From `orders`, match orders with status `"completed"`, add a `discountedTotal` field (total * 0.9), sort by discountedTotal desc, and limit to 2.

Problem Statement

<p>From <code>orders</code>, match <code>orders</code> with <code>status</code> <code>"completed"</code>, add a <code>discountedTotal</code> field (total * 0.9), sort by discountedTotal desc, and limit to 2.</p>

Examples

Input: orders collection: +-----+----------+-------+-----------+ | _id | customer | total | status | +-----+----------+-------+-----------+ | 1 | A | 500 | completed | | 2 | B | 200 | pending | | 3 | C | 800 | completed | | 4 | D | 300 | completed | +-----+----------+-------+-----------+

Output: +-----+----------+-------+-----------+-----------------+ | _id | customer | total | status | discountedTotal | +-----+----------+-------+-----------+-----------------+ | 3 | C | 800 | completed | 720 | | 1 | A | 500 | completed | 450 | +-----+----------+-------+-----------+-----------------+

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

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: Use db.<collection>.aggregate([ ... ]) to run a multi-stage data processing pipeline. 💡 Hint 2: Order pipeline stages logically (e.g. $match early to filter documents before processing). 💡 Hint 3: Convert the aggregation cursor using .toArray() at the end of the function.

Editorial & Approach

Problem Overview & Intuition

To solve "Pipeline: Match + AddFields + Sort + Limit", we query the MongoDB document store. The goal is to from `orders`, match orders with status `"completed"`, add a `discountedtotal` field (total * 0.9), sort by discountedtotal desc, and limit to 2. 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.orders.aggregate([
    { $match: { status: "completed" } },
    { $addFields: { discountedTotal: { $multiply: ["$total", 0.9] } } },
    { $sort: { discountedTotal: -1 } },
    { $limit: 2 }
  ]);
}

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.

Pipeline: Match + AddFields + Sort + Limit

Hard

From orders, match orders with status "completed", add a discountedTotal field (total * 0.9), sort by discountedTotal desc, and limit to 2.

Example Scenarios

1Example 1

Input:

orders collection

_id	customer	total	status
1	A	500	completed
2	B	200	pending
3	C	800	completed
4	D	300	completed

Output:

_id	customer	total	status	discountedTotal
3	C	800	completed	720
1	A	500	completed	450

Explanation:

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

MongoDB Editor

Loading Editor...

Query Results (JSON)

Run your MongoDB code to see results here.