MongoDB $match on object not considering key - mongodb

Please help compose a request.
[{
name: 'Peter',
items: {
a: [1, 2, 3, 6],
b: [0, 1],
c: [4, 1]
},
name: 'Joe',
items: {
d: [2, 3],
e: [0, 1],
},
name: 'Luk',
items: {
f: [0, 1, 8],
},
}]
filter - items.xxx> 5
result - "Peter" and "Luk"

Is this what you are looking for?
db.collection.aggregate([
{ $set: { items: { $objectToArray: "$items" } } },
{
$set: {
items: {
$reduce: {
input: "$items.v",
initialValue: [],
in: { $concatArrays: ["$$this", "$$value"] }
}
}
}
},
{ $match: { items: { $elemMatch: { $gte: 5 } } } },
{ $project: { name: 1 } }
])
Result:
{
"_id" : ObjectId("5e3d7ed0ac00d5ec3a32125f"),
"name" : "Peter"
}
{
"_id" : ObjectId("5e3d7ed0ac00d5ec3a321261"),
"name" : "Luk"
}
If you need the full documents, you can use this one:
db.collection.aggregate([
{
$facet:
{
filter: [
{ $set: { items: { $objectToArray: "$items" } } },
{
$set: {
items: {
$reduce: {
input: "$items.v",
initialValue: [],
in: { $concatArrays: ["$$this", "$$value"] }
}
}
}
},
{ $match: { items: { $elemMatch: { $gte: 5 } } } },
{ $project: { name: 1 } }
],
in: [{ $match: {} }],
}
},
{ $unwind: "$in" },
{ $match: { $expr: { $in: ["$in._id", "$filter._id"] } } },
{ $replaceRoot: { newRoot: "$in" } }
])

Related

MongoDB match computed value

I've created an aggregate query but for some reason it doesn't seem to work for custom fields created in the aggregation pipeline.
return this.repository.mongo().aggregate([
{
$match: { q1_avg: { $regex: baseQuery['value'], $options: 'i' } }, // NOT WORKING
},
{
$group: {
_id: '$product_sku',
id: { $first: "$_id" },
product_name: { $first: '$product_name' },
product_category: { $first: '$product_category' },
product_sku: { $first: '$product_sku' },
q1_cnt: { $sum: 1 },
q1_votes: { $push: "$final_rating" }
},
},
{
$facet: {
pagination: [ { $count: 'total' } ],
data: [
{
$project: {
_id: 1,
id: 1,
product_name: 1,
product_category: 1,
product_sku: 1,
q1_cnt: 1,
q1_votes: {
$filter: {
input: '$q1_votes',
as: 'item',
cond: { $ne: ['$$item', null] }
}
},
},
},
{
$set: {
q1_avg: { $round: [ { $avg: '$q1_votes' }, 2 ] },
}
},
{ $unset: ['q1_votes'] },
{ $skip: skip },
{ $limit: limit },
{ $sort: sortList }
]
}
},
{ $unwind : "$pagination" },
]).next();
q1_avg value is an integer and as far as I know, regex only works with strings. Could that be the reason

