$group stage for aggregation in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Output of $group with sum accumulator

Given the collection sales with documents:

{ "item": "apple", "qty": 5 }
{ "item": "banana", "qty": 10 }
{ "item": "apple", "qty": 15 }

What is the output of this aggregation?

db.sales.aggregate([{ $group: { _id: "$item", totalQty: { $sum: "$qty" } } }])

MongoDB

db.sales.aggregate([{ $group: { _id: "$item", totalQty: { $sum: "$qty" } } }])

A [{ "_id": "apple", "totalQty": 20 }, { "_id": "banana", "totalQty": 10 }]

B [{ "_id": "apple", "totalQty": 5 }, { "_id": "banana", "totalQty": 10 }, { "_id": "apple", "totalQty": 15 }]

C [{ "_id": null, "totalQty": 30 }]

D [{ "_id": "apple", "totalQty": 15 }, { "_id": "banana", "totalQty": 10 }]

💡 Hint

Think about grouping by the item name and summing quantities for each group.

The $group stage groups documents by the _id field, here the item name. Then it sums the qty values for each group. Apples have qty 5 + 15 = 20, bananas have qty 10.

📝 Syntax

intermediate

Identify the syntax error in $group stage

Which option contains a syntax error in the $group stage of this aggregation pipeline?

db.orders.aggregate([{ $group: { _id: "$customer", total: { $sum: "$amount" } } }])

A { $group: { _id: "$customer", total: { $sum: "$amount" } } }

B { $group: { _id: "$customer", total: { $sum: amount } } }

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D $group: { _id: "$customer", total: { $sum: "$amount" } } }

💡 Hint

Check if the field names are properly quoted as strings.

In option B, $sum is given amount without quotes, which is invalid. Field names must be strings with $ prefix inside quotes.

❓ query_result

advanced

Output of $group with multiple accumulators

Given the collection products with documents:

{ "category": "fruit", "price": 10 }
{ "category": "fruit", "price": 15 }
{ "category": "vegetable", "price": 20 }

What is the output of this aggregation?

db.products.aggregate([{ $group: { _id: "$category", count: { $sum: 1 }, avgPrice: { $avg: "$price" } } }])

MongoDB

db.products.aggregate([{ $group: { _id: "$category", count: { $sum: 1 }, avgPrice: { $avg: "$price" } } }])

A [{ "_id": "fruit", "count": 2, "avgPrice": 12.5 }, { "_id": "vegetable", "count": 1, "avgPrice": 20 }]

B [{ "_id": "fruit", "count": 1, "avgPrice": 12.5 }, { "_id": "vegetable", "count": 1, "avgPrice": 20 }]

C [{ "_id": "fruit", "count": 2, "avgPrice": 25 }, { "_id": "vegetable", "count": 1, "avgPrice": 20 }]

D [{ "_id": null, "count": 3, "avgPrice": 15 }]

💡 Hint

Count counts documents per group, avgPrice averages the price field per group.

The $group groups by category. For fruit, two documents with prices 10 and 15 average to 12.5 and count is 2. Vegetable has one document with price 20.

🔧 Debug

advanced

Why does this $group aggregation return empty results?

Consider this aggregation on collection logs:

db.logs.aggregate([{ $group: { _id: "$level", total: { $sum: "$count" } } }])

But the output is an empty array. The documents look like:

{ "level": "error", "count": 5 }
{ "level": "info", "count": 3 }

What is the most likely reason for empty output?

A The field "count" does not exist in documents, so $sum returns null and no groups form.

B The aggregation pipeline is missing a $match stage to filter documents.

C The field "count" is a string, so $sum fails silently and returns empty.

D The aggregation is correct; empty output means no documents in collection.

💡 Hint

Consider if there are actually documents in the collection matching the pipeline.

Empty output from an aggregation pipeline with no filtering stages ($match, etc.) indicates that the collection has no documents. Even if fields are missing, $group would output groups with accumulators initialized to 0 or null.

🧠 Conceptual

expert

Understanding $group _id field behavior

In MongoDB aggregation, what happens if you set _id to null in the $group stage?

Choose the correct explanation:

A Documents are grouped by a field named "null", which usually does not exist, so output is empty.

B Each document is grouped by its own _id field, so output has same number of documents as input.

C All documents are grouped into a single group, so the output has one document aggregating all input documents.

D The aggregation fails with an error because _id cannot be null in $group.

💡 Hint

Think about grouping all documents together regardless of any field.

Setting _id to null groups all documents into one group, producing a single output document with aggregated values over the entire collection.

Practice

1. What is the main purpose of the $group stage in a MongoDB aggregation pipeline?

easy

A. To project specific fields from documents

B. To filter documents based on a condition

C. To sort documents in ascending or descending order

D. To group documents by a specified key and perform calculations on each group

Solution

1. Step 1: Understand the role of $group

   The $group stage collects documents into groups based on a key defined in the _id field.

