🎯 Output Prediction Practice
Predict MongoDB Query Results - Master Mental Execution
🎓 About This Practice
Output prediction is a critical skill for MongoDB mastery. Instead of running queries, you'll predict what they return. This trains your mental model of how MongoDB processes queries, which is essential for interviews and debugging production issues.
- Read the data: Study the collection data carefully
- Analyze the query: Break down what each operator does
- Predict mentally: Write down your predicted output
- Check answer: Click "Show Answer" to verify
- Understand why: Read the explanation if you got it wrong
Your Progress
📝 Basic Queries (1-10)
Start with fundamental find() queries and basic filtering.
Collection: students
[
{ _id: 1, name: "Alice", age: 20, grade: "A", city: "NYC" },
{ _id: 2, name: "Bob", age: 22, grade: "B", city: "LA" },
{ _id: 3, name: "Charlie", age: 20, grade: "A", city: "NYC" },
{ _id: 4, name: "Diana", age: 21, grade: "C", city: "Chicago" }
]
Query:
db.students.find({ age: 20 })
What will this query return?
✓ Correct Answer:
[
{ _id: 1, name: "Alice", age: 20, grade: "A", city: "NYC" },
{ _id: 3, name: "Charlie", age: 20, grade: "A", city: "NYC" }
]
📖 Explanation:
The query finds ALL documents where age equals 20. Both Alice and Charlie match this condition, so both documents are returned.
Collection: students (same as above)
Query:
db.students.find({ city: "NYC" }, { name: 1, grade: 1, _id: 0 })
What will this query return?
✓ Correct Answer:
[
{ name: "Alice", grade: "A" },
{ name: "Charlie", grade: "A" }
]
📖 Explanation:
Projection { name: 1, grade: 1, _id: 0 } includes only name and grade fields, and explicitly excludes _id. Only students from NYC are returned.
Collection: products
[
{ _id: 1, name: "Laptop", price: 1200, stock: 5 },
{ _id: 2, name: "Mouse", price: 25, stock: 50 },
{ _id: 3, name: "Keyboard", price: 75, stock: 0 },
{ _id: 4, name: "Monitor", price: 300, stock: 10 }
]
Query:
db.products.findOne({ stock: 0 })
What will this query return?
✓ Correct Answer:
{ _id: 3, name: "Keyboard", price: 75, stock: 0 }
📖 Explanation:
findOne() returns only the FIRST matching document (not an array). Since only Keyboard has stock: 0, it returns that single document.
Collection: products (same as above)
Query:
db.products.find().sort({ price: -1 }).limit(2)
What will this query return?
✓ Correct Answer:
[
{ _id: 1, name: "Laptop", price: 1200, stock: 5 },
{ _id: 4, name: "Monitor", price: 300, stock: 10 }
]
📖 Explanation:
sort({ price: -1 }) sorts by price in descending order (highest first). limit(2) returns only the top 2 results: Laptop ($1200) and Monitor ($300).
Collection: employees
[
{ _id: 1, name: "John", dept: "IT", salary: 80000 },
{ _id: 2, name: "Sarah", dept: "HR", salary: 65000 },
{ _id: 3, name: "Mike", dept: "IT", salary: 90000 },
{ _id: 4, name: "Lisa", dept: "Finance", salary: 75000 }
]
Query:
db.employees.find({ dept: "IT" }).count()
What will this query return?
✓ Correct Answer:
2
📖 Explanation:
count() returns the NUMBER of documents matching the query. John and Mike are both in IT department, so the count is 2.
Collection: books
[
{ _id: 1, title: "MongoDB Guide", author: "Smith", pages: 320 },
{ _id: 2, title: "Node.js Basics", author: "Jones", pages: 280 },
{ _id: 3, title: "React Cookbook", author: "Smith", pages: 450 },
{ _id: 4, title: "Python 101", author: "Chen", pages: 380 }
]
Query:
db.books.find({ author: "Smith" }).sort({ pages: 1 })
What will this query return?
✓ Correct Answer:
[
{ _id: 1, title: "MongoDB Guide", author: "Smith", pages: 320 },
{ _id: 3, title: "React Cookbook", author: "Smith", pages: 450 }
]
📖 Explanation:
First, find all books by Smith (2 books). Then sort by pages in ascending order (1 means ascending). MongoDB Guide (320 pages) comes before React Cookbook (450 pages).
Collection: orders
[
{ _id: 1, customer: "Alice", total: 150, status: "delivered" },
{ _id: 2, customer: "Bob", total: 200, status: "pending" },
{ _id: 3, customer: "Charlie", total: 150, status: "delivered" },
{ _id: 4, customer: "Diana", total: 300, status: "shipped" }
]
Query:
db.orders.find({ total: 150, status: "delivered" })
What will this query return?
