy/_execute
----
// TEST[continued]


Use the <<put-pipeline-api,create or update pipeline API>> to create an ingest
pipeline. In the pipeline, add an <<enrich-processor,enrich processor>> that
includes:

* Your enrich policy.
* The `field` of incoming documents used to match documents
  from the enrich index.
* The `target_field` used to store appended enrich data for incoming documents.
  This field contains the `match_field` and `enrich_fields` specified in your
  enrich policy.

[source,console]
----
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"
      }
    }
  ]
}
----
// TEST[continued]

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

[source,console]
----
PUT /my-index-000001/_doc/my_id?pipeline=user_lookup
{
  "email": "mardy.brown@asciidocsmith.com"
}
----
// TEST[continued]

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

[source,console]
----
GET /my-index-000001/_doc/my_id
----
// TEST[continued]

The API returns the following response:

[source,console-result]
----
{
  "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"
  }
}
----
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term":1/"_primary_term" : $body._primary_term/]

////
[source,console]
--------------------------------------------------
DELETE /_ingest/pipeline/user_lookup
DELETE /_enrich/policy/users-policy
--------------------------------------------------
// TEST[continued]
////