$match (aggregation)

11/22/2024

APPLIES TO: MongoDB vCore

The $match stage in the aggregation pipeline is used to filter documents that match a specified condition. It's similar to the find operation but is used within the aggregation pipeline to narrow down the documents that pass through to the next stage. This stage is highly useful for optimizing performance by reducing the number of documents that need to be processed in subsequent stages.

Syntax

The basic syntax for the $match stage is as follows:

{
  $match: {
    <query>
  }
}

	Description
`<query>`	A standard MongoDB query document that specifies the conditions that the documents must meet.

Examples

Let's understand the usage with the following sample json.

{
  "_id": "7954bd5c-9ac2-4c10-bb7a-2b79bd0963c5",
   "name": "Lakeshore Retail | DJ Equipment Stop - Port Cecile",
  "location": {
    "lat": 60.1441,
    "lon": -141.5012
  },
  "staff": {
    "totalStaff": {
      "fullTime": 2,
      "partTime": 0
    }
  },
  "sales": {
    "salesByCategory": [
      {
        "categoryName": "DJ Headphones",
        "totalSales": 35921
      }
    ],
    "fullSales": 3700
  },
  "promotionEvents": [
    {
      "eventName": "Bargain Blitz Days",
      "promotionalDates": {
        "startDate": {
          "Year": 2024,
          "Month": 3,
          "Day": 11
        },
        "endDate": {
          "Year": 2024,
          "Month": 2,
          "Day": 18
        }
      },
      "discounts": [
        {
          "categoryName": "DJ Turntables",
          "discountPercentage": 18
        },
        {
          "categoryName": "DJ Mixers",
          "discountPercentage": 15
        }
      ]
    }
  ],
  "tag": [
    "#ShopLocal",
    "#SeasonalSale",
    "#FreeShipping",
    "#MembershipDeals"
  ]
}

Example 1: Match documents using string comparison

To filter documents where the _id is "7954bd5c-9ac2-4c10-bb7a-2b79bd0963c5":

db.stores.aggregate([
    {
      $match: {
        "_id": "7954bd5c-9ac2-4c10-bb7a-2b79bd0963c5"
      }
    }
])

This query would return the sample document.

Example 2: Match documents using numeric comparison

To filter documents where the total sales are greater than $35,000:

db.stores.aggregate([
    {
      $match: {
        "sales.totalSales": { $gt: 35000 }
      }
    },
    // Limit the result to the first 3 documents
    { $limit: 3 },
      // Include only _id and name fields in the output 
    { $project: { _id: 1, name: 1 } } 
])

This query would return the following document.

[
  {
    "_id": "8345de34-73ec-4a99-9cb6-a81f7b145c34",
    "name": "Northwind Traders | Bed and Bath Place - West Oraland"
  },
  {
    "_id": "57cc4095-77d9-4345-af20-f8ead9ef0197",
    "name": "Wide World Importers | Bed and Bath Store - West Vitafort"
  },
  {
    "_id": "560099f8-325f-4c35-a4e5-2e0879eb95af",
    "name": "Wide World Importers | Bed and Bath Depot - North Maritzaberg"
  }
]

Example 3: Match documents within sub documents

To filter documents where there's a discount of 15% on DJ Mixers:

db.stores.aggregate([
    {
      $match: {
        "promotionEvents.discounts": {
          $elemMatch: {
            "categoryName": "DJ Mixers",
            "discountPercentage": 15
          }
        }
      }
    },
    // Limit the result to the first 3 documents
    { $limit: 3 },
      // Include only _id and name fields in the output 
    { $project: { _id: 1, name: 1 } } 
])