Insert 3 new students `{name: "X", grade: 90}`, `{name: "Y", grade: 85}`, `{name: "Z", grade: 95}`, then find the student with the highest grade.

Problem Statement

<p>Insert 3 new <code>students</code> <code>{<code>name</code>: "X", grade: 90}</code>, <code>{<code>name</code>: "Y", grade: 85}</code>, <code>{<code>name</code>: "Z", grade: 95}</code>, then find the student with the highest grade.</p>

Examples

Input: students collection: []

Output: +--------------+------+-------+ | _id | name | grade | +--------------+------+-------+ | id_w3o976ky9 | Z | 95 | +--------------+------+-------+

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

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: Sort matched documents using .sort({ field: 1 }) for ascending or { field: -1 } for descending. 💡 Hint 2: Chain .sort(...) directly after db.<collection>.find(...) and before .limit() / .toArray(). 💡 Hint 3: Complete: return db.<collection>.find(<filter>).sort(<sortObj>).toArray();

Editorial & Approach

Problem Overview & Intuition

To solve "Insert Then Query Verification", we query the MongoDB document store. The goal is to insert 3 new students `{name: "x", grade: 90}`, `{name: "y", grade: 85}`, `{name: "z", grade: 95}`, then find the student with the highest grade. Using a targeted find query, 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 query filter with appropriate comparison operators.
Resolve Cursor: Invoke .toArray() to transform the query cursor into the required array of documents.

Optimal Implementation (MongoDB)

function solve(db) {
  db.students.insertMany([{name: "X", grade: 90}, {name: "Y", grade: 85}, {name: "Z", grade: 95}]);
  return db.students.find({}).sort({ grade: -1 }).limit(1).toArray();
}

Complexity Analysis

Time Complexity O(N) collection scan (O(log N) if index is present on filtered fields).

Space Complexity O(K) where K is the number of returned documents in memory.

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.

Insert Then Query Verification

Medium

Insert 3 new students {name: "X", grade: 90}, {name: "Y", grade: 85}, {name: "Z", grade: 95}, then find the student with the highest grade.

Example Scenarios

1Example 1

Input:

students collection:
[]

Output:

_id	name	grade
id_w3o976ky9	Z	95

Explanation:

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

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Query Results (JSON)

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