$sum accumulator in MongoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the $sum accumulator do in MongoDB aggregation?

It adds up all the numeric values from the documents in a group and returns the total sum.

beginner

How do you use $sum to count the number of documents in a group?

Use $sum: 1 inside $group stage to add 1 for each document, effectively counting them.

intermediate

Can $sum be used with non-numeric fields?

No, $sum only works with numeric values. Non-numeric values will cause errors or be ignored.

beginner

Example: What does this aggregation do?

{ $group: { _id: "$category", total: { $sum: "$price" } } }

It groups documents by the category field and calculates the total sum of the price field for each category.

intermediate

What happens if you use $sum with a field that sometimes is missing in documents?

Missing fields are treated as null and do not add to the sum. Only existing numeric values are summed.

What is the purpose of the $sum accumulator in MongoDB?

A To sort documents by a field

B To find the average of numeric values

C To add numeric values in grouped documents

D To count the number of fields in a document

$sum adds numeric values from documents in a group to get a total sum.

How can you count documents using $sum in an aggregation?

A Use <code>$sum: 1</code>

B Use <code>$sum: "$field"</code>

C Use <code>$sum: null</code>

D Use <code>$sum: true</code>

Using $sum: 1 adds 1 for each document, counting them.

What happens if $sum is used on a non-numeric field?

A It throws an error or ignores non-numeric values

B It sums the values as strings

C It converts values to numbers automatically

D It counts the number of documents

$sum requires numeric values; non-numeric values cause errors or are ignored.

In this aggregation, what does { $sum: "$price" } do?

{ $group: { _id: "$category", total: { $sum: "$price" } } }

A Counts documents per category

B Finds the max price per category

C Sorts categories by price

D Sums the price values per category

It sums the price field values for each category.

If some documents lack the field used in $sum, what happens?

A Missing fields count as zero in the sum

B Missing fields are ignored and do not add to the sum

C The aggregation fails

D The sum includes null values

Missing fields are treated as null and do not add to the sum.

Explain how the $sum accumulator works in MongoDB aggregation and give an example use case.

Think about adding numbers or counting items in groups.

What should you be careful about when using $sum with fields that might be missing or non-numeric?

Consider data types and missing data.

Practice

1. What does the $sum accumulator do in a MongoDB aggregation pipeline?

easy

A. Adds values together or counts documents within groups

B. Finds the average value of a field

C. Sorts documents in ascending order

D. Filters documents based on a condition

Solution

1. Step 1: Understand the role of $sum

   The $sum accumulator adds numeric values or counts documents when used in a $group stage.

2. Step 2: Compare with other accumulators

   Unlike $avg which calculates averages, $sum only totals values or counts documents.

3. Final Answer:

   Adds values together or counts documents within groups -> Option A

4. Quick Check:

   $sum = Adds or counts [OK]

Hint: Remember: $sum totals numbers or counts docs [OK]

Common Mistakes:

• Confusing $sum with $avg
• Thinking $sum sorts data
• Assuming $sum filters documents

2. Which of the following is the correct syntax to sum the field price in a $group stage?

easy

A. { $group: { _id: null, total: { $sum: "price" } } }

B. { $group: { _id: null, total: { $sum: "$price" } } }

C. { $group: { _id: null, total: { $sum: price } } }

D. { $group: { _id: null, total: { sum: "$price" } } }

Solution

1. Step 1: Identify correct field reference syntax

   In MongoDB aggregation, field names must be prefixed with "$" inside expressions, so "$price" is correct.

2. Step 2: Check accumulator syntax

   The accumulator must be $sum, not sum, and the value must be a string with "$" prefix.

3. Final Answer:

   { $group: { _id: null, total: { $sum: "$price" } } } -> Option B

4. Quick Check:

   Use $sum with "$field" syntax [OK]

Hint: Use "$field" inside $sum in $group [OK]

Common Mistakes:

• Omitting the $ before field name
• Using sum instead of $sum
• Not quoting the field name

3. Given the collection documents:

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

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

{ "category": "B", "value": 5 }

What will be the output of this aggregation?

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

medium

A. [{ "_id": "A", "totalValue": 30 }, { "_id": "B", "totalValue": 5 }]

B. [{ "_id": "A", "totalValue": 10 }, { "_id": "B", "totalValue": 5 }]

C. [{ "_id": "A", "totalValue": 20 }, { "_id": "B", "totalValue": 5 }]

D. [{ "_id": null, "totalValue": 35 }]

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 per group

   For category "A": 10 + 20 = 30; for category "B": 5.

3. Final Answer:

   [{ "_id": "A", "totalValue": 30 }, { "_id": "B", "totalValue": 5 }] -> Option A

4. Quick Check:

   Sum values per category [OK]

Hint: Sum values grouped by _id field [OK]

Common Mistakes:

• Summing without grouping
• Using null _id causing single group
• Adding only one document's value

4. Consider this aggregation pipeline:

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

What is the error in this pipeline?

medium

A. The _id field cannot be a string

B. Missing $group stage

C. Cannot use $sum inside $group

D. Field name 'value' should be quoted and prefixed with $ inside $sum

Solution

1. Step 1: Check field reference inside $sum

   The field 'value' must be referenced as "$value" (string with $ prefix) inside $sum.

2. Step 2: Confirm correct $group usage

   The $group stage is present and _id is correctly set to "$type".

3. Final Answer:

   Field name 'value' should be quoted and prefixed with $ inside $sum -> Option D

4. Quick Check:

   Use "$field" inside $sum [OK]

Hint: Always quote and prefix field with $ inside $sum [OK]

Common Mistakes:

• Using unquoted field names inside $sum
• Thinking $sum can't be used in $group
• Misunderstanding _id usage

5. You have a collection of sales documents with fields store and amount. You want to find the total sales per store but only for stores with total sales above 1000. Which aggregation pipeline correctly uses $sum and filters the results?

hard

A. [{ $match: { amount: { $gt: 1000 } } }, { $group: { _id: "$store", totalSales: { $sum: "$amount" } } }]

B. [{ $group: { _id: "$store", totalSales: { $sum: "$amount" } } }, { $match: { amount: { $gt: 1000 } } }]

C. [{ $group: { _id: "$store", totalSales: { $sum: "$amount" } } }, { $match: { totalSales: { $gt: 1000 } } }]

D. [{ $group: { _id: "$store", totalSales: { $sum: "$amount" } } }, { $match: { _id: { $gt: 1000 } } }]

Solution

1. Step 1: Group sales by store and sum amounts

   The first stage groups documents by "store" and sums the "amount" field into "totalSales".

2. Step 2: Filter groups with totalSales greater than 1000

   The second stage uses $match on the aggregated field "totalSales" to keep only stores with totals above 1000.

3. Final Answer:

   [{ $group: { _id: "$store", totalSales: { $sum: "$amount" } } }, { $match: { totalSales: { $gt: 1000 } } }] -> Option C

4. Quick Check:

   Group then filter on sum field [OK]

Hint: Group first, then filter on summed field [OK]

Common Mistakes:

• Filtering before grouping
• Filtering on original amount instead of totalSales
• Filtering on wrong field name