$accumulator (aggregation)
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Definition
$accumulator
New in version 4.4.
Defines a custom accumulator operator. Accumulators are operators that maintain their state (e.g. totals, maximums, minimums, and related data) as documents progress through the pipeline. Use the
$accumulator
operator to execute your own JavaScript functions to implement behavior not supported by the MongoDB Query Language. See also$function
.$accumulator
is available in these stages:Important
Executing JavaScript inside of an aggregation operator may decrease performance. Only use the
$accumulator
operator if the provided pipeline operators cannot fulfill your application's needs.
Syntax
The $accumulator
operator has this syntax:
{ $accumulator: { init: <code>, initArgs: <array expression>, // Optional accumulate: <code>, accumulateArgs: <array expression>, merge: <code>, finalize: <code>, // Optional lang: <string> } }
Field | Type | Description | ||||
---|---|---|---|---|---|---|
String or Code | Function used to initialize the state. The The
NoteSpilling to disk or running a query on a sharded cluster can
cause the accumulator to be computed as a merge of multiple
sub-accumulations, each of which begins by calling | |||||
Array | Optional. Arguments passed to the
ImportantWhen used in a | |||||
String or Code | Function used to accumulate documents. The The
| |||||
Array | Arguments passed to the
| |||||
String or Code | Function used to merge two internal states. The
| |||||
String or Code | Optional. Function used to update the result of the accumulation. The
| |||||
String | The language used in the ImportantCurrently, the only supported value for |
Behavior
The following steps outline how the $accumulator
operator
processes documents:
The operator begins at an initial state, defined by the init function.
For each document, the operator updates the state based on the accumulate function. The accumulate function's first argument is the current state, and additional arguments are be specified in the accumulateArgs array.
When the operator needs to merge multiple intermediate states, it executes the merge function. For more information on when the merge function is called, see Merge Two States with
$merge
.If a finalize function has been defined, once all documents have been processed and the state has been updated accordingly, finalize converts the state to a final output.
Merge Two States with $merge
As part of its internal operations, the $accumulator
operator
may need to merge two separate, intermediate states. The merge function specifies how the operator should merge
two states.
For example, $accumulator
may need to combine two states when:
$accumulator
is run on a sharded cluster. The operator needs to merge the results from each shard to obtain the final result.A single
$accumulator
operation exceeds its specified memory limit. If you specify theallowDiskUse
option, the operator stores the in-progress operation on disk and finishes the operation in memory. Once the operation finishes, the results from disk and memory are merged together using the merge function.
Note
The merge function always merges two states at a time. In the event that more than two states must be merged, the resulting merge of two states is merged with a single state. This process repeats until all states are merged.
Javascript Enabled
To use $accumulator
, you must have server-side scripting
enabled.
If you do not use $accumulator
(or $function
,
$where
, or mapReduce
), disable server-side
scripting:
For a
mongod
instance, seesecurity.javascriptEnabled
configuration option or--noscripting
command-line option.For a
mongos
instance, seesecurity.javascriptEnabled
configuration option or the--noscripting
command-line option starting in MongoDB 4.4.In earlier versions, MongoDB does not allow JavaScript execution onmongos
instances.
Unsupported Array and String Functions
MongoDB 6.0 upgrades the internal JavaScript engine used for
server-side JavaScript,
$accumulator
, $function
, and $where
expressions and from MozJS-60 to MozJS-91. Several deprecated,
non-standard array and string functions that existed in MozJS-60 are
removed in MozJS-91.
For the complete list of removed array and string functions, see the 6.0 compatibility notes.
Examples
Use $accumulator
to Implement the $avg
Operator
Note
This example walks through using the $accumulator
operator
to implement the $avg
operator, which is already supported
by MongoDB. The goal of this example is not to implement new
functionality, but to illustrate the behavior and syntax of the
$accumulator
operator with familiar logic.
