MongoDB aggregation and projection?

MongoDB aggregation with projection allows you to transform and reshape documents by selecting specific fields, computing new values, and controlling the output structure. The $project stage in the aggregation pipeline passes documents with requested fields to the next stage.

Syntax

db.collection.aggregate([
    { $project: {
        field1: 1,           // Include field
        field2: 0,           // Exclude field
        newField: "$existingField",  // Rename field
        computedField: { $operation: "expression" }
    }}
]);

Sample Data

Let us create a collection with documents ?

db.demo762.insertOne({
    "_id": {
        "userId": 101,
        "userName": "Chris"
    },
    "countryName": "US",
    "details": [
        {
            "Name": "Robert",
            "DueDate": "2020-04-10"
        },
        {
            "Name": "Robert",
            "DueDate": "2020-04-09"
        },
        {
            "Name": "Robert",
            "DueDate": "2020-03-06"
        }
    ]
});

{
    "acknowledged": true,
    "insertedId": {
        "userId": 101,
        "userName": "Chris"
    }
}

Display all documents from the collection ?

db.demo762.find();

{
    "_id": { "userId": 101, "userName": "Chris" },
    "countryName": "US",
    "details": [
        { "Name": "Robert", "DueDate": "2020-04-10" },
        { "Name": "Robert", "DueDate": "2020-04-09" },
        { "Name": "Robert", "DueDate": "2020-03-06" }
    ]
}

Example: Aggregation with Projection

The following query sorts details by DueDate and projects only the first 2 elements ?

db.demo762.aggregate([
    { "$match": {
        "_id": { "$eq": { userId: 101, userName: "Chris" }}
    }},
    { "$unwind": "$details" },
    { "$sort": { "details.DueDate": 1 }},
    { "$group": {
        "_id": "$_id",
        "details": { "$push": "$details" },
        "countryName": { "$first": "$countryName" }
    }},
    { "$project": {
        "details": { "$slice": ["$details", 2] },
        "countryName": 1
    }}
]).pretty();

{
    "_id": {
        "userId": 101,
        "userName": "Chris"
    },
    "countryName": "US",
    "details": [
        {
            "Name": "Robert",
            "DueDate": "2020-03-06"
        },
        {
            "Name": "Robert",
            "DueDate": "2020-04-09"
        }
    ]
}

How It Works

• $match filters documents by the specified criteria
• $unwind deconstructs the details array into separate documents
• $sort orders documents by DueDate in ascending order
• $group reassembles the array and preserves other fields
• $project limits the details array to first 2 elements using $slice

Conclusion

The $project stage in MongoDB aggregation enables field selection, transformation, and computed fields. Combined with other pipeline stages, it provides powerful document reshaping capabilities for complex data processing needs.