In a previous post I created a mongodb query projecting the number of elements matching a condition in an array. Now I need to filter this number of elements depending on another field.
This is my db :
db={
"fridges": [
{
_id: 1,
items: [
{
itemId: 1,
name: "beer"
},
{
itemId: 2,
name: "chicken"
}
],
brand: "Bosch",
size: 195,
cooler: true,
color: "grey",
nbMax: 2
},
{
_id: 2,
items: [
{
itemId: 1,
name: "beer"
},
{
itemId: 2,
name: "chicken"
},
{
itemId: 3,
name: "lettuce"
}
],
brand: "Electrolux",
size: 200,
cooler: true,
color: "white",
nbMax: 2
},
]
}
This is my query :
db.fridges.aggregate([
{
$match: {
$and: [
{
"brand": {
$in: [
"Bosch",
"Electrolux"
]
}
},
{
"color": {
$in: [
"grey",
"white"
]
}
}
]
}
},
{
$project: {
"itemsNumber": {
$size: {
"$filter": {
"input": "$items",
"as": "item",
"cond": {
$in: [
"$$item.name",
[
"beer",
"lettuce"
]
]
}
}
}
},
brand: 1,
cooler: 1,
color: 1,
nbMax: 1
}
}
])
The runnable example.
Which gives me this :
[
{
"_id": 1,
"brand": "Bosch",
"color": "grey",
"cooler": true,
"itemsNumber": 1,
"nbMax": 2
},
{
"_id": 2,
"brand": "Electrolux",
"color": "white",
"cooler": true,
"itemsNumber": 2,
"nbMax": 2
}
]
What I expect is to keep only the results having a itemsNumber different from nbMax. In this instance, the second fridge with _id:2 would not match the condition and should not be in returned. How can I modify my query to get this :
[
{
"_id": 1,
"brand": "Bosch",
"color": "grey",
"cooler": true,
"itemsNumber": 1,
"nbMax": 2
}
]
You can put a $match stage with expression condition at the end of your query,
$ne to check both fields should not same
{
$match: {
$expr: { $ne: ["$nbMax", "$itemsNumber"] }
}
}
Playground
Related
I'm trying to count my "$attendance.status" with aggregation mongodb.
I've get my data with relations. then i want to count by relation columns like 'present', 'off', etc.
code
Employee.aggregate([
{
$lookup: {
from: "Attendance",
let: { employeeId: "$_id" },
pipeline: [
{
$match: {
$and: [
{ $expr: { $eq: ["$employeeId", "$$employeeId"] } },
{ isApproved: true },
{
createdAt: {
$gte: startOfMonth.toDate(),
$lte: endOfMonth.toDate(),
},
},
],
},
},
],
as: "attendance",
},
},
{
$project: {
_id: 1,
username: 1,
name: 1,
attendance: 1,
present: { $sum: { $eq: ["$attendance.status", "present"] } },
},
},
]);
But why cannot count my column?
i use $eq, with $sum then count the result. but the result is 0
{
"username": "Ethyl",
"name": "Kuhn",
"id": "614d43cde735f3e601dea165",
"attendance": [
{
"_id": "614d43cde735f3e601dea16f",
"status": "present",
"start": "2021-09-24T03:19:41.645Z",
"employeeId": "614d43cde735f3e601dea165",
"isApproved": true
},
],
"present": 0,
"sick": 0,
"off": 0,
},
I have a collection of fridges and I would like to have some fields from each fridge matching a condition plus the 'conditionnal size' of the items in this fridge.
This is an example of my DB :
db={
"fridges": [
{
_id: 1,
items: [
{
itemId: 1,
name:"beer"
},
{
itemId: 2,
name: "chicken"
}
],
brand:"Bosch",
size:195,
cooler:true,
color:"grey"
},
{
_id: 2,
items: [
{
itemId: 1,
name:"beer"
},
{
itemId: 2,
name: "chicken"
},
{
itemId: 3,
name: "lettuce"
}
],
brand:"Electrolux",
size:200,
cooler:true,
color:"white"
},
]
}
I want to get fridges with these mutuals conditions ('and' condition):
brand is $in ["Bosch","Samsung"]
color is $in ["grey","white"]
In addition :
The number of items with a name $in ["beer","lettuce"]
And finally :
Removing some fields like the size and items of the result.
