Count the total number of documents in the `events` collection using `$count` and name the result `totalEvents`.

Problem Statement

<p>Count the total number of documents in the <code>events</code> collection using <code>$count</code> and <code>name</code> the result <code>totalEvents</code>.</p>

Examples

Input: events collection: +-----+--------+ | _id | type | +-----+--------+ | 1 | click | | 2 | scroll | | 3 | click | | 4 | hover | +-----+--------+

Output: +-------------+ | totalEvents | +-------------+ | 4 | +-------------+

Explanation: The query calculates the total count of documents that satisfy the given filter criteria.

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 "Aggregation: $count Stage", we query the MongoDB document store. The goal is to count the total number of documents in the `events` collection using `$count` and name the result `totalevents`. 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.events.aggregate([{ $count: "totalEvents" }]);
}

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.

Aggregation: $count Stage

Medium

Count the total number of documents in the events collection using $count and name the result totalEvents.

Example Scenarios

1Example 1

Input:

events collection

_id	type
1	click
2	scroll
3	click
4	hover

Output:

totalEvents
4

Explanation:

The query calculates the total count of documents that satisfy the given filter criteria.

MongoDB Editor

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Query Results (JSON)

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