610 lines
17 KiB
Plaintext
610 lines
17 KiB
Plaintext
[role="xpack"]
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[testenv="basic"]
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[[ingest-enriching-data]]
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== Enrich your data
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You can use the <<enrich-processor,enrich processor>> to add data from your
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existing indices to incoming documents during ingest.
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For example, you can use the enrich processor to:
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* Identify web services or vendors based on known IP addresses
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* Add product information to retail orders based on product IDs
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* Supplement contact information based on an email address
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* Add postal codes based on user coordinates
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[discrete]
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[[how-enrich-works]]
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=== How the enrich processor works
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An <<ingest,ingest pipeline>> changes documents before they are actually
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indexed. You can think of an ingest pipeline as an assembly line made up of a
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series of workers, called <<ingest-processors,processors>>. Each processor makes
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specific changes, like lowercasing field values, to incoming documents before
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moving on to the next. When all the processors in a pipeline are done, the
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finished document is added to the target index.
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image::images/ingest/ingest-process.svg[align="center"]
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Most processors are self-contained and only change _existing_ data in incoming
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documents. But the enrich processor adds _new_ data to incoming documents
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and requires a few special components:
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image::images/ingest/enrich/enrich-process.svg[align="center"]
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[[enrich-policy]]
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enrich policy::
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+
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--
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A set of configuration options used to add the right enrich data to the right
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incoming documents.
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An enrich policy contains:
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// tag::enrich-policy-fields[]
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* A list of one or more _source indices_ which store enrich data as documents
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* The _policy type_ which determines how the processor matches the enrich data
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to incoming documents
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* A _match field_ from the source indices used to match incoming documents
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* _Enrich fields_ containing enrich data from the source indices you want to add
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to incoming documents
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// end::enrich-policy-fields[]
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Before it can be used with an enrich processor, an enrich policy must be
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<<execute-enrich-policy-api,executed>>. When executed, an enrich policy uses
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enrich data from the policy's source indices to create a streamlined system
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index called the _enrich index_. The processor uses this index to match and
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enrich incoming documents.
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See <<enrich-policy-definition>> for a full list of enrich policy types and
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configuration options.
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--
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[[source-index]]
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source index::
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An index which stores enrich data you'd like to add to incoming documents. You
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can create and manage these indices just like a regular {es} index. You can use
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multiple source indices in an enrich policy. You also can use the same source
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index in multiple enrich policies.
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[[enrich-index]]
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enrich index::
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+
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--
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A special system index tied to a specific enrich policy.
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Directly matching incoming documents to documents in source indices could be
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slow and resource intensive. To speed things up, the enrich processor uses an
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enrich index.
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Enrich indices contain enrich data from source indices but have a few special
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properties to help streamline them:
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* They are system indices, meaning they're managed internally by {es} and only
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intended for use with enrich processors.
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* They always begin with `.enrich-*`.
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* They are read-only, meaning you can't directly change them.
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* They are <<indices-forcemerge,force merged>> for fast retrieval.
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--
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[role="xpack"]
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[testenv="basic"]
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[[enrich-setup]]
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=== Set up an enrich processor
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To set up an enrich processor, follow these steps:
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. Check the <<enrich-prereqs, prerequisites>>.
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. <<create-enrich-source-index>>.
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. <<create-enrich-policy>>.
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. <<execute-enrich-policy>>.
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. <<add-enrich-processor>>.
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. <<ingest-enrich-docs>>.
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Once you have an enrich processor set up,
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you can <<update-enrich-data,update your enrich data>>
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and <<update-enrich-policies, update your enrich policies>>.
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[IMPORTANT]
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====
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The enrich processor performs several operations
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and may impact the speed of your <<pipeline,ingest pipeline>>.
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We strongly recommend testing and benchmarking your enrich processors
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before deploying them in production.
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We do not recommend using the enrich processor to append real-time data.
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The enrich processor works best with reference data
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that doesn't change frequently.
