$reduce (aggregation)
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Definition
$reduce
Applies an expression to each element in an array and combines them into a single value.
$reduce
has the following syntax:{ $reduce: { input: <array>, initialValue: <expression>, in: <expression> } } FieldTypeDescriptioninput
arrayCan be any valid expression that resolves to an array. For more information on expressions, see Expression Operators.
If the argument resolves to a value of
null
or refers to a missing field,$reduce
returnsnull
.If the argument does not resolve to an array or
null
nor refers to a missing field,$reduce
returns an error.initialValue
expressionThe initial cumulativevalue
set beforein
is applied to the first element of theinput
array.in
expressionA valid expression that
$reduce
applies to each element in theinput
array in left-to-right order. Wrap theinput
value with$reverseArray
to yield the equivalent of applying the combining expression from right-to-left.During evaluation of the
in
expression, two variables will be available:If
input
resolves to an empty array,$reduce
returnsinitialValue
.
Example | Results | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
| "abc" | ||||||||||
| { "sum" : 15, "product" : 48 } | ||||||||||
| [ 1, 2, 3, 4, 5, 6 ] |
Examples
Multiplication
Probability
A collection named events
contains the events of a probability
experiment. Each experiment can have multiple events
, such as
rolling a die several times or drawing several cards (without replacement)
in succession to achieve a desired result. In order to obtain the
overall probability of the experiment, we will need to multiply the
probability of each event in the experiment.
db.events.insertMany( [ { _id : 1, type : "die", experimentId :"r5", description : "Roll a 5", eventNum : 1, probability : 0.16666666666667 }, { _id : 2, type : "card", experimentId :"d3rc", description : "Draw 3 red cards", eventNum : 1, probability : 0.5 }, { _id : 3, type : "card", experimentId :"d3rc", description : "Draw 3 red cards", eventNum : 2, probability : 0.49019607843137 }, { _id : 4, type : "card", experimentId :"d3rc", description : "Draw 3 red cards", eventNum : 3, probability : 0.48 }, { _id : 5, type : "die", experimentId :"r16", description : "Roll a 1 then a 6", eventNum : 1, probability : 0.16666666666667 }, { _id : 6, type : "die", experimentId :"r16", description : "Roll a 1 then a 6", eventNum : 2, probability : 0.16666666666667 }, { _id : 7, type : "card", experimentId :"dak", description : "Draw an ace, then a king", eventNum : 1, probability : 0.07692307692308 }, { _id : 8, type : "card", experimentId :"dak", description : "Draw an ace, then a king", eventNum : 2, probability : 0.07843137254902 } ] )
Steps:
Use
$group
to group by theexperimentId
and use$push
to create an array with the probability of each event.Use
$reduce
with$multiply
to multiply and combine the elements ofprobabilityArr
into a single value and project it.
db.probability.aggregate( [ { $group: { _id: "$experimentId", probabilityArr: { $push: "$probability" } } }, { $project: { description: 1, results: { $reduce: { input: "$probabilityArr", initialValue: 1, in: { $multiply: [ "$$value", "$$this" ] } } } } } ] )
The operation returns the following:
{ _id : "dak", results : 0.00603318250377101 } { _id : "r5", results : 0.16666666666667 } { _id : "r16", results : 0.027777777777778886 } { _id : "d3rc", results : 0.11764705882352879 }
Discounted Merchandise
A collection named clothes
contains the following documents:
db.clothes.insertMany( [ { _id : 1, productId : "ts1", description : "T-Shirt", color : "black", size : "M", price : 20, discounts : [ 0.5, 0.1 ] }, { _id : 2, productId : "j1", description : "Jeans", color : "blue", size : "36", price : 40, discounts : [ 0.25, 0.15, 0.05 ] }, { _id : 3, productId : "s1", description : "Shorts", color : "beige", size : "32", price : 30, discounts : [ 0.15, 0.05 ] }, { _id : 4, productId : "ts2", description : "Cool T-Shirt", color : "White", size : "L", price : 25, discounts : [ 0.3 ] }, { _id : 5, productId : "j2", description : "Designer Jeans", color : "blue", size : "30", price : 80, discounts : [ 0.1, 0.25 ] } ] )
Each document contains a discounts
array containing the currently
available percent-off coupons for each item. If each discount can be
applied to the product once, we can calculate the lowest price by using
$reduce
to apply the following formula for each element in the
discounts
array: (1 - discount) * price.
