Unwind the `tags` array from each post in the `posts` collection so each tag becomes its own document.
Problem Statement
Examples
Input: posts collection: +-----+--------+-----------------------------------+ | _id | title | tags | +-----+--------+-----------------------------------+ | 1 | Post A | ["mongodb","nosql"] | | 2 | Post B | ["javascript","nodejs","mongodb"] | +-----+--------+-----------------------------------+
Output: +-----+--------+------------+ | _id | title | tags | +-----+--------+------------+ | 1 | Post A | mongodb | | 1 | Post A | nosql | | 2 | Post B | javascript | | 2 | Post B | nodejs | | 2 | Post B | mongodb | +-----+--------+------------+
Explanation: Documents containing the matching array elements are selected from the collection.
Complexity
Time Complexity: -
Space Complexity: -
Hints
Editorial & Approach
Problem Overview & Intuition
To solve "Unwind an Array ($unwind)", we query the MongoDB document store. The goal is to unwind the `tags` array from each post in the `posts` collection so each tag becomes its own document. Using an aggregation pipeline, the database engine filters and structures the BSON documents efficiently.
Step-by-Step Approach
- Identify Target Collection: Access the collection through the
dbinstance. - Construct Query / Pipeline: Build the aggregation stages ($match, $group, $sort, etc.).
- Resolve Cursor: Invoke
.toArray()to transform the query cursor into the required array of documents.
Optimal Implementation (MongoDB)
function solve(db) {
return db.posts.aggregate([{ $unwind: "$tags" }]);
}
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.