In our example, the excepted output would be :
{
_id:1
itemsNumber:1,
brand:"Bosch",
cooler:true,
color:"grey"
}
Explanations :
We removed the field items and size, itemsNumber counts the number of beers and lettuce from items array. And we only keep the first fridge its brand is Bosch and it's grey.
This what I have so far :
db.fridges.aggregate([
{
"$match": {
$and: [
{
"brand": {
$in: [
"Bosch",
"Samsung"
]
}
},
{
"color": {
$in: [
"grey",
"white"
]
}
}
]
}
},
{
"$project": {
"itemsNumber": {
$size: "$items" // This is not good
},
brand: 1,
cooler: 1,
color: 1
}
}
])
Which returns me :
[
{
"_id": 1,
"brand": "Bosch",
"color": "grey",
"cooler": true,
"itemsNumber": 2
}
]
Counting the items matching with either beer or lettuce is my main problem.
This is an executable example.
Thanks in advance !
I found out how to make it work. Thank you #joe for suggesting to use filter this was indeed the solution.
Here is the complete query :
db.fridges.aggregate([
{
$match: {
$and: [
{
"brand": {
$in: [
"Bosch",
"Samsung"
]
}
},
{
"color": {
$in: [
"grey",
"white"
]
}
}
]
}
},
{
$project: {
"itemsNumber": {
"$filter": {
"input": "$items",
"as": "item",
"cond": {
$in: [
"$$item.name",
[
"beer",
"lettuce"
]
]
}
}
},
brand: 1,
cooler: 1,
color: 1
}
}
])
Runnable example.
I have a collection from which I need specific obj e.g. notes.blok2 and notes.curse5 as an object, not as an array
{
"year":2020,
"grade":4,
"seccion":"A",
"id": 100,
"name": "pedro",
"notes":[{"curse":5,
"block":1,
"score":{ "a1": 5,"a2": 10, "a3": 15}
},{"curse":5,
"block":2,
"score":{ "b1": 10,"b2": 20, "b3": 30}
}
]
}
My query
notas.find({
"$and":[{"grade":1},{"seccion":"A"},{"year":2020}]},
{"projection":{ "grade":1, "seccion":1,"name":1,"id":1,
"notes":{"$elemMatch":{"block":2,"curse":5}},"notes.score":1} })
It works but returns notes like array
{
"_id": "55",
"id": 100,
"grade": 5,
"name": "pedro",
"seccion": "A",
"notes": [
{"score": { "b1": 10,"b2": 20, "b3": 30} }
]
}
But I NEED LIKE THIS: score at the same level as others and if doesn't exist show empty "score":{}
{
"year":2020,
"grade":5,
"seccion":"A",
"id": 100,
"name": "pedro",
"score":{ "b1": 10,"b2": 20, "b3": 30}
}
Demo - https://mongoplayground.net/p/XlJqR2DYW1X
You can use aggregation query
db.collection.aggregate([
{
$match: { // filter
"grade": 1,
"seccion": "A",
"year": 2020,
"notes": {
"$elemMatch": {
"block": 2,
"curse": 5
}
}
}
},
{ $unwind: "$notes" }, //break into individual documents
{
$match: { // match query on individual note
"notes.block": 2,
"notes.curse": 5
}
},
{
$project: { // projection
"grade": 1,
"seccion": 1,
"name": 1,
"id": 1,
"score": "$notes.score"
}
}
])
Update
Demo - https://mongoplayground.net/p/mq5Kue3UG42
Use $filter
db.collection.aggregate([
{
$match: {
"grade": 1,
"seccion": "A",
"year": 2020
}
},
{
$set: {
"score": {
"$filter": {
"input": "$notes",
"as": "note",
"cond": {
$and: [
{
$eq: [ "$$note.block",3]
},
{
$eq: [ "$$note.curse", 5 ]
}
]
}
}
}
}
},
{
$project: {
// projection
"grade": 1,
"seccion": 1,
"name": 1,
"id": 1,
"score": {
"$first": "$score.score"
}
}
}
])
If you want empty object for score when match not found you can do -
Demo - https://mongoplayground.net/p/dumax58kgrc
{
$set: {
score: {
$cond: [
{ $size: "$score" }, // check array length
{ $first: "$score" }, // true - take 1st
{ score: {} } // false - set empty object
]
}
}
},
I have been searching on stackoverflow and cannot find exactly what I am looking for and hope someone can help. I want to submit a single query, get multiple counts back, for a single document, based on array of that document.
