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‎articles/cosmos-db/mongodb/vcore/commands/aggregation/TOC.yml‎

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- name: count
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href: count.md
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- name: distinct
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href: distinct.md
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href: distinct.md
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- name: set
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href: set.md
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- name: replacewith
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href: replacewith.md
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- name: sample
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href: sample.md

‎articles/cosmos-db/mongodb/vcore/commands/aggregation/replacewith.md‎

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---
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title: $replaceWith
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titleSuffix: Overview of the $replaceWith operator in Azure Cosmos DB for MongoDB vCore
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description: The $replaceWith operator in Azure Cosmos DB for MongoDB vCore returns a document after replacing a document with the specified document
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author: abinav2307
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ms.author: abramees
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ms.service: azure-cosmos-db
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ms.subservice: mongodb-vcore
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ms.topic: conceptual
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ms.date: 02/24/2025
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---
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# $replaceWith
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The `$replaceWith` aggregation stage operator is used to replace the input document with the specified document. The `$replaceWith` operator transforms documents from one structure to another or replaces them entirely with new fields and values.
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## Syntax
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```mongodb
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{
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"$replaceWith": <newDocument>
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}
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```
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## Parameters
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| Parameter | Description |
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| --- | --- |
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| **`newDocument`** | The new document to replace the original document|
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## Examples
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Consider this sample document from the stores collection in the StoreData database.
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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 - Return a document that replaces the contents of the original document with a subset of items
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First, match a specific document to replace by the _id field and replace the contents of the document with the specified fields.
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```mongodb
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db.stores.aggregate([{ "$match": { "_id": "bda56164-954d-4f47-a230-ecf64b317b43" } }, { "$replaceWith": { "_id": "$_id", "name": "$name", "sales": "$sales.totalSales" } }])
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```
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This returns the following result:
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```json
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{
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"_id": "bda56164-954d-4f47-a230-ecf64b317b43",
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"name": "Boulder Innovations | Home Security Place - Ankundingburgh",
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"sales": 37015
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}
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```
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### Example 2 - Return a document that replaces the contents of the original document after aggregating specified fields
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```mongodb
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db.stores.aggregate([{ "$match": { "_id": "bda56164-954d-4f47-a230-ecf64b317b43" } }, { "$replaceWith": { "_id": "$_id", "name": "$name", "totalStaff": {"$add": ["$staff.totalStaff.fullTime", "$staff.totalStaff.partTime"]}}}])
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```
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This returns the following result:
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```json
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{
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"_id": "bda56164-954d-4f47-a230-ecf64b317b43",
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"name": "Boulder Innovations | Home Security Place - Ankundingburgh",
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"totalStaff": 29
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}
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```
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## Related content
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- [Migrate to vCore based Azure Cosmos DB for MongoDB](https://aka.ms/migrate-to-azure-cosmosdb-for-mongodb-vcore)
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- [update with vCore based Azure Cosmos DB for MongoDB](../query-and-write/update.md)

‎articles/cosmos-db/mongodb/vcore/commands/aggregation/sample.md‎

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---
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title: $sample
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titleSuffix: Overview of the $sample operator in Azure Cosmos DB for MongoDB vCore
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description: The $sample operator in Azure Cosmos DB for MongoDB vCore returns a randomly selected number of documents
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author: abinav2307
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ms.author: abramees
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ms.service: azure-cosmos-db
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ms.subservice: mongodb-vcore
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ms.topic: conceptual
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ms.date: 02/24/2025
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---
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# $sample
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The `$sample` stage is used in aggregation pipelines to randomly select a specified number of documents from a collection. The `$sample` command is useful during testing, data analysis, and generating random subsets of data for machine learning.
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## Syntax
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```mongodb
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{
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"$sample": { "size": <number> }
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}
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```
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### Parameters
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| Parameter | Description |
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| --- | --- |
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| **`size`** | The number of documents to randomly select from the collection|
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## Examples
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Consider this sample document from the stores collection in the StoreData database.
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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 - Randomly select five documents and project the corresponding document IDs
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```mongodb
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db.stores.aggregate([{"$sample": {"size": 5}}, {"$project": {"_id": 1}}])
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```
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This query returns the following results:
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```json
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[
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{ "_id": "f7ae8b40-0c66-4e80-9261-ab31bbabffb4" },
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{ "_id": "25350272-6797-4f98-91f8-fe79084755c7" },
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{ "_id": "c7fd1d22-1a29-4cb0-9155-1ad71d600c2b" },
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{ "_id": "e602b444-9519-42e3-a2e1-b5a3da5f6e64" },
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{ "_id": "189c239a-edca-434b-baae-aada3a27a2c5" }
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]
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```
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## Related content
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- [Migrate to vCore based Azure Cosmos DB for MongoDB](https://aka.ms/migrate-to-azure-cosmosdb-for-mongodb-vcore)
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- [count with vCore based Azure Cosmos DB for MongoDB](count.md)

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