For each product, compute `totalValue = price * stock`. Then sum all totalValues to get the total inventory valuation.

Problem Statement

<p>For each product, compute <code>totalValue = <code>price</code> * stock</code>. Then sum all totalValues to get the total <code>inventory</code> valuation.</p>

Examples

Input: products collection: +-----+--------+-------+-------+ | _id | name | price | stock | +-----+--------+-------+-------+ | 1 | Widget | 10 | 100 | | 2 | Gadget | 50 | 20 | | 3 | Gizmo | 25 | 40 | +-----+--------+-------+-------+

Output: +------+--------------------+ | _id | inventoryValuation | +------+--------------------+ | null | 3000 | +------+--------------------+

Explanation: Documents containing the matching array elements are selected from the collection.

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 "Inventory Valuation Report", we query the MongoDB document store. The goal is to for each product, compute `totalvalue = price * stock`. then sum all totalvalues to get the total inventory valuation. 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.products.aggregate([
    { $addFields: { totalValue: { $multiply: ["$price", "$stock"] } } },
    { $group: { _id: null, inventoryValuation: { $sum: "$totalValue" } } }
  ]);
}

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.

Inventory Valuation Report

Hard

For each product, compute totalValue = price * stock. Then sum all totalValues to get the total inventory valuation.

Example Scenarios

1Example 1

Input:

products collection

_id	name	price	stock
1	Widget	10	100
2	Gadget	50	20
3	Gizmo	25	40

Output:

_id	inventoryValuation
null	3000

Explanation:

Documents containing the matching array elements are selected from the collection.

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Query Results (JSON)

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