Skip the first 2 sensors from the `sensors` collection and return the rest.

Problem Statement

<p>Skip the first 2 <code>sensors</code> from the <code>sensors</code> collection and return the rest.</p>

Examples

Input: sensors collection: +-----+-------------+-------+ | _id | type | value | +-----+-------------+-------+ | 1 | temperature | 22.5 | | 2 | humidity | 65 | | 3 | pressure | 1013 | | 4 | temperature | 23.1 | +-----+-------------+-------+

Output: +-----+-------------+-------+ | _id | type | value | +-----+-------------+-------+ | 3 | pressure | 1013 | | 4 | temperature | 23.1 | +-----+-------------+-------+

Explanation: The query restricts and skips documents to return the specified subset.

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 "Skip Results", we query the MongoDB document store. The goal is to skip the first 2 sensors from the `sensors` collection and return the rest. 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.sensors.find({}).skip(2).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.

Skip Results

Easy

Skip the first 2 sensors from the sensors collection and return the rest.

Example Scenarios

1Example 1

Input:

sensors collection

_id	type	value
1	temperature	22.5
2	humidity	65
3	pressure	1013
4	temperature	23.1

Output:

_id	type	value
3	pressure	1013
4	temperature	23.1

Explanation:

The query restricts and skips documents to return the specified subset.

MongoDB Editor

Loading Editor...

Query Results (JSON)

Run your MongoDB code to see results here.