My data:
db.myCollection.InsertOne({
"_id": "1",
"age": 30,
"items": [
{
"id": "1",
"isSuccessful": true,
"name": null
},{
"id": "2",
"isSuccessful": true,
"name": null
},{
"id": "3",
"isSuccessful": true,
"name": "Bob"
},{
"id": "4",
"isSuccessful": null,
"name": "Todd"
}
]
});
db.myCollection.InsertOne({
"_id": "2",
"age": 22,
"items": [
{
"id": "6",
"isSuccessful": true,
"name": "Jeff"
}
]
});
What I need back is the document and the counts associated to the items array for said document. In this example where the document _id = "1":
{
"_id": "1",
"age": 30,
{
"totalIsSuccessful" : 2,
"totalNotIsSuccessful": 1,
"totalSuccessfulNull": 1,
"totalNameNull": 2
}
}
I have found that I can get this in 4 queries using something like this below, but I would really like it to be one query.
db.test1.aggregate([
{ $match : { _id : "1" } },
{ "$project": {
"total": {
"$size": {
"$filter": {
"input": "$items",
"cond": { "$eq": [ "$$this.isSuccessful", true ] }
}
}
}
}}
])
Thanks in advance.
I am assuming your expected result is invalid since you have an object literal in the middle of another object and also you have totalIsSuccessful for id:1 as 2 where it seems they should be 3. With that said ...
you can get similar output via $unwind and then grouping with $sum and $cond:
db.collection.aggregate([
{ $match: { _id: "1" } },
{ $unwind: "$items" },
{ $group: {
_id: "_id",
age: { $first: "$age" },
totalIsSuccessful: { $sum: { $cond: [{ "$eq": [ "$items.isSuccessful", true ] }, 1, 0 ] } },
totalNotIsSuccessful: { $sum: { $cond: [{ "$ne": [ "$items.isSuccessful", true ] }, 1, 0 ] } },
totalSuccessfulNull: { $sum: { $cond: [{ "$eq": [ "$items.isSuccessful", null ] }, 1, 0 ] } },
totalNameNull: { $sum: { $cond: [ { "$eq": [ "$items.name", null ]}, 1, 0] } } }
}
])
The output would be this:
[
{
"_id": "_id",
"age": 30,
"totalIsSuccessful": 3,
"totalNameNull": 2,
"totalNotIsSuccessful": 1,
"totalSuccessfulNull": 1
}
]
You can see it working here
Here's the structure part of my collection:
_id: ObjectId("W"),
names: [
{
number: 1,
subnames: [ { id: "X", day: 1 }, { id: "Y", day: 10 }, { id: "Z", day: 2 } ],
list: ["A","B","C"],
day: 1
},
{
number: 2,
day: 5
},
{
number: 3,
subnames: [ { id: "X", day: 8 }, { id: "Z", day: 5 } ],
list: ["A","C"],
day: 2
},
...
],
...