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====
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[float]
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[[enrich-prereqs]]
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==== Prerequisites
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include::{docdir}/ingest/apis/enrich/put-enrich-policy.asciidoc[tag=enrich-policy-api-prereqs]
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[[create-enrich-source-index]]
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==== Add enrich data
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To begin, add documents to one or more source indices. These documents should
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contain the enrich data you eventually want to add to incoming documents.
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You can manage source indices just like regular {es} indices using the
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<<docs,document>> and <<indices,index>> APIs.
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You also can set up {beats-ref}/getting-started.html[{beats}], such as a
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{filebeat-ref}/filebeat-getting-started.html[{filebeat}], to automatically send
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and index documents to your source indices. See
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{beats-ref}/getting-started.html[Getting started with {beats}].
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[[create-enrich-policy]]
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==== Create an enrich policy
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After adding enrich data to your source indices, you can
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<<enrich-policy-definition,define an enrich policy>>. When defining the enrich
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policy, you should include at least the following:
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include::enrich.asciidoc[tag=enrich-policy-fields]
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You can use this definition to create the enrich policy with the
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<<put-enrich-policy-api,put enrich policy API>>.
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include::apis/enrich/put-enrich-policy.asciidoc[tag=update-enrich-policy]
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[[execute-enrich-policy]]
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==== Execute the enrich policy
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Once the enrich policy is created, you can execute it using the
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<<execute-enrich-policy-api,execute enrich policy API>> to create an
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<<enrich-index,enrich index>>.
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image::images/ingest/enrich/enrich-policy-index.svg[align="center"]
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include::apis/enrich/execute-enrich-policy.asciidoc[tag=execute-enrich-policy-def]
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[[add-enrich-processor]]
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==== Add an enrich processor to an ingest pipeline
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Once you have source indices, an enrich policy, and the related enrich index in
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place, you can set up an ingest pipeline that includes an enrich processor for
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your policy.
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image::images/ingest/enrich/enrich-processor.svg[align="center"]
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Define an <<enrich-processor,enrich processor>> and add it to an ingest
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pipeline using the <<put-pipeline-api,put pipeline API>>.
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When defining the enrich processor, you must include at least the following:
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* The enrich policy to use.
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* The field used to match incoming documents to the documents in your enrich index.
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* The target field to add to incoming documents. This target field contains the
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match and enrich fields specified in your enrich policy.
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You also can use the `max_matches` option to set the number of enrich documents
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an incoming document can match. If set to the default of `1`, data is added to
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an incoming document's target field as a JSON object. Otherwise, the data is
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added as an array.
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See <<enrich-processor>> for a full list of configuration options.
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You also can add other <<ingest-processors,processors>> to your ingest pipeline.
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[[ingest-enrich-docs]]
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==== Ingest and enrich documents
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You can now use your ingest pipeline to enrich and index documents.
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image::images/ingest/enrich/enrich-process.svg[align="center"]
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Before implementing the pipeline in production, we recommend indexing a few test
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documents first and verifying enrich data was added correctly using the
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<<docs-get,get API>>.
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[[update-enrich-data]]
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==== Update an enrich index
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include::{docdir}/ingest/apis/enrich/execute-enrich-policy.asciidoc[tag=update-enrich-index]
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If wanted, you can <<docs-reindex,reindex>>
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or <<docs-update-by-query,update>> any already ingested documents
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using your ingest pipeline.
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[[update-enrich-policies]]
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==== Update an enrich policy
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include::apis/enrich/put-enrich-policy.asciidoc[tag=update-enrich-policy]
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[role="xpack"]
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[testenv="basic"]
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[[enrich-policy-definition]]
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=== Enrich policy definition
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<<enrich-policy,Enrich policies>> are defined as JSON objects like the
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following:
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[source,js]
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----
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{
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"<enrich_policy_type>": {
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"indices": ["..."],
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"match_field": "...",
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"enrich_fields": ["..."],
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"query": "..."
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}
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}
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}
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----
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// NOTCONSOLE
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[[enrich-policy-parms]]
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==== Parameters
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`<enrich_policy_type>`::
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+
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--
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(Required, enrich policy object)
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The enrich policy type determines how enrich data is matched to incoming
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documents.
