Im trying to create a dynamic group by (with sum agg) in MongoDB. But don't know how to right syntax that.
Lets imaging 2 documents:
{
"_id": {"$oid":"5f69f6a360c8479d0908a649"},
"key":"key1",
"data":{
"key1":"value1",
"key2":"value2",
"key3":"value3",
"key4":"value4"
},
"count":10
}
{
"_id": {"$oid":"5f69f6a360c8479d0908a649"},
"key":"key2",
"data":{
"key1":"value5",
"key2":"value6",
"key3":"value7",
"key4":"value8"
},
"count":15
}
With the key attribute, I want to control, which is the groupby attribute.
A pseudo query could look like:
[{
$group: {
_id: {
'$key': data[$key]
},
sum: {
'$sum': '$count'
}
}
}]
Output should look like:
value1 : 10
value6 : 15
Somebody knows how to do that?
I don't understand the purpose of $sum and $group, there are no arrays in your documents.
This aggregation pipeline give desired result:
db.collection.aggregate([
{ $set: { data: { $objectToArray: "$data" } } },
{ $set: { data: { $filter: { input: "$data", cond: { $eq: ["$$this.k", "$key"] } } } } },
{ $set: { data: { k: { $arrayElemAt: ["$data.v", 0] }, v: "$count" } } },
{ $set: { data: { $arrayToObject: "$data" } } },
{ $replaceRoot: { newRoot: { $mergeObjects: ["$$ROOT", "$data"] } } },
{ $unset: ["key", "count", "data"] }
])
You can try,
$reduce input data as array using $objectToArray, check condition if key matches with data key then return key as value and value as count field
convert that returned key and value object array to exact object using $arrayToObject
replace field using $replaceWith
db.collection.aggregate([
{
$replaceWith: {
$arrayToObject: [
[
{
$reduce: {
input: { $objectToArray: "$data" },
initialValue: {},
in: {
$cond: [
{ $eq: ["$$this.k", "$key"] },
{
k: "$$this.v",
v: "$count"
},
"$$value"
]
}
}
}
]
]
}
}
])
Playground
Related
Updated:
I have a document on the database that looks like this:
My question is the following:
How can I retrieve the first 10 elements from the friendsArray from database and sort it descending or ascending based on the lastTimestamp value.
I don't want to download all values to my API and then sort them in Python because that is wasting my resources.
I have tried it using this code (Python):
listOfUsers = db.user_relations.find_one({'userId': '123'}, {'friendsArray' : {'$orderBy': {'lastTimestamp': 1}}}).limit(10)
but it just gives me this error pymongo.errors.OperationFailure: Unknown expression $orderBy
Any answer at this point would be really helpful! Thank You!
use aggregate
first unwind
then sort according timestap
group by _id to create sorted array
use addfields and filter for getting first 10 item of array
db.collection.aggregate([
{ $match:{userId:"123"}},
{
"$unwind": "$friendsArray"
},
{
$sort: {
"friendsArray.lastTimeStamp": 1
}
},
{
$group: {
_id: "$_id",
friendsArray: {
$push: "$friendsArray"
}
},
},
{
$addFields: {
friendsArray: {
$filter: {
input: "$friendsArray",
as: "z",
cond: {
$lt: [
{
$indexOfArray: [
"$friendsArray",
"$$z"
]
},
10
]
}// 10 is n first item
}
}
},
}
])
https://mongoplayground.net/p/2Usk5sRY2L2
and for pagination use this
db.collection.aggregate([
{ $match:{userId:"123"}},
{
"$unwind": "$friendsArray"
},
{
$sort: {
"friendsArray.lastTimeStamp": 1
}
},
{
$group: {
_id: "$_id",
friendsArray: {
$push: "$friendsArray"
}
},
},
{
$addFields: {
friendsArray: {
$filter: {
input: "$friendsArray",
as: "z",
cond: {
$and: [
{
$gt: [
{
$indexOfArray: [
"$friendsArray",
"$$z"
]
},
10
]
},
{
$lt: [
{
$indexOfArray: [
"$friendsArray",
"$$z"
]
},
20
]
},
]
}// 10 is n first item
}
}
},
}
])
The translation of your find to aggregation(we need unwind that why aggregation is used) would be like the bellow query.
