I am having a similar collection
db={
collectionA: [
{
"id": ObjectId("63b7c24c06ebe7a8fd11777b"),
"uniqueRefId": "UUID-2023-0001",
"products": [
{
"productIndex": 1,
"isProdApproved": false,
"productCategory": ObjectId("63b7c24c06ebe7a8fd11777b"),
"productOwners": [
{
_id: ObjectId("63b7c2fd06ebe7a8fd117781"),
iApproved: false
},
{
_id: ObjectId("63b7c2fd06ebe7a8fd117782"),
iApproved: false
}
]
},
{
"productIndex": 2,
"isProdApproved": false,
"productCategory": ObjectId("63b7c24c06ebe7a8fd11777b"),
"productOwners": [
{
_id: ObjectId("63b7c2fd06ebe7a8fd117781"),
iApproved: false
},
{
_id: ObjectId("63b7c2fd06ebe7a8fd117783"),
iApproved: false
}
]
},
{
"productIndex": 3,
"productCategory": "",
"productOwners": ""
}
]
}
]
}
I want to find the productOwner whose _id is 63b7c2fd06ebe7a8fd117781 in the productOwners and update the isApproved and isprodApproved to true. Other data will remain as it is.
I have tried this but it is only updating the first occurance
db.collectionA.update(
{
_id: ObjectId('63b7c24c06ebe7a8fd11777b'),
'products.productOwners._id': ObjectId('63b7c2fd06ebe7a8fd117781'),
},
{ $set: { 'products.$.productOwners.$[x].isApproved': true } },
{ arrayFilters: [{ 'x._id': ObjectId('63b7c2fd06ebe7a8fd117781') }] }
);
This one should work:
db.collection.updateMany({},
[
{
$set: {
products: {
$map: {
input: "$products",
as: "product",
in: {
$cond: {
if: { $eq: [{ $type: "$$product.productOwners" }, "array"] },
then: {
$mergeObjects: [
"$$product",
{ isProdApproved: { $in: [ObjectId("63b7c2fd06ebe7a8fd117781"), "$$product.productOwners._id"] } },
{
productOwners: {
$map: {
input: "$$product.productOwners",
as: 'owner',
in: {
$mergeObjects: [
"$$owner",
{ iApproved: { $eq: ["$$owner._id", ObjectId("63b7c2fd06ebe7a8fd117781")] } }
]
}
}
}
}
]
},
else: "$$product"
}
}
}
}
}
}
]
)
However, the data seem to be redundant. Better update only products.productOwners.iApproved and then derive products.isProdApproved from nested elements:
db.collection.aggregate([
{
$set: {
products: {
$map: {
input: "$products",
as: "product",
in: {
$cond: {
if: { $eq: [{ $type: "$$product.productOwners" }, "array"] },
then: {
$mergeObjects: [
"$$product",
{ isProdApproved: { $anyElementTrue: ["$$product.productOwners.iApproved"] } },
]
},
else: "$$product"
}
}
}
}
}
}
])
Related
I have a collection:
{
"_id": 1,
"_deleted": false,
"customFields": [{
"fieldName": "sapID",
"value": ""
}, {
"fieldName": "salesTerritory",
"value": ""
}, {
"fieldName": "clientType",
"value": "Corporate"
}],
}
How can I project(aggregate) only the value field of the element with fieldName = "clientType":
db.collection.aggregate(
{
$project:{value:<code>}
}
)
I tried $filter but it does not work
db.collection.aggregate([
{
$project: {
"customFields.value": 1
}
}
])
mongoplayground
db.collection.aggregate([
{
$set: {
customFields: {
$map: {
input: "$customFields",
as: "c",
in: {
$cond: {
if: { "$eq": [ "$$c.fieldName", "clientType" ] },
then: { value: "$$c.value" },
else: "$$c"
}
}
}
}
}
}
])
mongoplayground
What about this?