✓ Correct Answer:
[
{ _id: 1, customer: "Alice", total: 150, status: "delivered" },
{ _id: 3, customer: "Charlie", total: 150, status: "delivered" }
]
📖 Explanation:
When multiple conditions are in the query object, it's an implicit AND. Documents must match BOTH total: 150 AND status: "delivered".
Collection: movies
[
{ _id: 1, title: "Inception", year: 2010, rating: 8.8 },
{ _id: 2, title: "Interstellar", year: 2014, rating: 8.6 },
{ _id: 3, title: "Tenet", year: 2020, rating: 7.5 },
{ _id: 4, title: "Dunkirk", year: 2017, rating: 7.9 }
]
Query:
db.movies.find().skip(2).limit(2)
What will this query return?
✓ Correct Answer:
[
{ _id: 3, title: "Tenet", year: 2020, rating: 7.5 },
{ _id: 4, title: "Dunkirk", year: 2017, rating: 7.9 }
]
📖 Explanation:
skip(2) skips the first 2 documents (Inception and Interstellar). limit(2) then returns the next 2 documents (Tenet and Dunkirk). This is pagination!
Collection: cars
[
{ _id: 1, brand: "Toyota", model: "Camry", year: 2020 },
{ _id: 2, brand: "Honda", model: "Civic", year: 2021 },
{ _id: 3, brand: "Toyota", model: "Corolla", year: 2020 },
{ _id: 4, brand: "Ford", model: "Mustang", year: 2022 }
]
Query:
db.cars.distinct("brand")
What will this query return?
✓ Correct Answer:
[ "Toyota", "Honda", "Ford" ]
📖 Explanation:
distinct() returns an array of unique values for the specified field. Even though Toyota appears twice, it only appears once in the result.
Collection: inventory
[
{ _id: 1, item: "Notebook", qty: 50, price: 2.5 },
{ _id: 2, item: "Pen", qty: 100, price: 1.0 },
{ _id: 3, item: "Eraser", qty: 75, price: 0.5 },
{ _id: 4, item: "Pencil", qty: 80, price: 0.75 }
]
Query:
db.inventory.find({ qty: { $exists: true }, price: { $exists: true } }).count()
What will this query return?
✓ Correct Answer:
4
📖 Explanation:
$exists: true checks if a field exists. All 4 documents have both qty and price fields, so count returns 4. This query checks for complete documents.
🔧 Query Operators (11-20)
Practice with comparison and logical operators.
Collection: scores
[
{ _id: 1, student: "Alice", score: 85 },
{ _id: 2, student: "Bob", score: 92 },
{ _id: 3, student: "Charlie", score: 78 },
{ _id: 4, student: "Diana", score: 95 },
{ _id: 5, student: "Eve", score: 88 }
]
Query:
db.scores.find({ score: { $gte: 85, $lt: 90 } })
What will this query return?
✓ Correct Answer:
[
{ _id: 1, student: "Alice", score: 85 },
{ _id: 5, student: "Eve", score: 88 }
]
📖 Explanation:
$gte: 85 means >= 85, $lt: 90 means < 90. This finds scores in range [85, 90). Alice (85) and Eve (88) match. Bob (92) and Diana (95) are too high, Charlie (78) is too low.
Collection: products
[
{ _id: 1, name: "Laptop", price: 1200, category: "Electronics" },
{ _id: 2, name: "Desk", price: 300, category: "Furniture" },
{ _id: 3, name: "Mouse", price: 25, category: "Electronics" },
{ _id: 4, name: "Chair", price: 150, category: "Furniture" }
]
Query:
db.products.find({ $or: [{ price: { $lt: 100 } }, { category: "Furniture" }] })
What will this query return?
✓ Correct Answer:
[
{ _id: 2, name: "Desk", price: 300, category: "Furniture" },
{ _id: 3, name: "Mouse", price: 25, category: "Electronics" },
{ _id: 4, name: "Chair", price: 150, category: "Furniture" }
]
📖 Explanation:
$or returns documents matching ANY condition. Mouse ($25) matches price < $100. Desk and Chair match category "Furniture". Laptop matches neither.
Collection: users
[
{ _id: 1, name: "Alice", age: 25, city: "NYC", active: true },
{ _id: 2, name: "Bob", age: 30, city: "LA", active: false },
{ _id: 3, name: "Charlie", age: 25, city: "NYC", active: true },
{ _id: 4, name: "Diana", age: 28, city: "Chicago", active: true }
]
Query:
db.users.find({ city: { $in: ["NYC", "LA"] }, active: true })
What will this query return?