I use this request:
db.publication.aggregate( [ { $match: { _id: ObjectId("W") } }, { $group: { _id: "$_id", SizeName: { $first: { $size: { $ifNull: [ "$names", [] ] } } }, names: { $first: "$names" } } }, { $unwind: "$names" }, { $sort: { "names.day": 1 } }, { $group: { _id: "$_id", SzNames: { $sum: 1 }, names: { $push: { number: "$names.number", subnames: "$names.subnames", list: "$names.list", SizeList: { $size: { $ifNull: [ "$names.list", [] ] } } } } } } ] );
but I would now use $sort for my names array AND my subnames array to obtain this result (subnames may not exist) :
_id: ObjectId("W"),
names: [
{
number: 2,
SizeList: 0,
day: 5
},
{
number: 3,
subnames: [ { id: "Z", day: 5 }, { id: "X", day: 8 } ],
list: ["A","C"],
SizeList: 2,
day: 2
},
{
number: 1,
subnames: [ { id: "X", day: 1 }, { id: "Z", day: 2 }, { id: "Y", day: 10 } ],
list: ["A","B","C"],
SizeList: 3,
day: 1
}
...
],
...
Can you help me ?
You can do this, but with great difficulty. I for one would gladly vote for an inline version of $sort along the lines of the $map operator. That would makes things so much easier.
For now though you need to de-construct and re-build the arrays after sorting. And you have to be very careful about this. Hence make false arrays with a single entry before processing $unwind:
db.publication.aggregate([
{ "$project": {
"SizeNames": {
"$size": {
"$ifNull": [ "$names", [] ]
}
},
"names": { "$ifNull": [{ "$map": {
"input": "$names",
"as": "el",
"in": {
"SizeList": {
"$size": {
"$ifNull": [ "$$el.list", [] ]
}
},
"SizeSubnames": {
"$size": {
"$ifNull": [ "$$el.subnames", [] ]
}
},
"number": "$$el.number",
"day": "$$el.day",
"subnames": { "$ifNull": [ "$$el.subnames", [0] ] },
"list": "$$el.list"
}
}}, [0] ] }
}},
{ "$unwind": "$names" },
{ "$unwind": "$names.subnames" },
{ "$sort": { "_id": 1, "names.subnames.day": 1 } },
{ "$group": {
"_id": {
"_id": "$_id",
"SizeNames": "$SizeNames",
"names": {
"SizeList": "$names.SizeList",
"SizeSubnames": "$names.SizeSubnames",
"number": "$names.number",
"list": "$names.list",
"day": "$names.day"
}
},
"subnames": { "$push": "$names.subnames" }
}},
{ "$sort": { "_id._id": 1, "_id.names.day": 1 } },
{ "$group": {
"_id": "$_id._id",
"SizeNames": { "$first": "$_id.SizeNames" },
"names": {
"$push": { "$cond": [
{ "$ne": [ "$_id.names.SizeSubnames", 0 ] },
{
"number": "$_id.names.number",
"subnames": "$subnames",
"list": "$_id.names.list",
"SizeList": "$_id.names.SizeList",
"day": "$_id.names.day"
},
{
"number": "$_id.names.number",
"list": "$_id.names.list",
"SizeList": "$_id.names.SizeList",
"day": "$_id.names.day"
}
]}
}
}},
{ "$project": {
"SizeNames": 1,
"names": {
"$cond": [
{ "$ne": [ "$SizeNames", 0 ] },
"$names",
[]
]
}
}}
])
You can kind of "hide away" the original empty array from the inner document as shown, but it's really difficult to remove all presence of the outer "names" array without pulling a similar conditional array "push" technique, and that really isn't a practical approach.
If all of this is just about sorting array elements in individual documents though, the aggregation framework should not be the tool to do this. It can be done as shown, but per document this is much easier to do in client side code.
Output:
{
"_id" : ObjectId("54b5cff8102f292553ce9bb5"),
"SizeNames" : 3,
"names" : [
{
"number" : 1,
"subnames" : [
{
"id" : "X",
"day" : 1
},
{
"id" : "Z",
"day" : 2
},
{
"id" : "Y",
"day" : 10
}
],
"list" : [
"A",
"B",
"C"
],
"SizeList" : 3,
"day" : 1
},
{
"number" : 3,
"subnames" : [
{
"id" : "Z",
"day" : 5
},
{
"id" : "X",
"day" : 8
}
],
"list" : [
"A",
"C"
],
"SizeList" : 2,
"day" : 2
},
{
"number" : 2,
"SizeList" : 0,
"day" : 5
}
]
}