Find a single patient document with `_id: "p2"` from the `patients` collection.

Problem Statement

<p>Find a single patient document with <code>_id: "p2"</code> from the <code>patients</code> collection.</p>

Examples

Input: patients collection: +-----+---------+-----+ | _id | name | age | +-----+---------+-----+ | p1 | Alice | 30 | | p2 | Bob | 45 | | p3 | Charlie | 28 | +-----+---------+-----+

Output: +-----+------+-----+ | _id | name | age | +-----+------+-----+ | p2 | Bob | 45 | +-----+------+-----+

Explanation: The query projects only the requested document fields matching the criteria.

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: Use db.<collection>.find(<filter>) to query the documents in the collection. 💡 Hint 2: Pass an empty object {} to retrieve all documents, or specify key-value pairs for exact matching. 💡 Hint 3: Chain .toArray() to resolve the MongoDB cursor into a JavaScript array: return db.<collection>.find(...).toArray();

Editorial & Approach

Problem Overview & Intuition

To solve "Find One Document (findOne)", we query the MongoDB document store. The goal is to find a single patient document with `_id: "p2"` from the `patients` collection. 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) {
  return db.patients.findOne({ _id: "p2" });
}

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.

Find One Document (findOne)

Easy

Find a single patient document with _id: "p2" from the patients collection.

Example Scenarios

1Example 1

Input:

patients collection

_id	name	age
p1	Alice	30
p2	Bob	45
p3	Charlie	28

Output:

_id	name	age
p2	Bob	45

Explanation:

The query projects only the requested document fields matching the criteria.

MongoDB Editor

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Query Results (JSON)

Run your MongoDB code to see results here.