Calculate the average `gpa` per `major` from the `students` collection.

Problem Statement

<p>Calculate the average <code>gpa</code> per <code>major</code> from the <code>students</code> collection.</p>

Examples

Input: students collection: +-----+---------+-------+-----+ | _id | name | major | gpa | +-----+---------+-------+-----+ | 1 | Alice | CS | 3.8 | | 2 | Bob | Math | 3.5 | | 3 | Charlie | CS | 3.6 | | 4 | Dana | Math | 3.9 | +-----+---------+-------+-----+

Output: +------+--------+ | _id | avgGpa | +------+--------+ | CS | 3.7 | | Math | 3.7 | +------+--------+

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 and Average ($group + $avg)", we query the MongoDB document store. The goal is to calculate the average `gpa` per `major` from the `students` 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.students.aggregate([
    { $group: { _id: "$major", avgGpa: { $avg: "$gpa" } } }
  ]);
}

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 and Average ($group + $avg)

Medium

Calculate the average gpa per major from the students collection.

Example Scenarios

1Example 1

Input:

students collection

_id	name	major	gpa
1	Alice	CS	3.8
2	Bob	Math	3.5
3	Charlie	CS	3.6
4	Dana	Math	3.9

Output:

_id	avgGpa
CS	3.7
Math	3.7

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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