Find all properties with `bedrooms` greater than or equal to `3` AND `price` less than `500000`.

Problem Statement

<p>Find all properties with <code>bedrooms</code> greater than or equal to <code>3</code> AND <code>price</code> less than <code>500000</code>.</p>

Examples

Input: properties collection: +-----+----------+----------+--------+ | _id | address | bedrooms | price | +-----+----------+----------+--------+ | 1 | 123 Main | 4 | 450000 | | 2 | 456 Oak | 2 | 300000 | | 3 | 789 Pine | 3 | 600000 | | 4 | 101 Elm | 5 | 350000 | +-----+----------+----------+--------+

Output: +-----+----------+----------+--------+ | _id | address | bedrooms | price | +-----+----------+----------+--------+ | 1 | 123 Main | 4 | 450000 | | 4 | 101 Elm | 5 | 350000 | +-----+----------+----------+--------+

Explanation: The query retrieves all documents from the collection that satisfy the specified filter criteria.

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: Use comparison operators ($gt, $gte, $lt, $lte) to filter documents based on numeric or date ranges. 💡 Hint 2: Construct the filter condition: { fieldName: { $gt: value } } inside db.<collection>.find(...). 💡 Hint 3: Chain projection or sorting if requested, and invoke .toArray() to produce the result array.

Editorial & Approach

Problem Overview & Intuition

To solve "Logical AND ($and)", we query the MongoDB document store. The goal is to find all properties with `bedrooms` greater than or equal to `3` and `price` less than `500000`. 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.properties.find({ $and: [{ bedrooms: { $gte: 3 } }, { price: { $lt: 500000 } }] }).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.

Logical AND ($and)

Easy

Find all properties with bedrooms greater than or equal to 3 AND price less than 500000.

Example Scenarios

1Example 1

Input:

properties collection

_id	address	bedrooms	price
1	123 Main	4	450000
2	456 Oak	2	300000
3	789 Pine	3	600000
4	101 Elm	5	350000

Output:

_id	address	bedrooms	price
1	123 Main	4	450000
4	101 Elm	5	350000

Explanation:

The query retrieves all documents from the collection that satisfy the specified filter criteria.

MongoDB Editor

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Query Results (JSON)

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