From `subscriptions`, match active subscriptions (`status: "active"`), group with `_id: null` to compute the total MRR by summing `price`.

Problem Statement

<p>From <code>subscriptions</code>, match active subscriptions (<code>status: "active"</code>), group with <code>_id: null</code> to compute the total MRR by summing <code>price</code>.</p>

Examples

Input: subscriptions collection: +-----+--------+------------+-------+-----------+ | _id | tenant | plan | price | status | +-----+--------+------------+-------+-----------+ | 1 | A | Starter | 29 | active | | 2 | B | Pro | 99 | active | | 3 | C | Enterprise | 499 | active | | 4 | D | Starter | 29 | cancelled | +-----+--------+------------+-------+-----------+

Output: +------+----------+ | _id | totalMRR | +------+----------+ | null | 627 | +------+----------+

Explanation: The query retrieves all documents from the collection that satisfy the specified filter criteria.

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 "Calculate MRR (SaaS Revenue)", we query the MongoDB document store. The goal is to from `subscriptions`, match active subscriptions (`status: "active"`), group with `_id: null` to compute the total mrr by summing `price`. 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.subscriptions.aggregate([
    { $match: { status: "active" } },
    { $group: { _id: null, totalMRR: { $sum: "$price" } } }
  ]);
}

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.

Calculate MRR (SaaS Revenue)

Hard

From subscriptions, match active subscriptions (status: "active"), group with _id: null to compute the total MRR by summing price.

Example Scenarios

1Example 1

Input:

subscriptions collection

_id	tenant	plan	price	status
1	A	Starter	29	active
2	B	Pro	99	active
3	C	Enterprise	499	active
4	D	Starter	29	cancelled

Output:

_id	totalMRR
null	627

Explanation:

The query retrieves all documents from the collection that satisfy the specified filter criteria.

MongoDB Editor

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Query Results (JSON)

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