Docs Home → Develop Applications → MongoDB Manual

# $sum (aggregation)

On this page

## Definition

*Changed in version 5.0*.

Calculates and returns the collective sum of numeric values.
`$sum`

ignores non-numeric values.

`$sum`

is available in these stages:

`$addFields`

(Available starting in MongoDB 3.4)`$replaceRoot`

(Available starting in MongoDB 3.4)`$replaceWith`

(Available starting in MongoDB 4.2)`$set`

(Available starting in MongoDB 4.2)`$setWindowFields`

(Available starting in MongoDB 5.0)

## Compatibility

You can use `$sum`

for deployments hosted in the following
environments:

MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud

MongoDB Enterprise: The subscription-based, self-managed version of MongoDB

MongoDB Community: The source-available, free-to-use, and self-managed version of MongoDB

## Syntax

When used in the `$bucket`

, `$bucketAuto`

,
`$group`

, and `$setWindowFields`

stages,
`$sum`

has this syntax:

{ $sum: <expression> }

When used in other supported stages, `$sum`

has one of
two syntaxes:

`$sum`

has one specified expression as its operand:{ $sum: <expression> } `$sum`

has a list of specified expressions as its operand:{ $sum: [ <expression1>, <expression2> ... ] }

For more information on expressions, see Expression Operators.

## Behavior

### Result Data Type

The result will have the same type as the input except when it cannot be represented accurately in that type. In these cases:

A 32-bit integer will be converted to a 64-bit integer if the result is representable as a 64-bit integer.

A 32-bit integer will be converted to a double if the result is not representable as a 64-bit integer.

A 64-bit integer will be converted to double if the result is not representable as a 64-bit integer.

### Non-Numeric or Non-Existent Fields

If used on a field that contains both numeric and non-numeric values,
`$sum`

ignores the non-numeric values and returns the sum of the
numeric values.

If used on a field that does not exist in any document in the collection,
`$sum`

returns `0`

for that field.

If all operands are non-numeric, `$sum`

returns `0`

.

### Array Operand

In the `$group`

stage, if the expression resolves to an
array, `$sum`

treats the operand as a non-numerical value.

In the other supported stages:

With a single expression as its operand, if the expression resolves to an array,

`$sum`

traverses into the array to operate on the numerical elements of the array to return a single value.With a list of expressions as its operand, if any of the expressions resolves to an array,

`$sum`

does**not**traverse into the array but instead treats the array as a non-numerical value.

## Examples

### Use in `$group`

Stage

Consider a `sales`

collection with the following documents:

{ "_id" : 1, "item" : "abc", "price" : 10, "quantity" : 2, "date" : ISODate("2014-01-01T08:00:00Z") } { "_id" : 2, "item" : "jkl", "price" : 20, "quantity" : 1, "date" : ISODate("2014-02-03T09:00:00Z") } { "_id" : 3, "item" : "xyz", "price" : 5, "quantity" : 5, "date" : ISODate("2014-02-03T09:05:00Z") } { "_id" : 4, "item" : "abc", "price" : 10, "quantity" : 10, "date" : ISODate("2014-02-15T08:00:00Z") } { "_id" : 5, "item" : "xyz", "price" : 5, "quantity" : 10, "date" : ISODate("2014-02-15T09:05:00Z") }

Grouping the documents by the day and the year of the `date`

field,
the following operation uses the `$sum`

accumulator to compute the
total amount and the count for each group of documents.

db.sales.aggregate( [ { $group: { _id: { day: { $dayOfYear: "$date"}, year: { $year: "$date" } }, totalAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } }, count: { $sum: 1 } } } ] )

The operation returns the following results:

{ "_id" : { "day" : 46, "year" : 2014 }, "totalAmount" : 150, "count" : 2 } { "_id" : { "day" : 34, "year" : 2014 }, "totalAmount" : 45, "count" : 2 } { "_id" : { "day" : 1, "year" : 2014 }, "totalAmount" : 20, "count" : 1 }

Using `$sum`

on a non-existent field returns a value of `0`

.
The following operation attempts to `$sum`

on `qty`

:

db.sales.aggregate( [ { $group: { _id: { day: { $dayOfYear: "$date"}, year: { $year: "$date" } }, totalAmount: { $sum: "$qty" }, count: { $sum: 1 } } } ] )

The operation returns:

{ "_id" : { "day" : 46, "year" : 2014 }, "totalAmount" : 0, "count" : 2 } { "_id" : { "day" : 34, "year" : 2014 }, "totalAmount" : 0, "count" : 2 } { "_id" : { "day" : 1, "year" : 2014 }, "totalAmount" : 0, "count" : 1 }

The `$count`

aggregation accumulator can be used in place of
`{ $sum : 1 }`

in the `$group`

stage.