✓ Correct Answer:
[
{ _id: 1, name: "Alice", age: 25, city: "NYC", active: true },
{ _id: 3, name: "Charlie", age: 25, city: "NYC", active: true }
]
📖 Explanation:
$in: ["NYC", "LA"] matches documents where city is NYC OR LA. Combined with active: true (AND condition), only Alice and Charlie match. Bob is in LA but not active.
Collection: inventory
[
{ _id: 1, item: "Apple", qty: 50 },
{ _id: 2, item: "Banana", qty: 30 },
{ _id: 3, item: "Orange", qty: 40 },
{ _id: 4, item: "Grape", qty: 25 }
]
Query:
db.inventory.find({ qty: { $ne: 30 } })
What will this query return?
✓ Correct Answer:
[
{ _id: 1, item: "Apple", qty: 50 },
{ _id: 3, item: "Orange", qty: 40 },
{ _id: 4, item: "Grape", qty: 25 }
]
📖 Explanation:
$ne (not equal) returns all documents where qty is NOT 30. Apple (50), Orange (40), and Grape (25) all match. Only Banana (30) is excluded.
Collection: orders
[
{ _id: 1, items: ["apple", "banana"], total: 15 },
{ _id: 2, items: ["orange"], total: 10 },
{ _id: 3, items: ["apple", "orange", "grape"], total: 25 },
{ _id: 4, items: ["banana", "grape"], total: 18 }
]
Query:
db.orders.find({ items: { $all: ["apple", "orange"] } })
What will this query return?
✓ Correct Answer:
[
{ _id: 3, items: ["apple", "orange", "grape"], total: 25 }
]
📖 Explanation:
$all requires the array to contain ALL specified elements. Only order 3 has both "apple" AND "orange" in its items array. Order 1 has apple but not orange. Order 2 has orange but not apple.
For operator questions, always read carefully: $gt (>), $gte (>=), $lt (<), $lte (<=), $ne (!=), $in (array contains), $nin (not in array), $all (array contains all).
✏️ Update Operations (21-30)
Predict the result of update operations.
Collection: counter
{ _id: 1, count: 10, name: "visitor" }
Query:
db.counter.updateOne({ _id: 1 }, { $inc: { count: 5 } })
What will the document look like after this update?
✓ Correct Answer:
{ _id: 1, count: 15, name: "visitor" }
📖 Explanation:
$inc increments the field value. count was 10, $inc: { count: 5 } adds 5, making it 15. Other fields remain unchanged.
Collection: products
{ _id: 1, name: "Laptop", price: 1200, tags: ["electronics"] }
Query:
db.products.updateOne({ _id: 1 }, { $push: { tags: "computers" } })
What will the document look like after this update?
✓ Correct Answer:
{ _id: 1, name: "Laptop", price: 1200, tags: ["electronics", "computers"] }
📖 Explanation:
$push appends an element to an array. "computers" is added to the end of the tags array. The array now has two elements.
Collection: users
{ _id: 1, name: "Alice", age: 25, status: "active" }
Query:
db.users.updateOne({ _id: 1 }, { $unset: { status: "" } })
What will the document look like after this update?
✓ Correct Answer:
{ _id: 1, name: "Alice", age: 25 }
📖 Explanation:
$unset removes the specified field from the document. The status field is completely removed. The value in $unset doesn't matter (can be "", 1, true, etc.).
📊 Aggregation Pipelines (31-40)
Predict aggregation results.
Collection: sales
[
{ _id: 1, item: "A", quantity: 5, price: 10 },
{ _id: 2, item: "B", quantity: 3, price: 15 },
{ _id: 3, item: "A", quantity: 2, price: 10 },
{ _id: 4, item: "C", quantity: 4, price: 20 }
]
Query:
db.sales.aggregate([
{
$group: {
_id: "$item",
totalQty: { $sum: "$quantity" }
}
}
])
What will this aggregation return?
✓ Correct Answer:
[
{ _id: "A", totalQty: 7 },
{ _id: "B", totalQty: 3 },
{ _id: "C", totalQty: 4 }
]
📖 Explanation:
$group groups by item. For item "A", there are 2 documents (qty 5 and 2), so totalQty = 5 + 2 = 7. Item "B" has qty 3, item "C" has qty 4.
🎉 Keep Practicing!
Output prediction is one of the best ways to internalize MongoDB behavior. The more you practice, the faster you'll be able to write correct queries on the first try!
Next Steps: Try writing the queries in MongoDB Shell to verify your predictions. The hands-on practice solidifies your learning!