Find all users that have a `phone` field defined (not null/undefined).
Problem Statement
Examples
Input: users collection: +-----+---------+------------------+----------+ | _id | name | email | phone | +-----+---------+------------------+----------+ | 1 | Alice | alice@test.com | 555-0101 | | 2 | Bob | bob@test.com | null | | 3 | Charlie | charlie@test.com | 555-0303 | +-----+---------+------------------+----------+
Output: +-----+---------+------------------+----------+ | _id | name | email | phone | +-----+---------+------------------+----------+ | 1 | Alice | alice@test.com | 555-0101 | | 3 | Charlie | charlie@test.com | 555-0303 | +-----+---------+------------------+----------+
Explanation: The query retrieves all documents from the collection that satisfy the specified filter criteria.
Complexity
Time Complexity: -
Space Complexity: -
Hints
Editorial & Approach
Problem Overview & Intuition
To solve "Field Exists ($exists)", we query the MongoDB document store. The goal is to find all users that have a `phone` field defined (not null/undefined). 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
dbinstance. - 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.users.find({ phone: { $exists: true } }).toArray();
}Complexity Analysis
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.