How to Index Numeric Values
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You can use the Atlas Search number type to index fields with numeric
values of int32, int64, and double data types.
You can use the equals, range, and near
operators to query indexed fields of type number.
Note
To query numeric values in arrays, you can use only the range operator.
Atlas Search doesn't automatically index numeric values for faceting. Instead, you must index the numeric values using numberFacet to run a facet query on number fields.
Atlas Search automatically indexes all numeric fields in indexes created after July 2023 for sorting the Atlas Search results. For preexisting indexes, you must rebuild the index to use number fields in the index for sorting. To learn more, see Rebuild Index for Sorting and Sort Atlas Search Results.
If you enable dynamic mappings, Atlas Search
automatically indexes fields of type number. You can
use the Visual Editor or the JSON Editor in the Atlas UI to
index fields as the number type.
Define the Index for the number Type
Configure number Field Properties
The Atlas Search number type has the following parameters:
UI Field Name | JSON Option | Type | Necessity | Description | Default |
|---|---|---|---|---|---|
Data Type | type | string | Required | Human-readable label that identifies this field type.
Value must be number. | |
Representation | representation | string | Optional | Data type of the field to index. Values are:
To learn more, see example below. | double |
Index Integers | indexIntegers | boolean | Optional | Flag that indicates whether to index or omit indexing int32
and int64 type values. Value can be true or false.
Either this or indexDoubles must be true.
To learn more, see example below. | true |
Index Doubles | indexDoubles | boolean | Optional | Flag that indicates whether to index or omit indexing double
type values. Value can be true or false.
Either this or indexIntegers must be true.
To learn more, see example below. | true |
Try an Example for the number Type
The following index definition examples use multiple collections in the sample data. If you have the sample data already loaded on your cluster, you can use the Visual Editor and JSON Editor to configure these indexes. After you select your preferred configuration method, select the database and collection, and refine your index to add field mappings.