Test code here
Query (for descending replace 1 with -1)
db.collection.aggregate([
{
"$match": {
"userId": "123"
}
},
{
"$unwind": {
"path": "$friendsArray"
}
},
{
"$sort": {
"friendsArray.lastTimeStamp": 1
}
},
{
"$limit": 10
},
{
"$replaceRoot": {
"newRoot": "$friendsArray"
}
}
])
If you want to skip some before limit add one stage also
{
"$skip" : 10
}
To take the 10-20 messages for example.
Need to format the date and make a sum per day but sometimes a or b values are not available.
in the end, get one document with respect to date and sum. I'm using MongoDB 4.2.
Data Structure:
{
"data": {
"11-10-2001": {
"a": 17.281150000000001,
"b": 11.864060000000006
},
"13-10-2020": {
"b": 2.7616699999999994
},
"12-10-2001": {
"b": 4.0809599999999997
},
"09-10-2001": {
"b": 4.1286300000000005
},
"17-10-2001": {
"a": 15.140560000000123,
"b": 5.017139999999998
},
"18-10-2001": {
"b": 1.975189999999997,
"a": 7.093789999999976
}
}
}
Expected Output one document that contains the day and sum:
{
{
day: 11-10-2001,
sum : 29.145
},
{
day: 13-10-201,
sum : 2.7616699
},
{
day: 12-10-2001,
sum : 4.0809599999999997
},
{
day: 17-10-2001,
sum : 20.114
},
{
day: 18-10-2001,
sum : 9.145
}
}
You can try,
$map to iterate loop of data object after converting to array using $objectToArray
add key day, and sum, $reduce to loop of number object after converting to array using $objectToArray, $add to sum the value of number
$unwind deconstruct data array
$replaceRoot to replace data object to root
db.collection.aggregate([
{
$addFields: {
data: {
$map: {
input: { $objectToArray: "$data" },
in: {
day: "$$this.k",
sum: {
$reduce: {
input: { $objectToArray: "$$this.v" },
initialValue: 0,
in: { $add: ["$$this.v", "$$value"] }
}
}
}
}
}
}
},
{ $unwind: "$data" },
{ $replaceRoot: { newRoot: "$data" } }
])
Playground
You can do like following
db.collection.aggregate([
{
$project: { data: { "$objectToArray": "$data" } }
},
{
$unwind: "$data"
},
{
"$replaceRoot": { "newRoot": "$data" }
},
{
$addFields: { v: { "$objectToArray": "$v" } }
},
{
$addFields: {
v: {
$reduce: {
input: "$v",
initialValue: 0,
in: {
$add: [ "$$this.v", "$$value" ]
}
}
}
}
},
{
$group: {
_id: null,
data: {
$push: {
day: "$k",
sum: "$v"
}
}
}
}
])
Working Mongo playground
I have three tables below is the structure like below
I'm looking to get a result like below
"type1": [ -- type from Accounts collection
{
"_id": "5e97e9a224f62f93d5x3zz46", -- _id from Accounts collection
"locs": "sampleLocks 1", -- field from Accounts collection
"solutions": "sample solutions 1", -- field from Accounts collection
"Clause": "clause 1" -- field from AccountsDesc collection
},
{
"_id": "5e97e9a884f62f93d5x3zz46",
"locs": "sampleLocks2",
"solutions": "sample solutions2",
"Clause": "clause2"
}
],
"type2": [
// same data construction as of type1 above
]
_id, locks, solution to be coming from Accounts collection
Clause field to be coming from AccountsDesc collection
accounts_id is kind of a foreign key in AccountsDesc coming from Account
competitor_id is kind of a foreign key in AccountsDesc coming from Competitor
Below is what my query looks like
db.accountDesc.aggregate([
{
$match : {accounts_Id : "123456"}, active: true}
},
{
$lookup: {
from: 'accounts',
pipeline: [{ $match: { type: { $in: ["type1, type2, type3"] } } }],
as: 'accountsData'
}
},
{
$group: {
_id: "$accountsData.type",
data: {
$push: {_id: "$accountsData._id", clause: "$clause", locs: "$type.locs", solutions: "$type.solutions"}
}
}
},
{
$group: {
_id: null,
data: {
$push: {
k: {
$toString: '$_id'
},
v: '$data'
}
}
}
},
{
$replaceRoot: {
newRoot: {
$arrayToObject: '$data'
}
}
}
])
Issues related with the query -
$match : {accountId : "123456"}, active: true} -- No data is returned if i use match on AccountsDesc collection
cant set localField, foriegnField if im using pipeline, then how the mapping will happen like a LEFT join.