db.collection.aggregate([
{
$project: {
customFields: {
$filter: {
input: "$customFields",
$cond: { $eq: ["$$this.fieldName", "clientType"] }
}
}
}
}
])
Mongo Playground
I have an object like so
{
"_id": "62334a3c86f03ce0985f11a1",
"stops": [
{
"location": {
"baseLocation": "622e29bd0a56c69f81e0e6e9",
"extraLocation": "622e29bd0a56c69f81e0e6eb"
},
"timesData": [
{
"wType": "date"
}
],
},
{
"location": {
"baseLocation": "622e70a59975be022276178c",
"extraLocation": "622e70a59975be022276178e"
},
"timesData": [
{
"wType": "date"
}
],
}
},
],
}
I need to find the index of objects that have a baseLocation equal to a value and which have a wType of date and I do so using a $map like the one below
{
$map: {
input: "$stops",
in: {
$and: [
{
$eq: ["$$this.location.baseLocation", mongoose.Types.ObjectId(from.id)]
},
{
$eq: ["$$this.timesData.0.wType", "date"]
}
]
}
}
},
I get no matches, but if I do it like this
{
$map: {
input: "$stops",
in: {
$eq: ["$$this.location.baseLocation", mongoose.Types.ObjectId(from.id)]
}
}
},
It works, so I guess the problem is that I can't access "$$this.timesData.0.wType"
How about using $arrayElemAt:
$map: {
input: "$stops",
in: {
$and: [
{
$eq: [
"$$this.location.baseLocation",
mongoose.Types.ObjectId(from.id)]
]
},
{
$eq: [
{
"$arrayElemAt": [
"$$this.timesData",
0
]
},
{
"wType": "date"
}
]
}
]
}
}
}
}
You can check it on the playground: https://mongoplayground.net/p/p5eRv0pXYXM
I have collection like this:
{
"labels": [{
"description": "Dog"
}, {
"description": "Red"
}, {
"description": "XXX"
}]
}
{
"labels": [{
"description": "Cat"
}, {
"description": "XXX"
}, {
"description": "Yellow"
}]
}
{
"labels": [{
"description": "Dog"
}, {
"description": "Red"
}, {
"description": "Yellow"
}]
}
{
"labels": [{
"description": "Bird"
}, {
"description": "XXX"
}, {
"description": "XXX"
}]
}
I want to filter for example only "Red" and "Yellow" colors from ALL elements and output document like this:
// because "Dog" appears 2 times so total = 2
{
description: "Dog",
total: 2,
colors: [
{ "_id": "Red", total: 2 },
{ "_id": "Yellow", total: 1 }
]
}
{
description: "Cat",
total: 1,
colors: [
{ "_id": "Yellow", total: 1 }
]
}
{
description: "Bird",
total: 1,
colors: []
}
{
description: "Red",
total: 2,
colors: [
{ _id: "Yellow", total: 1 }
]
}
{
description: "XXX",
total: 4,
colors: [
{ _id: "Yellow", total: 1 }
]
}
I can do this by using collection.distinct('labels.description') and then iterating through every single element + make a separate collection.count({ 'labels.description': 'Dog' }) like this:
for (...)
db.collection.aggregate([
{
"$match": {
"labels.description": valueFromLoop // (e.g. Dog)
}
},
{ $unwind : "$labels" },
{
"$group": {
"_id": "$labels.description",
"count": { "$sum": 1 }
}
},
{
"$match": {
"$or": [
{ "_id": "Red" },
{ "_id": "Yellow" }
]
}
},
{
"$sort": {
"count": -1
}
}
])
I want to do this in a single aggregation or mapReduce so that I could easily output it to new collection using $out instead of using Bulk operations separately, however I don't know if it's possible.
Try this:
let filter = ["Red", "Yellow"];
db.testcollection.aggregate([
{
$addFields: { bkp: "$labels" }
},
{ $unwind: "$labels" },
{
$addFields: {
bkp: {
$filter: {
input: "$bkp",
as: "item",
cond: {
$and: [
{ $ne: ["$$item.description", "$labels.description"] },
{ $in: ["$$item.description", filter] }
]
}
}
}
}
},
{
$unwind: {
path: "$bkp",
preserveNullAndEmptyArrays: true
}
},
{
$group: {
_id: {
key1: "$labels.description",
key2: { $ifNull: ["$bkp.description", false] }
},
total: { $sum: 1 }
}
},
{
$group: {
_id: "$_id.key1",
description: { $first: "$_id.key1" },
total: {
$sum: {
$cond: {
if: { $first: [["$_id.key2"]] },
then: 1,
else: "$total"
}
}
},
colors: {
$push: {
$cond: {
if: { $first: [["$_id.key2"]] },
then: {
_id: "$_id.key2",
total: "$total"
},
else: "$$REMOVE"
}
}
}
}
},
{ $project: { _id: 0 } }
]);
For some reason with code from both answers it does not count all tags properly.
