How to Index the Elements of an Array

For indexing arrays, Atlas Search requires only the data type of the array elements. You don't have to specify that the data is contained in an array ([]) in the index definition.

If you enable dynamic mappings, Atlas Search automatically indexes elements of dynamically indexable data types inside the array. To learn more about the data types that Atlas Search dynamically indexes, see Data Types.

You can use the Visual Editor or the JSON Editor in the Atlas UI to define the index for elements in arrays.

How Does Atlas Search Index Array Elements?

Atlas Search indexes the supported data types inside an array by flattening the fields during indexing.

Example

Consider the following documents:

doc1 = { a: {b: [[<value1>, <value2>], <value3>] }}
doc2 = { a: {b: [<value1>, <value2>, <value3>] } }
doc3 = { a: [{ b: <value1>}, {b: <value2>}, {b: <value3>}] }

Atlas Search flattens the preceding arrays similar to the following during indexing:

LuceneDoc<n> = {"a.b":[<value1>,<value2>,<value3>]}

How Can I Index Objects in Arrays?

To query fields inside an array of documents or objects, you must use the embeddedDocuments type to index the field that contains the array of objects.

Define the Index for the Array Elements

To define the index for the array elements, 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 of type array to index from the Field Name dropdown.
Click the Data Type dropdown and select the data type of the array element that you want to index. To learn more about the configuring the properties for the selected type, refer to the documentation for the selected type.
Click Add.

The following is the JSON syntax for indexing elements inside an array. Replace the default index definition with the following.

1 {
2   "mappings": {
3     "dynamic": true|false,
4     "fields": {
5       "<array-field-name>": {
6         "type": "<array-element-data-type>"
7       }
8     }
9   }
10 }

Try an Example for Indexing Array Elements

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 indexes the genres field, which contains an array of string values.

In the Add Field Mapping window, select genres from the Field Name dropdown.
Click the Data Type dropdown and select String.
Keep the default settings for the String Properties.
Click Add.

Replace the default index definition with the following index definition.

1 {
2   "mappings": {
3     "fields": {
4       "genres": {
5         "type": "string"
6       }
7     }
8   }
9 }

Back

Field Mappings

autocomplete

1	{
2	"mappings": {
3	"dynamic": true\|false,
4	"fields": {
5	"<array-field-name>": {
6	"type": "<array-element-data-type>"
7	}
8	}
9	}
10	}

1	{
2	"mappings": {
3	"fields": {
4	"genres": {
5	"type": "string"
6	}
7	}
8	}
9	}