mongo / mongoose aggregation pipeline query for survey data

I am trying to write a query to get all of the results of some survey data stored in a mongo. The tricky part is some questions are radio questions with a single answer, and some questions are multi-select type questions, some are values that need to be averaged, so I want to perform different aggregations depending on the type of question.
The results are stored in a schema like this, with each item in the array being a survey response.
[
{
metaData: {
survey: new ObjectId("62206ea0b31be3535abac547")
},
answers: {
'question1': 'a',
'question2': 'a',
'question3': ['a','c'],
'question4': 3
},
createdAt: 2022-03-03T07:30:40.517Z,
},
{
metaData: {
survey: new ObjectId("62206ea0b31be3535abac547"),
},
answers: {
'question1': 'a',
'question2': 'b',
'question3': ['a','c'],
'question4': 2
},
createdAt: 2022-03-03T07:30:40.518Z,
},
{
metaData: {
survey: new ObjectId("62206ea0b31be3535abac547"),
},
answers: {
'question1': 'b',
'question2': 'c',
'question3': ['b']
'question4': 1
},
createdAt: 2022-03-03T07:30:40.518Z,
}
]
question1 and question2 are radio questions, so there can be only 1 answer, whereas question 3 is a multi-select, so the user can have multiple answers. Question 4 is a value that needs to be averaged.
I think there is some way to accomplish this in a single aggregation pipeline with some combination of facets, grouping, filters, projections, etc, but I am stuck.
I'd like to get a final result that looks like this
{
'question1' : {
'a' : 2,
'b' : 1
},
'question2' : {
'a' : 1,
'b' : 1,
'c' : 1,
},
'question3' : {
'a' : 2,
'b' : 1,
'c' : 2,
},
'question4' : 2 //avg (3+2+1)/3
}
OR even better:
{
'radio': {
'question1' : {
'a' : 2,
'b' : 1
},
'question2' : {
'a' : 1,
'b' : 1,
'c' : 1,
},
},
'multi': {
'question3' : {
'a' : 2,
'b' : 1,
'c' : 2,
}
},
'avg' : {
'question4' : 2
}
}
My pipeline would look something like this:
Response.aggregate([
{ $match: { 'metaData.survey': surveyId} }, // filter only for the specific survey
{ $project: { // I assume I have to turn the answers into an array
"answers": { $objectToArray: "$answers" },
"createdAt": "$createdAt"
}
},
// maybe facet here?
// conceptually, In the next stage I'd want to bucket the questions
// by type with something like below, then perform the right type of
// aggregation depending on the question type
// if $in [$$answers.k ['question1, 'question2']] group by k, v and count
// if $in [$$answers.k ['question3']] unwind and count each unique value?
// { $facet : { radio: [], multi:[]}}
])
Basically, I know which question Id is a radio or a multi-select, I'm just trying to figure out how to format the pipeline to achieve the desired output based on the questionId being in a known array.
Bonus points if I can figure out how to also group the by day/month based on the createdAt time
db.collection.aggregate([
{
$match: {}
},
{
$project: { answers: { $objectToArray: "$answers" } }
},
{
$unwind: "$answers"
},
{
$unwind: "$answers.v"
},
{
$group: {
_id: "$answers",
c: { "$sum": 1 }
}
},
{
$group: {
_id: "$_id.k",
v: { "$push": { k: "$_id.v", v: "$c" } }
}
},
{
$group: {
_id: null,
v: { "$push": { k: "$_id", v: { "$arrayToObject": "$v" } } }
}
},
{
$set: { v: { $arrayToObject: "$v" } }
},
{
$replaceWith: "$v"
}
])
mongoplayground
db.collection.aggregate([
{
$match: {}
},
{
$project: { answers: { $objectToArray: "$answers" } }
},
{
$unwind: "$answers"
},
{
$set: {
"answers.type": {
$switch: {
branches: [
{
case: { $isArray: "$answers.v" },
then: "multi"
},
{
case: { $eq: [ { $type: "$answers.v" }, "string" ] },
then: "radio"
},
{
case: { $isNumber: "$answers.v" },
then: "avg"
}
],
default: "other"
}
}
}
},
{
$unwind: "$answers.v"
},
{
$group: {
_id: "$answers",
c: { $sum: 1 }
}
},
{
$group: {
_id: "$_id.k",
type: { $first: "$_id.type" },
v: {
$push: {
k: { $toString: "$_id.v" },
v: "$c"
}
}
}
},
{
$group: {
_id: "$type",
v: {
$push: {
k: "$_id",
v: { $arrayToObject: "$v" }
}
}
}
},
{
$group: {
_id: null,
v: {
$push: {
k: "$_id",
v: { $arrayToObject: "$v" }
}
}
}
},
{
$set: { v: { $arrayToObject: "$v" } }
},
{
$replaceWith: "$v"
},
{
$set: {
avg: {
$arrayToObject: {
$map: {
input: { $objectToArray: "$avg" },
as: "s",
in: {
k: "$$s.k",
v: {
$avg: {
$map: {
input: { $objectToArray: "$$s.v" },
as: "x",
in: { $multiply: [ { $toInt: "$$x.k" }, "$$x.v" ] }
}
}
}
}
}
}
}
}
}
])
mongoplayground

how to convert mongodb fields to subdocument fields?

sorry it may be silly question, mongodb contains thousands of documents .
hard to be changed manually
original format
{"name" : "aaaa",
"price" : 111,
"ing1" : "abcd",
"ing1Conc" : 50 ,
"ing2" : "wxyz",
"ing2conc": 100}
needed to be converted to
{"name" : "aaaa",
"price" : 111,
"content":[
{ "ing1" : "abcd", "ing1Conc" : 50},
{ "ing2" : "wxyz", "ing2conc": 100}
]
}
The trivial solution would be this one:
db.collection.aggregate([
{
$project: {
name: 1,
price: 1,
content: [
{ ing1: "$ing1", ing1Conc: "$ing1Conc" },
{ ing2: "$ing1", ing2conc: "$ing2conc" }
]
}
}
])
A more generic solution would be this one:
db.collection.aggrega
{
$project: {
name: 1,
price: 1,
data: {
$filter: {
input: { $objectToArray: "$$ROOT" },
cond: { $regexMatch: { input: "$$this.k", regex: "^ing\\d+" } }
}
}
}
},
{ $unwind: "$data" },
{ $set: { i: { $regexFind: { input: "$data.k", regex: "\\d+" } } } },
{ $set: { i: "$i.match" } },
{
$group: {
_id: {
name: "$name",
price: "$price",
i: "$i"
},
content: { $push: "$data" }
}
},
{ $sort: { "_id.i": 1 } },
{ $set: { content: { $arrayToObject: "$content" } } },
{
$group: {
_id: { name: "$_id.name", price: "$_id.price" },
content: { $push: "$content" }
}
},
{ $replaceRoot: { newRoot: { $mergeObjects: [ "$$ROOT", "$_id" ] } } },
{ $unset: "_id" }
])
Mongo Playground
However, I think this structure is still bad. I would suggest something like
content: {
ing: [ "abcd", "wxyz"],
conc: [ 50, 100 ]
}
content: [
{ ing: "abcd", conc: 50 },
{ ing: "wxyz", conc :100 }
]
content: [
{ idx: 1, ing: "abcd", conc: 50 },
{ idx: 2, ing: "wxyz", conc: 100 }
]