In mongosh
, create a sample collection named
books
with the following documents:
db.books.insertMany([ { "_id" : 8751, "title" : "The Banquet", "author" : "Dante", "copies" : 2 }, { "_id" : 8752, "title" : "Divine Comedy", "author" : "Dante", "copies" : 1 }, { "_id" : 8645, "title" : "Eclogues", "author" : "Dante", "copies" : 2 }, { "_id" : 7000, "title" : "The Odyssey", "author" : "Homer", "copies" : 10 }, { "_id" : 7020, "title" : "Iliad", "author" : "Homer", "copies" : 10 } ])
The following operation groups
the documents by
author
, and uses $accumulator
to compute the average
number of copies across books for each author:
db.books.aggregate([ { $group : { _id : "$author", avgCopies: { $accumulator: { init: function() { // Set the initial state return { count: 0, sum: 0 } }, accumulate: function(state, numCopies) { // Define how to update the state return { count: state.count + 1, sum: state.sum + numCopies } }, accumulateArgs: ["$copies"], // Argument required by the accumulate function merge: function(state1, state2) { // When the operator performs a merge, return { // add the fields from the two states count: state1.count + state2.count, sum: state1.sum + state2.sum } }, finalize: function(state) { // After collecting the results from all documents, return (state.sum / state.count) // calculate the average }, lang: "js" } } } } ])
Result
This operation returns the following result:
{ "_id" : "Dante", "avgCopies" : 1.6666666666666667 } { "_id" : "Homer", "avgCopies" : 10 }
Behavior
The $accumulator
defines an initial state where count
and sum
are both set to 0
. For each document that the
$accumulator
processes, it updates the state by:
Incrementing the
count
by 1 andAdding the values of the document's
copies
field to thesum
. The accumulate function can access thecopies
field because it is passed in the accumulateArgs field.
With each document that is processed, the accumulate function returns the updated state.
Once all documents have been processed, the
finalize function divides the sum
of
the copies by the count
of documents to obtain the average. This
removes the need to keep a running computed average, since the
finalize function receives the cumulative
sum
and count
of all documents.
Comparison with $avg
This operation is equivalent to the following pipeline, which uses the
$avg
operator:
db.books.aggregate([ { $group : { _id : "$author", avgCopies: { $avg: "$copies" } } } ])
Use initArgs
to Vary the Initial State by Group
You can use the initArgs option in
to vary the initial state of $accumulator
. This can be
useful if you want to, for example:
Use the value of a field which is not in your state to affect your state, or
Set the initial state to a different value based on the group being processed.
In mongosh
, create a sample collection named
restaurants
with the following documents:
db.restaurants.insertMany([ { "_id" : 1, "name" : "Food Fury", "city" : "Bettles", "cuisine" : "American" }, { "_id" : 2, "name" : "Meal Macro", "city" : "Bettles", "cuisine" : "Chinese" }, { "_id" : 3, "name" : "Big Crisp", "city" : "Bettles", "cuisine" : "Latin" }, { "_id" : 4, "name" : "The Wrap", "city" : "Onida", "cuisine" : "American" }, { "_id" : 5, "name" : "Spice Attack", "city" : "Onida", "cuisine" : "Latin" }, { "_id" : 6, "name" : "Soup City", "city" : "Onida", "cuisine" : "Chinese" }, { "_id" : 7, "name" : "Crave", "city" : "Pyote", "cuisine" : "American" }, { "_id" : 8, "name" : "The Gala", "city" : "Pyote", "cuisine" : "Chinese" } ])
Suppose an application allows users to query this data to find
restaurants. It may be useful to show more results for
the city where the user lives. For this example, we assume that the
user's city is called in a variable called userProfileCity
.