db.clothes.aggregate( [ { $project: { discountedPrice: { $reduce: { input: "$discounts", initialValue: "$price", in: { $multiply: [ "$$value", { $subtract: [ 1, "$$this" ] } ] } } } } } ] )
The operation returns the following:
{ _id : ObjectId("57c893067054e6e47674ce01"), discountedPrice : 9 } { _id : ObjectId("57c9932b7054e6e47674ce12"), discountedPrice : 24.224999999999998 } { _id : ObjectId("57c993457054e6e47674ce13"), discountedPrice : 24.224999999999998 } { _id : ObjectId("57c993687054e6e47674ce14"), discountedPrice : 17.5 } { _id : ObjectId("57c993837054e6e47674ce15"), discountedPrice : 54 }
String Concatenation
A collection named people
contains the following documents:
db.people.insertMany( [ { _id : 1, name : "Melissa", hobbies : [ "softball", "drawing", "reading" ] }, { _id : 2, name : "Brad", hobbies : [ "gaming", "skateboarding" ] }, { _id : 3, name : "Scott", hobbies : [ "basketball", "music", "fishing" ] }, { _id : 4, name : "Tracey", hobbies : [ "acting", "yoga" ] }, { _id : 5, name : "Josh", hobbies : [ "programming" ] }, { _id : 6, name : "Claire" } ] )
The following example reduces the hobbies
array of strings into a single string
bio
:
db.people.aggregate( [ // Filter to return only non-empty arrays { $match: { "hobbies": { $gt: [ ] } } }, { $project: { name: 1, bio: { $reduce: { input: "$hobbies", initialValue: "My hobbies include:", in: { $concat: [ "$$value", { $cond: { if: { $eq: [ "$$value", "My hobbies include:" ] }, then: " ", else: ", " } }, "$$this" ] } } } } } ] )
The operation returns the following:
{ _id : 1, name : "Melissa", bio : "My hobbies include: softball, drawing, reading" } { _id : 2, name : "Brad", bio : "My hobbies include: gaming, skateboarding" } { _id : 3, name : "Scott", bio : "My hobbies include: basketball, music, fishing" } { _id : 4, name : "Tracey", bio : "My hobbies include: acting, yoga" } { _id : 5, name : "Josh", bio : "My hobbies include: programming" }
Array Concatenation
A collection named matrices
contains the following documents:
db.matrices.insertMany( [ { _id : 1, arr : [ [ 24, 55, 79 ], [ 14, 78, 35 ], [ 84, 90, 3 ], [ 50, 89, 70 ] ] }, { _id : 2, arr : [ [ 39, 32, 43, 7 ], [ 62, 17, 80, 64 ], [ 17, 88, 11, 73 ] ] }, { _id : 3, arr : [ [ 42 ], [ 26, 59 ], [ 17 ], [ 72, 19, 35 ] ] }, { _id : 4 } ] )
Computing a Single Reduction
The following example collapses the two dimensional arrays into a single array collapsed
:
db.arrayconcat.aggregate( [ { $project: { collapsed: { $reduce: { input: "$arr", initialValue: [ ], in: { $concatArrays: [ "$$value", "$$this" ] } } } } } ] )
The operation returns the following:
{ _id : 1, collapsed : [ 24, 55, 79, 14, 78, 35, 84, 90, 3, 50, 89, 70 ] } { _id : 2, collapsed : [ 39, 32, 43, 7, 62, 17, 80, 64, 17, 88, 11, 73 ] } { _id : 3, collapsed : [ 42, 26, 59, 17, 72, 19, 35 ] } { _id : 4, collapsed : null }
Computing a Multiple Reductions
The following example performs the same two dimensional array collapse as the example above, but also creates a new array containing only the first element of each array.
db.arrayconcat.aggregate( [ { $project: { results: { $reduce: { input: "$arr", initialValue: [ ], in: { collapsed: { $concatArrays: [ "$$value.collapsed", "$$this" ] }, firstValues: { $concatArrays: [ "$$value.firstValues", { $slice: [ "$$this", 1 ] } ] } } } } } } ] )
The operation returns the following:
{ _id : 1, results : { collapsed : [ 24, 55, 79, 14, 78, 35, 84, 90, 3, 50, 89, 70 ], firstValues : [ 24, 14, 84, 50 ] } } { _id : 2, results : { collapsed : [ 39, 32, 43, 7, 62, 17, 80, 64, 17, 88, 11, 73 ], firstValues : [ 39, 62, 17 ] } } { _id : 3, results : { collapsed : [ 42, 26, 59, 17, 72, 19, 35 ], firstValues : [ 42, 26, 17, 72 ] } } { _id : 4, results : null }