How to Index String Fields For Faceted Search
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You can use the Atlas Search stringFacet type to index string fields for faceting, which allows you
to run a facet query on that field. Atlas Search doesn't apply the analyzer
when indexing string fields for faceting.
Atlas Search only supports facet queries against fields
indexed as the stringFacet type. To perform a normal search also
on the same field, you must index the field as type string also.
To facet on string fields in embedded documents, you must index the parent fields as the document type. When you facet on a string field inside embedded documents, Atlas Search returns facet count for only the number of matching parent documents.
Atlas Search doesn't dynamically index
string values for faceting. You must use static
mappings to index string values for
faceting. You can use the Visual Editor or the JSON Editor in
the Atlas UI to index string fields as the number type.
Define the Index for the stringFacet Type
To define the index for the stringFacet type, choose your preferred
configuration method in the Atlas UI and then select the
database and collection.
Click Refine Your Index to configure your index.
In the Field Mappings section, click Add Field Mapping to open the Add Field Mapping window.
Click Customized Configuration.
Select the field to index from the Field Name dropdown.
Note
You can't index fields that contain the dollar (
$) sign at the start of the field name.Click the Data Type dropdown and select StringFacet. To learn more more about this type, see Field Properties.
Click Add.
The following is the JSON syntax for the stringFacet type.
Replace the default index definition with the following. To learn more
about the fields, see Field Properties.
{ "mappings": { "dynamic": true|false, "fields": { "<field-name>": { "type": "stringFacet" } } } }
Configure Properties for the stringFacet Type
The Atlas Search stringFacet type has the following parameters:
UI Field Name | JSON Option | Type | Necessity | Description |
|---|---|---|---|---|
Data Type |
| string | Required | Human-readable label that identifies this field type.
Value must be |
Try an Example for the stringFacet Type
The following index definition example uses the sample_mflix.movies collection. If you have the sample data already loaded on your cluster, you can use the Visual Editor or JSON Editor in the Atlas UI to configure the index. After you select your preferred configuration method, select the database and collection, and refine your index to add field mappings.
The following index definition for the sample_mflix.movies
collection in the sample dataset indexes the genres field as
stringFacet for faceting.
In the Add Field Mapping window, select genres from the Field Name dropdown.
Click the Data Type dropdown and select StringFacet.
Click Add.
{ "mappings": { "dynamic": false, "fields": { "genres": { "type": "stringFacet" } } } }
The following index definition for the sample_mflix.movies
collection in the sample dataset indexes the genres field as
stringFacet and string types to return the following
types of results for your queries:
Metadata results for queries using Atlas Search facet.
Search results for queries using Atlas Search operators like text, phrase, and other operators that perform text search.
In the Add Field Mapping window, select genres from the Field Name dropdown.
Click the Data Type dropdown and select StringFacet.
Click Add.
Repeat step 1 and select String from the Data Type dropdown.
Review the default setting for String Properties and click Add.
{ "mappings": { "dynamic": false, "fields": { "genres": [ { "type": "stringFacet" }, { "type": "string" } ] } } }
Learn More
To learn more about the facet collector and see example queries, see Examples.
To learn how to create an index with a facet definition and query that index using the facet collector,
see the How to Use Facets with Atlas Search tutorial.
To see an example index and query that uses stringFacet to run a faceted search with paginated results,
see Use Facet with the Paginated Results.