Group invoices by `client`, sum `amount`, then project `_id` as `client` and show `totalAmount`.

Problem Statement

<p>Group invoices by <code>client</code>, sum <code>amount</code>, then project <code>_id</code> as <code>client</code> and show <code>totalAmount</code>.</p>

Examples

Input: invoices collection: +-----+--------+--------+ | _id | client | amount | +-----+--------+--------+ | 1 | Acme | 500 | | 2 | Globex | 300 | | 3 | Acme | 700 | +-----+--------+--------+

Output: +-------------+ | totalAmount | +-------------+ | 1200 | | 300 | +-------------+

Explanation: The aggregation pipeline processes the documents through stages to compute the grouped results.

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: This problem requires grouping documents by a key and aggregating values. Use db.<collection>.aggregate([...]) with a $group stage. 💡 Hint 2: In the $group stage, set _id to the grouping field (e.g. "$category" or "$dept") and use accumulator operators like $sum, $avg, $max, or $min. 💡 Hint 3: Remember to call .toArray() at the end of the aggregation pipeline to return the resolved documents array.

Editorial & Approach

Problem Overview & Intuition

To solve "Group + Project (Rename Fields)", we query the MongoDB document store. The goal is to group invoices by `client`, sum `amount`, then project `_id` as `client` and show `totalamount`. Using an aggregation pipeline, the database engine filters and structures the BSON documents efficiently.

Step-by-Step Approach

Identify Target Collection: Access the collection through the db instance.
Construct Query / Pipeline: Build the aggregation stages ($match, $group, $sort, etc.).
Resolve Cursor: Invoke .toArray() to transform the query cursor into the required array of documents.

Optimal Implementation (MongoDB)

function solve(db) {
  return db.invoices.aggregate([
    { $group: { _id: "$client", totalAmount: { $sum: "$amount" } } },
    { $project: { _id: 0, client: 1, totalAmount: 1 } }
  ]);
}

Complexity Analysis

Time Complexity O(N) pipeline traversal through aggregation stages.

Space Complexity O(M) intermediate document buffer in aggregation pipeline.

Key Considerations & Edge Cases

Empty Collections: If no documents match, the query cleanly returns an empty array [].
Missing / NULL Fields: Missing fields in documents are handled safely without throwing runtime exceptions.
Type Coercion: BSON types (ObjectId, Numbers, Strings) are compared strictly according to MongoDB specifications.

Group + Project (Rename Fields)

Medium

Group invoices by client, sum amount, then project _id as client and show totalAmount.

Example Scenarios

1Example 1

Input:

invoices collection

_id	client	amount
1	Acme	500
2	Globex	300
3	Acme	700

Output:

totalAmount
1200
300

Explanation:

The aggregation pipeline processes the documents through stages to compute the grouped results.

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Query Results (JSON)

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