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Supported enrich policy types include:
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<<geo-match-enrich-policy-type,`geo_match`>>:::
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Matches enrich data to incoming documents based on a geographic location using
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a <<query-dsl-geo-shape-query,`geo_shape` query>>. For an example, see
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<<geo-match-enrich-policy-type>>.
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<<match-enrich-policy-type,`match`>>:::
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Matches enrich data to incoming documents based on a precise value, such as an
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email address or ID, using a <<query-dsl-term-query,`term` query>>. For an
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example, see <<match-enrich-policy-type>>.
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--
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`indices`::
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+
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--
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(Required, String or array of strings)
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Source indices used to create the enrich index.
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If multiple indices are provided, they must share a common `match_field`, which
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the enrich processor can use to match incoming documents.
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--
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`match_field`::
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(Required, string)
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Field in the source indices used to match incoming documents.
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`enrich_fields`::
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(Required, Array of strings)
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Fields to add to matching incoming documents. These fields must be present in
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the source indices.
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`query`::
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(Optional, string)
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Query type used to filter documents in the enrich index for matching. Valid
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value is <<query-dsl-match-all-query,`match_all`>> (default).
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[role="xpack"]
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[testenv="basic"]
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[[geo-match-enrich-policy-type]]
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=== Example: Enrich your data based on geolocation
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`geo_match` <<enrich-policy,enrich policies>> match enrich data to incoming
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documents based on a geographic location, using a
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<<query-dsl-geo-shape-query,`geo_shape` query>>.
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The following example creates a `geo_match` enrich policy that adds postal
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codes to incoming documents based on a set of coordinates. It then adds the
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`geo_match` enrich policy to a processor in an ingest pipeline.
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Use the <<indices-create-index,create index API>> to create a source index
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containing at least one `geo_shape` field.
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[source,console]
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----
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PUT /postal_codes
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{
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"mappings": {
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"properties": {
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"location": {
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"type": "geo_shape"
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},
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"postal_code": {
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"type": "keyword"
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}
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}
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}
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}
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----
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Use the <<docs-index_,index API>> to index enrich data to this source index.
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[source,console]
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----
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PUT /postal_codes/_doc/1?refresh=wait_for
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{
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"location": {
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"type": "envelope",
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"coordinates": [[13.0, 53.0], [14.0, 52.0]]
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},
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"postal_code": "96598"
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}
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----
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// TEST[continued]
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Use the <<put-enrich-policy-api,put enrich policy API>> to create an enrich
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policy with the `geo_match` policy type. This policy must include:
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* One or more source indices
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* A `match_field`,
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the `geo_shape` field from the source indices used to match incoming documents
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* Enrich fields from the source indices you'd like to append to incoming
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documents
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[source,console]
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----
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PUT /_enrich/policy/postal_policy
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{
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"geo_match": {
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"indices": "postal_codes",
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"match_field": "location",
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"enrich_fields": ["location","postal_code"]
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}
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}
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----
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// TEST[continued]
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Use the <<execute-enrich-policy-api,execute enrich policy API>> to create an
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enrich index for the policy.
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[source,console]
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----
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POST /_enrich/policy/postal_policy/_execute
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----
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// TEST[continued]
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Use the <<put-pipeline-api,put pipeline API>> to create an ingest pipeline. In
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the pipeline, add an <<enrich-processor,enrich processor>> that includes:
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* Your enrich policy.
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* The `field` of incoming documents used to match the geo_shape of documents
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from the enrich index.
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* The `target_field` used to store appended enrich data for incoming documents.
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This field contains the `match_field` and `enrich_fields` specified in your
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enrich policy.
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* The `shape_relation`, which indicates how the processor matches geo_shapes in
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incoming documents to geo_shapes in documents from the enrich index. See
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<<_spatial_relations>> for valid options and more information.
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[source,console]
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----
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PUT /_ingest/pipeline/postal_lookup
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{
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"description": "Enrich postal codes",
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"processors": [
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{
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"enrich": {
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"policy_name": "postal_policy",
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"field": "geo_location",
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"target_field": "geo_data",
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"shape_relation": "INTERSECTS"
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}
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}
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]
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}
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----
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// TEST[continued]
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Use the ingest pipeline to index a document. The incoming document should
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include the `field` specified in your enrich processor.
