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Database Manual

Aggregation Operations

Reference

Operators

$addToSet (aggregation)

Definition

Changed in version 5.0.

$addToSet

$addToSet returns an array of all unique values that results from applying an expression to each document in a group.

The order of the elements in the returned array is unspecified.

$addToSet is available in these stages:

$bucket
$bucketAuto
$group
$setWindowFields (Available starting in MongoDB 5.0)

Syntax

$addToSet syntax:

{ $addToSet: <expression> }

For more information on expressions, see Expression Operators.

Behavior

If the value of the expression is an array, $addToSet appends the whole array as a single element.

If the value of the expression is a document, MongoDB determines that the document is a duplicate if another document in the array matches the to-be-added document exactly. Specifically, the existing document has the exact same fields and values in the exact same order.

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("2014-02-15T09:12:00Z") }

Grouping the documents by the day and the year of the date field, the following operation uses the $addToSet accumulator to compute the list of unique items sold for each group:

db.sales.aggregate(
   [
     {
       $group:
         {
           _id: { day: { $dayOfYear: "$date"}, year: { $year: "$date" } },
           itemsSold: { $addToSet: "$item" }
         }
     }
   ]
)

The operation returns the following results:

{ "_id" : { "day" : 46, "year" : 2014 }, "itemsSold" : [ "xyz", "abc" ] }
{ "_id" : { "day" : 34, "year" : 2014 }, "itemsSold" : [ "xyz", "jkl" ] }
{ "_id" : { "day" : 1, "year" : 2014 }, "itemsSold" : [ "abc" ] }

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 $addToSet in the $setWindowFields stage to output the unique cake type sales for each state:

db.cakeSales.aggregate( [
   {
      $setWindowFields: {
         partitionBy: "$state",
         sortBy: { orderDate: 1 },
         output: {
            cakeTypesForState: {
               $addToSet: "$type",
               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 adds each unique cake type to the cakeTypesForState array field using $addToSet that is run in a documents window.
The window contains documents between an unbounded lower limit and the current document. This means $addToSet returns an array containing the unique cake type fields for the documents between the beginning of the partition and the current document.

In this example output, the cake type array for CA and WA is shown in the cakeTypesForState field:

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

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