IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.

« Enrich your data Example: Enrich your data based on geolocation »

› › ›

Set up an enrich processor

edit

Set up an enrich processor

edit

To set up an enrich processor, follow these steps:

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

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.

Prerequisites

edit

If you use Elasticsearch security features, you must have:

read index privileges for any indices used
The enrich_user built-in role

Add enrich data

edit

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 Elasticsearch indices using the document and index APIs.

You also can set up Beats, such as a Filebeat, to automatically send and index documents to your source indices. See Getting started with Beats.

Create an enrich policy

edit

After adding enrich data to your source indices, use the create enrich policy API to create an enrich policy.

Once created, you can’t update or change an enrich policy. See Update an enrich policy.

Execute the enrich policy

edit

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

The enrich index contains documents from the policy’s source indices. Enrich indices always begin with .enrich-*, are read-only, and are force merged.

Enrich indices should be used by the enrich processor only. Avoid using enrich indices for other purposes.

Add an enrich processor to an ingest pipeline

edit

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.

Define an enrich processor and add it to an ingest pipeline using the 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 for a full list of configuration options.

You also can add other processors to your ingest pipeline.

Ingest and enrich documents

edit

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

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

Update an enrich index

edit

Once created, you cannot update or index documents to an enrich index. Instead, update your source indices and execute the enrich policy again. This creates a new enrich index from your updated source indices. The previous enrich index will deleted with a delayed maintenance job. By default this is done every 15 minutes.

If wanted, you can reindex or update any already ingested documents using your ingest pipeline.

Update an enrich policy

edit

Once created, you can’t update or change an enrich policy. Instead, you can:

Create and 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 to delete the previous enrich policy.

Enrich components

edit

The enrich coordinator is a component that manages and performs the searches required to enrich documents on each ingest node. It combines searches from all enrich processors in all pipelines into bulk multi-searches.

The enrich policy executor is a component that manages the executions of all enrich policies. When an enrich policy is executed, this component creates a new enrich index and removes the previous enrich index. The enrich policy executions are managed from the elected master node. The execution of these policies occurs on a different node.

Node Settings

edit

The enrich processor has node settings for enrich coordinator and enrich policy executor.

The enrich coordinator supports the following node settings:

enrich.cache_size: Maximum number of searches to cache for enriching documents. Defaults to 1000. There is a single cache for all enrich processors in the cluster. This setting determines the size of that cache.
enrich.coordinator_proxy.max_concurrent_requests: Maximum number of concurrent multi-search requests to run when enriching documents. Defaults to 8.
enrich.coordinator_proxy.max_lookups_per_request: Maximum number of searches to include in a multi-search request when enriching documents. Defaults to 128.

The enrich policy executor supports the following node settings:

enrich.fetch_size: Maximum batch size when reindexing a source index into an enrich index. Defaults to 10000.
enrich.max_force_merge_attempts: Maximum number of force merge attempts allowed on an enrich index. Defaults to 3.
enrich.cleanup_period: How often Elasticsearch checks whether unused enrich indices can be deleted. Defaults to 15m.
enrich.max_concurrent_policy_executions: Maximum number of enrich policies to execute concurrently. Defaults to 50.

« Enrich your data Example: Enrich your data based on geolocation »