2. Step 2: Identify what $group does with groups

   It allows performing calculations like sum, count, or average on each group.

3. Final Answer:

   To group documents by a specified key and perform calculations on each group -> Option D

4. Quick Check:

   $group groups and calculates [OK]

Hint: Remember: $group always groups and aggregates [OK]

Common Mistakes:

• Confusing $group with $match for filtering
• Thinking $group sorts documents
• Assuming $group projects fields without grouping

2. Which of the following is the correct syntax to group documents by the field category and count the number of documents in each group?

easy

A. { $group: { category: "$category", count: { $sum: 1 } } }

B. { $group: { _id: "$category", count: { $sum: 1 } } }

C. { $group: { _id: "$category", count: { $count: 1 } } }

D. { $group: { _id: "$category", count: { $add: 1 } } }

Solution

1. Step 1: Identify the grouping key field

   The grouping key must be assigned to _id, so _id: "$category" is correct.

2. Step 2: Use the correct accumulator for counting

   Counting documents uses $sum: 1 to add 1 for each document in the group.

3. Final Answer:

   { $group: { _id: "$category", count: { $sum: 1 } } } -> Option B

4. Quick Check:

   Group key in _id and count with $sum: 1 [OK]

Hint: Always use _id for group key and $sum: 1 to count [OK]

Common Mistakes:

• Using field name instead of _id for grouping key
• Using $count instead of $sum for counting
• Using $add which is not an accumulator

3. Given the collection documents:

{ "category": "A", "value": 10 }

{ "category": "B", "value": 20 }

{ "category": "A", "value": 15 }

What will be the output of this aggregation?

[{ $group: { _id: "$category", total: { $sum: "$value" } } }]

medium

A. [{ "_id": "A", "total": 25 }, { "_id": "B", "total": 20 }]

B. [{ "_id": "A", "total": 10 }, { "_id": "B", "total": 20 }, { "_id": "A", "total": 15 }]

C. [{ "_id": "A", "total": 15 }, { "_id": "B", "total": 20 }]

D. [{ "_id": null, "total": 45 }]

Solution

1. Step 1: Group documents by category

   Documents with category "A" are grouped together, and category "B" separately.

2. Step 2: Sum the value fields in each group

   For category "A": 10 + 15 = 25; for category "B": 20.

3. Final Answer:

   [{ "_id": "A", "total": 25 }, { "_id": "B", "total": 20 }] -> Option A

4. Quick Check:

   Sum values per category = correct totals [OK]

Hint: Sum values grouped by _id key field [OK]

Common Mistakes:

• Expecting separate documents without grouping
• Summing incorrectly or ignoring grouping
• Using _id: null which groups all documents together

4. Identify the error in this aggregation pipeline stage:

{ $group: { category: "$category", total: { $sum: "$amount" } } }

medium

A. Field names should not be in quotes

B. Incorrect use of $sum operator

C. Missing _id field for grouping key

D. Aggregation pipeline stage must be an array

Solution

1. Step 1: Check for required _id field in $group

   The _id field is mandatory to specify the grouping key.

2. Step 2: Verify other syntax elements

   The $sum operator and field references are correct; only _id is missing.

3. Final Answer:

   Missing _id field for grouping key -> Option C

4. Quick Check:

   _id is required in $group [OK]

Hint: Always include _id in $group stage [OK]

Common Mistakes:

• Omitting the _id field
• Confusing field names with grouping key
• Thinking $sum needs special syntax

5. You have a collection of sales documents with fields store, item, and quantity. You want to find the total quantity sold per store, but only for stores where the total quantity exceeds 100. Which aggregation pipeline correctly achieves this?

hard

A. [{ $group: { _id: "$store", totalQuantity: { $sum: "$quantity" } } }, { $match: { totalQuantity: { $gt: 100 } } }]

B. [{ $match: { quantity: { $gt: 100 } } }, { $group: { _id: "$store", totalQuantity: { $sum: "$quantity" } } }]

C. [{ $group: { _id: "$store", totalQuantity: { $sum: "$quantity" } } }, { $match: { _id: { $gt: 100 } } }]

D. [{ $group: { _id: "$store", totalQuantity: { $sum: "$quantity" } } }, { $sort: { totalQuantity: -1 } }]

Solution

1. Step 1: Group by store and sum quantity

   The $group stage groups documents by store and calculates total quantity sold per store.

2. Step 2: Filter groups where total quantity > 100

   The $match stage after grouping filters groups with totalQuantity greater than 100.

3. Final Answer:

   [{ $group: { _id: "$store", totalQuantity: { $sum: "$quantity" } } }, { $match: { totalQuantity: { $gt: 100 } } }] -> Option A

4. Quick Check:

   Group then filter by aggregated field [OK]

Hint: Filter after grouping using $match on aggregated fields [OK]

Common Mistakes:

• Filtering before grouping which filters documents, not groups
• Filtering on _id instead of aggregated field
• Using $sort instead of filtering