## Tip

### See also:

### Use in `$project`

Stage

A collection `students`

contains the following documents:

{ "_id": 1, "quizzes": [ 10, 6, 7 ], "labs": [ 5, 8 ], "final": 80, "midterm": 75 } { "_id": 2, "quizzes": [ 9, 10 ], "labs": [ 8, 8 ], "final": 95, "midterm": 80 } { "_id": 3, "quizzes": [ 4, 5, 5 ], "labs": [ 6, 5 ], "final": 78, "midterm": 70 }

The following example uses the `$sum`

in the
`$project`

stage to calculate the total quiz scores, the
total lab scores, and the total of the final and the midterm:

db.students.aggregate([ { $project: { quizTotal: { $sum: "$quizzes"}, labTotal: { $sum: "$labs" }, examTotal: { $sum: [ "$final", "$midterm" ] } } } ])

The operation results in the following documents:

{ "_id" : 1, "quizTotal" : 23, "labTotal" : 13, "examTotal" : 155 } { "_id" : 2, "quizTotal" : 19, "labTotal" : 16, "examTotal" : 175 } { "_id" : 3, "quizTotal" : 14, "labTotal" : 11, "examTotal" : 148 }

### Use in `$setWindowFields`

Stage

*New in version 5.0*.

Create a `cakeSales`

collection that contains cake sales in the states
of California (`CA`

) and Washington (`WA`

):

db.cakeSales.insertMany( [ { _id: 0, type: "chocolate", orderDate: new Date("2020-05-18T14:10:30Z"), state: "CA", price: 13, quantity: 120 }, { _id: 1, type: "chocolate", orderDate: new Date("2021-03-20T11:30:05Z"), state: "WA", price: 14, quantity: 140 }, { _id: 2, type: "vanilla", orderDate: new Date("2021-01-11T06:31:15Z"), state: "CA", price: 12, quantity: 145 }, { _id: 3, type: "vanilla", orderDate: new Date("2020-02-08T13:13:23Z"), state: "WA", price: 13, quantity: 104 }, { _id: 4, type: "strawberry", orderDate: new Date("2019-05-18T16:09:01Z"), state: "CA", price: 41, quantity: 162 }, { _id: 5, type: "strawberry", orderDate: new Date("2019-01-08T06:12:03Z"), state: "WA", price: 43, quantity: 134 } ] )

This example uses `$sum`

in the `$setWindowFields`

stage to output the sum of the `quantity`

of cakes sold in each
`state`

:

db.cakeSales.aggregate( [ { $setWindowFields: { partitionBy: "$state", sortBy: { orderDate: 1 }, output: { sumQuantityForState: { $sum: "$quantity", window: { documents: [ "unbounded", "current" ] } } } } } ] )

In the example:

`partitionBy: "$state"`

partitions the documents in the collection by`state`

. There are partitions for`CA`

and`WA`

.`sortBy: { orderDate: 1 }`

sorts the documents in each partition by`orderDate`

in ascending order (`1`

), so the earliest`orderDate`

is first.

`output`

sets the`sumQuantityForState`

field to the sum of the`quantity`

values using`$sum`

that is run in a documents window.The window contains documents between an

`unbounded`

lower limit and the`current`

document in the output. This means`$sum`

returns the sum of the`quantity`

values for the documents between the beginning of the partition and the current document.

In this output, the sum of the `quantity`

values for `CA`

and `WA`

is shown in the `sumQuantityForState`

field:

{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"), "state" : "CA", "price" : 41, "quantity" : 162, "sumQuantityForState" : 162 } { "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"), "state" : "CA", "price" : 13, "quantity" : 120, "sumQuantityForState" : 282 } { "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"), "state" : "CA", "price" : 12, "quantity" : 145, "sumQuantityForState" : 427 } { "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"), "state" : "WA", "price" : 43, "quantity" : 134, "sumQuantityForState" : 134 } { "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"), "state" : "WA", "price" : 13, "quantity" : 104, "sumQuantityForState" : 238 } { "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"), "state" : "WA", "price" : 14, "quantity" : 140, "sumQuantityForState" : 378 }