range
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Definition
rangeThe
rangeoperator supports querying and scoring numeric and date values. This operator can be used to perform a search over:Number fields of BSON
int32,int64, anddoubledata types.Date fields of BSON
datedata type in ISODate format.
You can use the
rangeoperator to find results that are within a given numeric or date range.
Syntax
range has the following syntax:
1 { 2 "$search": { 3 "index": <index name>, // optional, defaults to "default" 4 "range": { 5 "path": "<field-to-search>", 6 "gt | gte": <value-to-search>, 7 "lt | lte": <value-to-search>, 8 "score": <score-options> 9 } 10 } 11 }
Options
range uses the following terms to construct a query:
Field | Type | Description | Necessity |
|---|---|---|---|
gt or gte | BSON date or number | Find values greater than (
| no |
lt or lte | BSON date or number | Find values less than (
| no |
path | string or array of strings | Indexed field or fields to search.
See Path Construction. | yes |
score | object | Modify the score assigned to matching search results. You can modify the default score using the following options:
For information on using NoteWhen you query values in arrays, Atlas Search doesn't alter the score of the matching results based on the number of values inside the array that matched the query. The score would be the same as a single match regardless of the number of matches inside an array. | no |
Examples
The following examples use the collection in the sample data. If you loaded the sample data on your cluster, you can create the indexes using the index definitions in the examples below and run the example queries on your cluster.
Tip
If you've already loaded the sample dataset, follow the Get Started with Atlas Search tutorial to create an index definition and run Atlas Search queries.
Number Example
The following examples use indexes on numeric fields in the
sample data and run
range queries against the indexed fields.
Date Example
The following example uses the range operator to query a date
field in the sample_mflix.movies collection. For this example, you
can use either static or dynamic mappings to index the date type
field named released in the collection.
The following query searches for movies released between January 1,
2010 and January 1, 2015. It includes a $limit stage to
limit the output to 5 results and a $project stage to
exclude all fields except title and released.
1 db.movies.aggregate([ 2 { 3 "$search": { 4 "range": { 5 "path": "released", 6 "gt": ISODate("2010-01-01T00:00:00.000Z"), 7 "lt": ISODate("2015-01-01T00:00:00.000Z") 8 } 9 } 10 }, 11 { 12 "$limit": 5 13 }, 14 { 15 "$project": { 16 "_id": 0, 17 "title": 1, 18 "released": 1 19 } 20 } 21 ])
The above query returns the following search results:
1 { "title" : "The Fall of the House of Usher", "released" : ISODate("2011-09-20T00:00:00Z") } 2 { "title" : "The Blood of a Poet", "released" : ISODate("2010-05-20T00:00:00Z") } 3 { "title" : "Too Much Johnson", "released" : ISODate("2014-08-30T00:00:00Z") } 4 { "title" : "Stolen Desire", "released" : ISODate("2012-07-01T00:00:00Z") } 5 { "title" : "The Monkey King", "released" : ISODate("2012-01-12T00:00:00Z") }