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Merge pull request #2982 from abinav2307/geospatial-third-pass-validation
Geospatial third pass validation
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‎articles/cosmos-db/mongodb/vcore/operators/geospatial/$box.md‎

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ms.service: azure-cosmos-db
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ms.subservice: mongodb-vcore
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ms.topic: language-reference
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ms.date: 07/25/2025
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ms.date: 09/04/2025
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---
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# $box
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## Syntax
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The syntax for the `$box` operator is as follows:
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```javascript
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{
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<location field>: {
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| `lower_left`| An array of [longitude, latitude] specifying the bottom-left corner |
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| `upper_right`| An array of [longitude, latitude] specifying the top-right corner |
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## Example
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## Examples
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Consider this sample document from the stores collection.
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```json
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{
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"_id": "0fcc0bf0-ed18-4ab8-b558-9848e18058f4",
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"name": "First Up Consultants | Beverage Shop - Satterfieldmouth",
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"location": {
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"lat": -89.2384,
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"lon": -46.4012
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},
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"staff": {
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"totalStaff": {
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"fullTime": 8,
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"partTime": 20
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}
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},
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"sales": {
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"totalSales": 75670,
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"salesByCategory": [
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{
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"categoryName": "Wine Accessories",
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"totalSales": 34440
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},
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{
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"categoryName": "Bitters",
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"totalSales": 39496
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},
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{
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"categoryName": "Rum",
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"totalSales": 1734
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}
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]
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},
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"promotionEvents": [
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{
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"eventName": "Unbeatable Bargain Bash",
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"promotionalDates": {
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"startDate": {
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"Year": 2024,
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"Month": 6,
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"Day": 23
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},
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"endDate": {
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"Year": 2024,
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"Month": 7,
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"Day": 2
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}
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},
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"discounts": [
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{
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"categoryName": "Whiskey",
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"discountPercentage": 7
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},
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{
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"categoryName": "Bitters",
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"discountPercentage": 15
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},
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{
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"categoryName": "Brandy",
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"discountPercentage": 8
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},
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{
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"categoryName": "Sports Drinks",
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"discountPercentage": 22
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},
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{
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"categoryName": "Vodka",
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"discountPercentage": 19
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}
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]
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},
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{
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"eventName": "Steal of a Deal Days",
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"promotionalDates": {
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"startDate": {
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"Year": 2024,
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"Month": 9,
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"Day": 21
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},
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"endDate": {
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"Year": 2024,
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"Month": 9,
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"Day": 29
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}
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},
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"discounts": [
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{
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"categoryName": "Organic Wine",
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"discountPercentage": 19
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},
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{
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"categoryName": "White Wine",
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"discountPercentage": 20
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},
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{
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"categoryName": "Sparkling Wine",
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"discountPercentage": 19
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},
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{
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"categoryName": "Whiskey",
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"discountPercentage": 17
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},
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{
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"categoryName": "Vodka",
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"discountPercentage": 23
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}
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]
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}
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]
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}
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```
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Using the `stores` collection, let's find stores within a rectangular region:
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### Example 1 - Find stores within a rectangular region
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```javascript
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db.stores.find(
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).limit(2)
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```
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This query returns all stores that fall within the rectangular region defined by these coordinates.
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The first two results returned by this query are:
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```json
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[
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{
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"_id": "923d2228-6a28-4856-ac9d-77c39eaf1800",
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"name": "Lakeshore Retail | Home Decor Hub - Franciscoton",
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"lon": 0.6784
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}
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}
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]
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```
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## Related content
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[!INCLUDE[Related content](../includes/related-content.md)]
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‎articles/cosmos-db/mongodb/vcore/operators/geospatial/$center.md‎

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@@ -32,9 +32,123 @@ The `$center` operator specifies a circle using legacy coordinate pairs to be us
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| `<y>` | The y-coordinate of the circle's center point |
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| `<radius>` | The radius of the circle in the same units as the coordinates |
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## Example
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## Examples
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Let's find all stores within a 50-degree radius of 'First Up Consultants Microphone Bazaar' using our `stores` dataset.
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Consider this sample document from the stores collection.
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```json
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{
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"_id": "0fcc0bf0-ed18-4ab8-b558-9848e18058f4",
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"name": "First Up Consultants | Beverage Shop - Satterfieldmouth",
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"location": {
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"lat": -89.2384,
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"lon": -46.4012
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},
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"staff": {
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"totalStaff": {
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"fullTime": 8,
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"partTime": 20
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}
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},
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"sales": {
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"totalSales": 75670,
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"salesByCategory": [
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{
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"categoryName": "Wine Accessories",
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"totalSales": 34440
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},
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{
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"categoryName": "Bitters",
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"totalSales": 39496
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},
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{
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"categoryName": "Rum",
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"totalSales": 1734
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}
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]
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},
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"promotionEvents": [
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{
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"eventName": "Unbeatable Bargain Bash",
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"promotionalDates": {
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"startDate": {
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"Year": 2024,
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"Month": 6,
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"Day": 23
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},
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"endDate": {
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"Year": 2024,
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"Month": 7,
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"Day": 2
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}
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},
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"discounts": [
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{
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"categoryName": "Whiskey",
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"discountPercentage": 7
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},
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{
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"categoryName": "Bitters",
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"discountPercentage": 15
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},
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{
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"categoryName": "Brandy",
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"discountPercentage": 8
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},
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{
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"categoryName": "Sports Drinks",
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"discountPercentage": 22
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},
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{
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"categoryName": "Vodka",
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"discountPercentage": 19
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}
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]
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},
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{
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"eventName": "Steal of a Deal Days",
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"promotionalDates": {
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"startDate": {
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"Year": 2024,
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"Month": 9,
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"Day": 21
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},
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"endDate": {
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"Year": 2024,
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"Month": 9,
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"Day": 29
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}
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},
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"discounts": [
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{
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"categoryName": "Organic Wine",
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"discountPercentage": 19
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},
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{
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"categoryName": "White Wine",
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"discountPercentage": 20
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},
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{
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"categoryName": "Sparkling Wine",
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"discountPercentage": 19
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},
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{
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"categoryName": "Whiskey",
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"discountPercentage": 17
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},
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{
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"categoryName": "Vodka",
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"discountPercentage": 23
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}
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]
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}
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]
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}
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```
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### Example 1 - Search within a 50-degree radius
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Let's find all stores within a 50-degree radius of 'First Up Consultants Microphone Bazaar' using our `stores` dataset. This query retrieves stores within a 50-degree radius of the First Up Consultants Microphone Bazaar location.
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```javascript
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db.stores.find(
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).limit(2)
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```
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The query returns stores within 50-degree radius of the First Up Consultants Microphone Bazaar location, which could be useful for analyzing market coverage or planning delivery routes.
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The first two results returned by this query are:
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```json
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[
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{
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"name": "Contoso, Ltd. | Baby Products Corner - Port Jerrold",
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"location": { "lat": -72.7709, "lon": -24.3031 },
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"location": { "lat": -64.5509, "lon": -28.7144 },
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"city": "Trystanport"
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}
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]
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```
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> [!IMPORTANT]
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## Related content
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[!INCLUDE[Related content](../includes/related-content.md)]
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