I'm posting what works:
db.collection.aggregate([
{
$project: {
labels: 1,
result: {
$filter: {
input: "$labels",
as: "label",
cond: {
$or: [
{ $eq: ["$$label.description", "Blue"] },
{ $eq: ["$$label.description", "Red"] },
{ $eq: ["$$label.description", "Black-and-white"] },
{ $eq: ["$$label.description", "Purple"] },
{ $eq: ["$$label.description", "Orange"] },
{ $eq: ["$$label.description", "Yellow"] },
{ $eq: ["$$label.description", "Green"] },
{ $eq: ["$$label.description", "Teal"] }
]
}
}
}
}
},
{
$unwind: "$labels"
},
{
"$group": {
_id: "$labels.description",
x: {
$push: "$result.description"
},
total: { "$sum": 1 }
}
},
{
$project: {
x: {
$reduce: {
input: '$x',
initialValue: [],
in: {$concatArrays: ['$$value', '$$this']}
}
},
total: 1
}
},
{
$project: {
x: 1,
y: { $setUnion: "$x" },
total: 1
}
},
{
$project: {
_id: 0,
description: "$_id",
"colors": {
$map: {
input: "$y",
as: "item",
in: {
_id: "$$item",
count: {
$size: {
$filter: {
input: "$x",
as: "itemx",
cond: {
$eq: ["$$item", "$$itemx"]
}
}
}
}
}
}
},
total: 1
}
},
{
$out: "backgrounds_meta"
}
])
db.test2.aggregate([
{
$project: {
labels:1,
colours: {
$filter: {
input: "$labels",
as: "label",
cond: {
$or: [
{$eq:["Yellow","$$label.description"]},
{$eq:["Red", "$$label.description"]}
]
}
}
}
}
},
{$unwind:"$labels"},
{$group:{
_id: "$labels.description",
total: {$sum:1},
colours: {$addToSet:"$colours.description"}
}},
{
$project:{
_id:0,
description:"$_id",
total:1,
colours: {
$reduce:{
input: "$colours",
initialValue: [],
in: {$concatArrays: ["$$value", "$$this"]}
}
}
}
},
{
$unwind: {
path:"$colours",preserveNullAndEmptyArrays: true
}
},
{
$group:{
_id:{
description:"$description",
total:"$total",
colour:"$colours"
},
count: {
$sum: {$cond:[{$ifNull:["$colours",false]},1,0]}
}
}
},
{
$group:{
_id:{
description:"$_id.description",
total:"$_id.total"
},
colours: {
$push: {
$cond: [{$gt:["$count",0]},
{
"_id":"$_id.colour",
total:"$count"
},
"$$REMOVE"
]
}
}
}
},
{
$project: {
_id:0,
description: "$_id.description",
total: "$_id.total",
colours: 1
}
}
]);
**Edit In your answer, you are missing the Yellows for Red and Dog because you are taking the first item from $result with $arrayElemAt: ["$result.description", 0].
If description is a colour, do you also want to include the counts for itself in colours?
Never mind, you've updated the answer
I need to fetch distinct nested documents.
Please find the sample document:
{
"propertyId": 1001820437,
"date": ISODate("2020-07-17T00:00:00.000Z"),
"HList":[
{
"productId": 123,
"name": "Dubai",
"tsh": true
}
],
"PList":[
{
"productId": 123,
"name": "Dubai",
"tsh": false
},
{
"productId": 234,
"name": "India",
"tsh": true
}
],
"CList":[
{
"productId": 234,
"name": "India",
"tsh": false
}
]
}
Expected result is:
{
"produts":[
{
"productId": 123,
"name": "Dubai"
},
{
"productId": 234,
"name": "India"
}
]
}
I tried with this query:
db.property.aggregate([
{
$match: {
"propertyId": 1001820437,
"date": ISODate("2020-07-17T00:00:00.000Z")
}
},
{
"$project": {
"_id": 0,
"unique": {
"$filter": {
"input": {
"$setDifference": [
{
"$concatArrays": [
"$HList.productId",
"$PList.productId",
"$CList.productId"
]
},
[]
]
},
"cond": {
"$ne": [ "$$this", "" ]
}
}
}
}
}
]);
Is $setDifference aggregation is correct choice here?
My query returns only unique product ids but i need a productId with name.
Could someone help me to solve this?