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[source,console]
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----
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PUT /users/_doc/0?pipeline=postal_lookup
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{
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"first_name": "Mardy",
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"last_name": "Brown",
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"geo_location": "POINT (13.5 52.5)"
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}
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----
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// TEST[continued]
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To verify the enrich processor matched and appended the appropriate field data,
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use the <<docs-get,get API>> to view the indexed document.
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[source,console]
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----
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GET /users/_doc/0
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----
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// TEST[continued]
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The API returns the following response:
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[source,console-result]
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----
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{
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"found": true,
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"_index": "users",
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"_type": "_doc",
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"_id": "0",
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"_version": 1,
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"_seq_no": 55,
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"_primary_term": 1,
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"_source": {
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"geo_data": {
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"location": {
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"type": "envelope",
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"coordinates": [[13.0, 53.0], [14.0, 52.0]]
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},
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"postal_code": "96598"
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},
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"first_name": "Mardy",
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"last_name": "Brown",
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"geo_location": "POINT (13.5 52.5)"
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}
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}
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----
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// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term":1/"_primary_term" : $body._primary_term/]
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////
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[source,console]
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--------------------------------------------------
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DELETE /_ingest/pipeline/postal_lookup
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DELETE /_enrich/policy/postal_policy
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--------------------------------------------------
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// TEST[continued]
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////
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[role="xpack"]
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[testenv="basic"]
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[[match-enrich-policy-type]]
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=== Example: Enrich your data based on exact values
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`match` <<enrich-policy,enrich policies>> match enrich data to incoming
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documents based on an exact value, such as a email address or ID, using a
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<<query-dsl-term-query,`term` query>>.
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The following example creates a `match` enrich policy that adds user name and
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contact information to incoming documents based on an email address. It then
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adds the `match` enrich policy to a processor in an ingest pipeline.
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Use the <<indices-create-index, create index API>> or <<docs-index_,index
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API>> to create a source index.
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The following index API request creates a source index and indexes a
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new document to that index.
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[source,console]
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----
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PUT /users/_doc/1?refresh=wait_for
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{
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"email": "mardy.brown@asciidocsmith.com",
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"first_name": "Mardy",
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"last_name": "Brown",
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"city": "New Orleans",
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"county": "Orleans",
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"state": "LA",
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"zip": 70116,
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"web": "mardy.asciidocsmith.com"
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}
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----
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Use the put enrich policy API to create an enrich policy with the `match`
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policy type. This policy must include:
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* One or more source indices
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* A `match_field`,
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the field from the source indices used to match incoming documents
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* Enrich fields from the source indices you'd like to append to incoming
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documents
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[source,console]
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----
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PUT /_enrich/policy/users-policy
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{
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"match": {
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"indices": "users",
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"match_field": "email",
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"enrich_fields": ["first_name", "last_name", "city", "zip", "state"]
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}
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}
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----
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// TEST[continued]
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Use the <<execute-enrich-policy-api,execute enrich policy API>> to create an
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enrich index for the policy.
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[source,console]
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----
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POST /_enrich/policy/users-policy/_execute
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----
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// TEST[continued]
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|
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Use the <<put-pipeline-api,put pipeline API>> to create an ingest pipeline. In
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the pipeline, add an <<enrich-processor,enrich processor>> that includes:
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* Your enrich policy.
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* The `field` of incoming documents used to match documents
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from the enrich index.
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* The `target_field` used to store appended enrich data for incoming documents.
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This field contains the `match_field` and `enrich_fields` specified in your
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enrich policy.
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[source,console]
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----
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PUT /_ingest/pipeline/user_lookup
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{
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"description" : "Enriching user details to messages",
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"processors" : [
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{
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"enrich" : {
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"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/_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/_doc/my_id
|
|
----
|
|
// TEST[continued]
|
|
|
|
The API returns the following response:
|
|
|
|
[source,console-result]
|
|
----
|
|
{
|
|
"found": true,
|
|
"_index": "my_index",
|
|
"_type": "_doc",
|
|
"_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]
|
|
////
|