clause: "$clause" don't get the value of this field in the response
As we discussed in chat, you want RIGHT OUTER JOIN for your aggregation.
Try the query below:
db.User_Promo_Map.aggregate([
{
$match: {
user_Id: ObjectId("5e8c1180d59de1704ce68112")
}
},
{
$lookup: {
from: "promo",
pipeline: [
{
$match: {
active: true,
platform: {
$in: [
"twitch",
"youtube",
"facebook"
]
}
}
}
],
as: "accountsData"
}
},
{
$unwind: "$accountsData"
},
{
$group: {
_id: "$accountsData.platform",
data2: {
$addToSet: {
amount: "$amount",
promo_Id: "$promo_Id"
}
},
data: {
$addToSet: {
_id: "$accountsData._id",
format: "$accountsData.format",
description: "$accountsData.description"
}
}
}
},
{
$addFields: {
data: {
$map: {
input: "$data",
as: "data",
in: {
"_id": "$$data._id",
"description": "$$data.description",
"format": "$$data.format",
amount: {
$reduce: {
input: "$data2",
initialValue: "$$REMOVE",
in: {
$cond: [
{
$eq: [
"$$this.promo_Id",
"$$data._id"
]
},
"$$this.amount",
"$$value"
]
}
}
}
}
}
}
}
},
{
$group: {
_id: null,
data: {
$push: {
k: {
$toString: "$_id"
},
v: "$data"
}
}
}
},
{
$replaceRoot: {
newRoot: {
$arrayToObject: "$data"
}
}
}
])
MongoPlayground
Have a record with value in a aggregation.
_id:asdgrsdv
surname:cooper,
comapany:sabesto,
salary:15748
mapped:Array
0:Object
name:'mark',
age:'25',
surname:'cooper'
1:Object
name:'snow',
age:'29',
surname:'wyte'
how to map surname outside with surname in mapped array like this in mongodb aggregation
required output:
_id:asdgrsdv
name:'mark',
comapany:sabesto,
salary:15748
age:'25',
surname:'cooper'
Try this one:
db.collection.aggregate([
{
$addFields: {
data: {
$mergeObjects: [
"$$ROOT",
{
$arrayElemAt: [
{
$filter: {
input: "$mapped",
cond: {
$eq: [
"$$this.surname",
"$surname"
]
}
}
},
0
]
}
]
}
}
},
{
$replaceRoot: {
newRoot: "$data"
}
},
{
$project: {
"mapped": 0
}
}
])
MongoPlayground
I have a MongoDB database with the following document structure:
{
"name": "ServiceA",
"areas": ["X", "Y", "Z"],
"tags": [
{
"name": "Financial",
"type": "A"
},
{
"name": "Consumer",
"type": "B"
}
]
}
There's many entries each with the same structure. Containing the same areas.
There's many predefined tag names, sorted into a few types.