Aggregate and project with multiples conditions

I have a collection myCollection with array of members :
{
name : String,
members: [{status : Number, memberId : {type: Schema.Types.ObjectId, ref: 'members'}]
}
and i have this data
"_id" : ObjectId("5e83791eb49ab07a48e0282b")
"members" : [
{
"status" : 1,
"_id" : ObjectId("5e83791eb49ab07a48e0282c"),
"memberId" : ObjectId("5e7dbf5b257e6b18a62f2da9")
},
{
"status" : 2,
"_id" : ObjectId("5e837944b49ab07a48e0282d"),
"memberId" : ObjectId("5e7de2dbe027f43adf678db8")
}
],
I want to check by aggregate query if member 5e7dbf5b257e6b18a62f2da9 exists with status 1 but it didn't return true
db.getCollection('myCollection').aggregate([
{$match: {_id: ObjectId("5e83791eb49ab07a48e0282b")}},
{
$project: {
isMember: {
$cond: [
{ $and: [ {$in: [ObjectId("5e7dbf5b257e6b18a62f2da9"), '$members.memberId']}, {$eq: ['$members.status', 1]} ] },
// if
true, // then
false // else
]
}
}
}
])
Thank you for your responses.
If you want to get just true/false you can shortcut like this:
db.collection.aggregate([
{ $match: { _id: ObjectId("5e83791eb49ab07a48e0282b") } },
{
$project: {
isMember: {
$map: {
input: "$members",
in: {
$and: [
{ $eq: [ObjectId("5e7dbf5b257e6b18a62f2da9"), '$$this.memberId'] },
{ $eq: [1, '$$this.status'] }
]
}
}
}
}
},
{ $set: { isMember: { $anyElementTrue: "$isMember" } } }
])
A different style would be this:
db.collection.aggregate([
{ $match: { _id: ObjectId("5e83791eb49ab07a48e0282b") } },
{
$project: {
isMember: {
$map: {
input: "$members",
in: {
$eq: [
{ memberId: ("5e7dbf5b257e6b18a62f2da9"), status: 1 },
{ memberId: "$$this.memberId", status: "$$this.status" }
]
}
}
}
}
},
{ $set: { isMember: { $anyElementTrue: "$isMember" } } }
])

Grouping and counting across documents?

I have a collection with documents similar to the following format:
{
departure:{name: "abe"},
arrival:{name: "tom"}
},
{
departure:{name: "bob"},
arrival:{name: "abe"}
}
And to get output like so:
{
name: "abe",
departureCount: 1,
arrivalCount: 1
},
{
name: "bob",
departureCount: 1,
arrivalCount: 0
},
{
name: "tom",
departureCount: 0,
arrivalCount: 1
}
I'm able to get the counts individually by doing a query for the specific data like so:
db.sched.aggregate([
{
"$group":{
_id: "$departure.name",
departureCount: {$sum: 1}
}
}
])
But I haven't figured out how to merge the arrival and departure name into one document along with counts for both. Any suggestions on how to accomplish this?
You should use a $map to split your doc into 2, then $unwind and $group..
[
{
$project: {
dep: '$departure.name',
arr: '$arrival.name'
}
},
{
$project: {
f: {
$map: {
input: {
$literal: ['dep', 'arr']
},
as: 'el',
in : {
type: '$$el',
name: {
$cond: [{
$eq: ['$$el', 'dep']
}, '$dep', '$arr']
}
}
}
}
}
},
{
$unwind: '$f'
}, {
$group: {
_id: {
'name': '$f.name'
},
departureCount: {
$sum: {
$cond: [{
$eq: ['$f.type', 'dep']
}, 1, 0]
}
},
arrivalCount: {
$sum: {
$cond: [{
$eq: ['$f.type', 'arr']
}, 1, 0]
}
}
}
}, {
$project: {
_id: 0,
name: '$_id.name',
departureCount: 1,
arrivalCount: 1
}
}
]