The following aggregation pipeline groups
the
documents by city
. The operation uses the $accumulator
to display a different number of results from each city depending on
whether the restaurant's city matches the city in the user's profile:
Note
1 db.restaurants.aggregate([ 2 { 3 $group : 4 { 5 _id : { city: "$city" }, 6 restaurants: 7 { 8 $accumulator: 9 { 10 init: function(city, userProfileCity) { // Set the initial state 11 return { 12 max: city === userProfileCity ? 3 : 1, // If the group matches the user's city, return 3 restaurants 13 restaurants: [] // else, return 1 restaurant 14 } 15 }, 16 17 initArgs: ["$city", <userProfileCity>], // Argument to pass to the init function 18 19 accumulate: function(state, restaurantName) { // Define how to update the state 20 if (state.restaurants.length < state.max) { 21 state.restaurants.push(restaurantName); 22 } 23 return state; 24 }, 25 26 accumulateArgs: ["$name"], // Argument required by the accumulate function 27 28 merge: function(state1, state2) { 29 return { 30 max: state1.max, 31 restaurants: state1.restaurants.concat(state2.restaurants).slice(0, state1.max) 32 } 33 }, 34 35 finalize: function(state) { // Adjust the state to only return field we need 36 return state.restaurants 37 } 38 39 lang: "js" 40 } 41 } 42 } 43 } 44 ])
Results
If the value of userProfileCity
is Bettles
, this operation
returns the following result:
{ "_id" : { "city" : "Bettles" }, "restaurants" : { "restaurants" : [ "Food Fury", "Meal Macro", "Big Crisp" ] } } { "_id" : { "city" : "Onida" }, "restaurants" : { "restaurants" : [ "The Wrap" ] } } { "_id" : { "city" : "Pyote" }, "restaurants" : { "restaurants" : [ "Crave" ] } }
If the value of userProfileCity
is Onida
, this operation
returns the following result:
{ "_id" : { "city" : "Bettles" }, "restaurants" : { "restaurants" : [ "Food Fury" ] } } { "_id" : { "city" : "Onida" }, "restaurants" : { "restaurants" : [ "The Wrap", "Spice Attack", "Soup City" ] } } { "_id" : { "city" : "Pyote" }, "restaurants" : { "restaurants" : [ "Crave" ] } }
If the value of userProfileCity
is Pyote
, this operation
returns the following result:
{ "_id" : { "city" : "Bettles" }, "restaurants" : { "restaurants" : [ "Food Fury" ] } } { "_id" : { "city" : "Onida" }, "restaurants" : { "restaurants" : [ "The Wrap" ] } } { "_id" : { "city" : "Pyote" }, "restaurants" : { "restaurants" : [ "Crave", "The Gala" ] } }
If the value of userProfileCity
is any other value, this operation
returns the following result:
{ "_id" : { "city" : "Bettles" }, "restaurants" : { "restaurants" : [ "Food Fury" ] } } { "_id" : { "city" : "Onida" }, "restaurants" : { "restaurants" : [ "The Wrap" ] } } { "_id" : { "city" : "Pyote" }, "restaurants" : { "restaurants" : [ "Crave" ] } }
Behavior
The init function defines an initial state
containing max
and restaurants
fields. The max
field sets
the maximum number of restaurants for that particular group. If the
document's city
field matches userProfileCity
, that group
contains a maximum of 3 restaurants. Otherwise, if the document _id
does not match userProfileCity
, the group contains at most a single
restaurant. The init function receives both
the city
userProfileCity
arguments from the initArgs array.
For each document that the $accumulator
processes, it pushes
the name
of the restaurant to the restaurants
array, provided
that name would not put the length of restaurants
over the max
value. With each document that is processed, the accumulate function returns the updated state.
The merge function defines how to merge two
states. The function concatenates the restaurant
arrays from each
state together, and the length of the resulting array is limited using
the slice()
method to ensure that it does not exceed the max
value.
Once all documents have been processed, the finalize function modifies the resulting state to only
return the names of the restaurants. Without this function, the max
field would also be included in the output, which does not fulfill any
needs for the application.