Calculate the overall average `rating` across all reviews in the `reviews` collection.

Problem Statement

<p>Calculate the overall average <code>rating</code> across all reviews in the <code>reviews</code> collection.</p>

Examples

Input: reviews collection: +-----+---------+--------+ | _id | product | rating | +-----+---------+--------+ | 1 | A | 4 | | 2 | B | 5 | | 3 | A | 3 | | 4 | C | 5 | +-----+---------+--------+

Output: +------+-----------+ | _id | avgRating | +------+-----------+ | null | 4.25 | +------+-----------+

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 All Documents ($group _id: null)", we query the MongoDB document store. The goal is to calculate the overall average `rating` across all reviews in the `reviews` collection. 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.reviews.aggregate([
    { $group: { _id: null, avgRating: { $avg: "$rating" } } }
  ]);
}

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 All Documents ($group _id: null)

Medium

Calculate the overall average rating across all reviews in the reviews collection.

Example Scenarios

1Example 1

Input:

reviews collection

_id	product	rating
1	A	4
2	B	5
3	A	3
4	C	5

Output:

_id	avgRating
null	4.25

Explanation:

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

MongoDB Editor

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Query Results (JSON)

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