The aim is to group by area and then count the number of occurrences of each tag. So an output like this:
{
"area": "X",
"count": 100, // Total entries with X as an area
"tagNameCount": {
"Financial": 20,
"Consumer": 10,
...
},
"tagTypeCount": {
"A": 70,,
"B: 40
}
}
I've been starting of using $unwind on areas, but it's the next steps from there I'm stuck on. I get that I need to use $group, but I can't work out how to count occurrences.
You may use $facet operator which allows perform several aggregation in one.
Walkthrough
1. We $unwind by area and tags
2. With $facet, we perform 3 parallel aggregations:
2.1 We count unique areas
2.2 We count unique tag names for each area
2.3 We count unique tag type for each area
3. We join 2 parallel arrays by flatten areas
4. We assemble desired output
db.collection.aggregate([
{
$unwind: "$areas"
},
{
$unwind: "$tags"
},
{
$facet: {
areas: [
{
$group: {
_id: "$areas",
count: {
$addToSet: "$_id"
}
}
},
{
$project: {
_id: 0,
area: "$_id",
count: {
$size: "$count"
}
}
}
],
tagNameCount: [
{
$group: {
_id: {
name: "$tags.name",
areas: "$areas"
},
count: {
$addToSet: "$_id"
}
}
},
{
$group: {
_id: "$_id.areas",
tagNameCount: {
$push: {
k: "$_id.name",
v: {
$size: "$count"
}
}
}
}
},
{
$addFields: {
tagNameCount: {
$arrayToObject: "$tagNameCount"
}
}
}
],
tagTypeCount: [
{
$group: {
_id: {
type: "$tags.type",
areas: "$areas"
},
count: {
$addToSet: "$_id"
}
}
},
{
$group: {
_id: "$_id.areas",
tagTypeCount: {
$push: {
k: "$_id.type",
v: {
$size: "$count"
}
}
}
}
},
{
$addFields: {
tagTypeCount: {
$arrayToObject: "$tagTypeCount"
}
}
}
]
}
},
{
$unwind: "$areas"
},
{
$addFields: {
"tagNameCount": {
$filter: {
input: "$tagNameCount",
cond: {
$eq: [
"$areas.area",
"$$this._id"
]
}
}
},
"tagTypeCount": {
$filter: {
input: "$tagTypeCount",
cond: {
$eq: [
"$areas.area",
"$$this._id"
]
}
}
}
}
},
{
$project: {
area: "$areas.area",
count: "$areas.count",
tagNameCount: {
$arrayElemAt: [
"$tagNameCount.tagNameCount",
0
]
},
tagTypeCount: {
$arrayElemAt: [
"$tagTypeCount.tagTypeCount",
0
]
}
}
},
{
$sort: {
area: 1
}
}
])
MongoPlayground
Here's one method:
unwind both areas and tags
for each area collect the applicable tags, and the unique names and types
count the names to get the total number of tags
for each unique name, count the matching values in the tags
do the same for each unique type
project out the unique fields
db.collection.aggregate([
{$unwind: "$areas"},
{$unwind: "$tags"},
{$group: {
_id: "$areas",
names: {$push: "$tags.name"},
uniqueNames: {$addToSet: "$tags.name"},
types: {$push: "$tags.type"},
uniqueTypes: {$addToSet: "$tags.type"}
}},
{$addFields: {
count: {$size: "$names"},
names: {
$arrayToObject: {
$map: {
input: "$uniqueNames",
as: "needle",
in: {
k: "$$needle",
v: {
$size: {
$filter: {
input: "$names",
cond: {$eq: ["$$this","$$needle"]}
}}}}}}},
types: {
$arrayToObject: {
$map: {
input: "$uniqueTypes",
as: "needle",
in: {
k: "$$needle",
v: {$size: {
$filter: {
input: "$types",
cond: { $eq: [ "$$this","$$needle"]}
}}}}}}}}},
{
$project: {
uniqueNames: 0,
uniqueTypes: 0
}}
])
Playground