Thanks in advance
You can use $projectfirst to get rid of tsh field and then run $setUnion which ignores duplicated entries:
db.collection.aggregate([
{
$project: {
"HList.tsh": 0,
"PList.tsh": 0,
"CList.tsh": 0,
}
},
{
$project: {
products: {
$setUnion: [ "$HList", "$PList", "$CList" ]
}
}
}
])
Mongo Playground
The following two aggregations return the expected and same result (you can use any of the two):
db.collection.aggregate( [
{
$project: {
_id: 0,
products: {
$reduce: {
input: { $setUnion: [ "$HList", "$PList", "$CList" ] },
initialValue: [],
in: {
$setUnion: [ "$$value", [ { productId: "$$this.productId", name: "$$this.name" } ] ]
}
}
}
}
}
] )
This one is little verbose:
db.collection.aggregate( [
{
$project: { list: { $setUnion: [ "$HList", "$PList", "$CList" ] } }
},
{
$unwind: "$list"
},
{
$group: {
_id: null,
products: { $addToSet: { "productId": "$list.productId", "name": "$list.name" } }
}
},
{
$project: { _id: 0 }
}
] )
db.collection.aggregate([
{
$match: {
"propertyId": 1001820437,
"date": ISODate("2020-07-17T00:00:00.000Z")
}
},
{
$project: {
products: {
$filter: {
input: { "$setUnion" : ["$CList", "$HList", "$PList"] },
as: 'product',
cond: {}
}
}
}
},
{
$project: {
"_id":0,
"products.tsh": 1,
"products.name": 1,
}
},
])
Provided I have following collections
Customers
[
{
uuid: "first",
culture: "it-it"
},
{
uuid: "second",
culture: "de-de"
}
]
Vehicles
[
{
model: "mymodel",
users: [
{
uuid: "first",
isOwner: true,
createdOn: "2019-05-15T06: 00: 00"
}
]
},
{
model: "mymodel",
users: [
{
uuid: "first",
isOwner: false,
createdOn: "2019-05-15T06: 00: 00"
},
{
uuid: "second",
isOwner: true,
createdOn: "2019-05-15T06: 00: 00"
}
]
}
]
And following query:
db.customers.aggregate([
{
$lookup: {
from: "vehicles",
let: {
uuid: "$uuid"
},
pipeline: [
{
$match: {
$expr: {
$in: [
"$$uuid",
"$users.uuid"
]
}
}
},
{
$project: {
model: 1,
users: {
$filter: {
input: "$users",
as: "user",
cond: {
$eq: [
"$$user.uuid",
"$$uuid"
]
}
}
}
}
},
{
$unwind: "$users"
},
{
$replaceRoot: {
newRoot: {
isOwner: "$users.isOwner",
createdOn: "$users.createdOn"
}
}
}
],
as: "vehicles"
}
},
{
$facet: {
"createdOn": [
{
$match: {
"vehicles": {
$elemMatch: {
isOwner: true,
$and: [
{
"createdOn": {
$gte: "2019-05-15T00: 00: 00"
}
},
{
"createdOn": {
$lt: "2019-05-16T00: 00: 00"
}
}
]
}
}
}
},
{
$project: {
culture: 1,
count: {
$size: "$vehicles"
}
}
},
{
$group: {
_id: 0,
"total": {
$sum: "$count"
}
}
}
]
}
},
{
$project: {
"CreatedOn": {
$arrayElemAt: [
"$CreatedOn.total",
0
]
}
}
}
])
I get following result:
[
{
"createdOn": 2
}
]
What I would like to achieve is a result as follows:
[
{
culture: "it-it",
results: {
"createdOn": 1
}
},
{
culture: "de-de",
results: {
"createdOn": 1
}
}
]
But I cannot seem to figure out where I can group so that I can get that result.
Can someone show me the way to do this?
The query is more complex with more metrics so this is a trimmed down version of what I have.
I tried grouping everywhere but fail to get the desired result I want.
The following query can get us the expected output:
db.customers.aggregate([
{
$lookup: {
"from": "vehicles",
"let": {
"uuid": "$uuid"
},
"pipeline": [
{
$unwind: "$users"
},
{
$match: {
$expr: {
$and: [
{
$eq: ["$users.uuid", "$$uuid"]
},
{
$eq: ["$users.isOwner", true]
},
{
$gte: ["$users.createdOn", "2019-05-15T00: 00: 00"]
},
{
$lte: ["$users.createdOn", "2019-05-16T00: 00: 00"]
}
]
}
}
},
{
$count:"totalVehicles"
}
],
as: "vehiclesInfo"
}
},
{
$unwind: {
"path": "$vehiclesInfo",
"preserveNullAndEmptyArrays": true
}
},
{
$group: {
"_id": "$culture",
"culture": {
$first: "$culture"
},
"createdOn": {
$sum: "$vehiclesInfo.totalVehicles"
}
}
},
{
$project: {
"_id": 0,
"culture": 1,
"results.createdOn": "$createdOn"
}
}
]).pretty()
Output:
{ "culture" : "de-de", "results" : { "createdOn" : 1 } }
{ "culture" : "it-it", "results" : { "createdOn" : 1 } }