Hello friend I am not friendly with mongodb aggregation I want is that I have array of object that contains subjects with its score for each question and I am using node js so I want is that full calculation with mongo query if possible that include subject name with its total score and count of attempt and not attempt my Json Array is as bellow
{
"examId": ObjectId("597367af7d8d3219d88c4341"),
"questionId": ObjectId("597368207d8d3219d88c4342"),
"questionNo": 1,
"subject": "Reasoning Ability",
"yourChoice": "A",
"correctMark": "1",
"attempt": true,
"notAttempt": false,
}
here in object one field is for correct marks subject are different an I want an output like
|Subject Name | Total attempts | total not attempts | total score |
| A | 5 | 3 | 10 |
| B | 10 | 5 | 25 |
I am trying with aggregation but not done yet I have tried this query
db.examscores.aggregate([
{ $group:{
_id:"$examId",
score: { $sum: '$correctMark' },
count: { $sum: 1 }
}}
])
Any one has idea how to achieve this type of output.
and if another way to achieve this using node than also good.
I have solved this here is my query
[
{ $match: { subject:'Reasoning Ability' } },
{
$group:
{
_id:{id:"$examId",subject:'$subject'},
totalAttempt: { $sum: {$cond : [ "$attempt", 1, 0 ]} },
totalNotAttempt: { $sum: {$cond : [ "$notAttempt", 1, 0 ]} },
markedForReview:{ $sum: {$cond : [ "$markedForReview", 1, 0 ]} },
answerAndMarkedForReview:{ $sum: {$cond : [ "$answerAndMarkedForReview", 1, 0 ]} },
score: { $sum: '$correctMark' },
count: { $sum: 1 }
}
}
]
Related
I have tree records in mongodb but there could be many more, I'm getting shops by an ID coming from frontend
I need to get 20 records and group them by itemId and colorId, and get counts for every shop. the count of shops can be 1,2,3,....10etc..
this is output I need:
+--------+----------+-------+-------+-------+
| itemId | colorId | shop1 | shop2 | shop3 |
+========+==========+=======+=======+=======+
| 1 | colorId1 | 5 | 0 | 3 |
+--------+----------+-------+-------+-------+
| 2 | colorId2 | 3 | 0 | 0 |
+--------+----------+-------+-------+-------+
| 3 | colorId2 | 0 | 3 | 0 |
+--------+----------+-------+-------+-------+
| 2 | colorId1 | 0 | 5 | 0 |
+--------+----------+-------+-------+-------+
| 3 | colorId1 | 0 | 0 | 5 |
+--------+----------+-------+-------+-------+
here is my data and query - here shopId is string and it's work good.
but when I use this query on my local mashine, I'm getting this error:
MongoError: PlanExecutor error during aggregation :: caused by :: $arrayToObject requires an object with keys 'k' and 'v', where the value of 'k' must be of type string. Found type: objectId
but when I change shopId to the ObjectId I'm getting error.
ObjectId versoin
Per your request in the comments (if I got it right):
db.collection.aggregate([
{
"$match": {}// <-- Highly recommend you to use match due to the complexity of this query
},
{
$group: {
_id: 0,
data: {
$push: {
shopId: "$shopId",
shopItems: "$shopItems"
}
},
shopIds: {
"$push": {
shopId: "$shopId",
"count": 0
}
}
}
},
{
$unwind: "$data"
},
{
$unwind: "$data.shopItems"
},
{
$group: {
_id: {
itemId: "$data.shopItems.itemId",
colorId: "$data.shopItems.colorId"
},
data: {
$push: {
shopId: "$data.shopId",
count: "$data.shopItems.itemCount"
}
},
existing: {
$push: {
shopId: "$data.shopId",
"count": 0
}
},
shopIds: {
$first: "$shopIds"
}
}
},
{
"$addFields": {
"missing": {
"$setDifference": [
"$shopIds",
"$existing"
]
}
}
},
{
$project: {
data: {
$concatArrays: [
"$data",
"$missing"
]
}
}
},
{
$unwind: "$data"
},
{
$sort: {
"data.shopId": 1
}
},
{
$group: {
_id: "$_id",
counts: { // here you can change this key
$push: "$data"
},
totalCount: {
$sum: "$data.count" // if you want it
}
}
}
])
After the first $match, we $group in order to get all shopIds in each document.
Next we $unwind and $group by the group you wanted: by colorId and itemId. Then we are adding all the shops with count 0 and removing the ones that do have actual count. Last three steps are just for sorting, summing and formating.
You can play with it here.
I'm having to deal with a query that is kind of strange. I'm creating an app for boat tracking: I have a collections of documents with the timestamp and the Port ID where it was the board at that moment.
After sorting all the documents of this collection by the timestamp descending, I need to grab the elements that have the same Port ID in that range of time.
For example:
timestamp | port_id
2021-11-10T23:00:00.000Z | 1
2021-11-10T22:00:00.000Z | 1
2021-11-10T21:00:00.000Z | 1
2021-11-10T20:00:00.000Z | 2
2021-11-10T19:00:00.000Z | 2
2021-11-10T18:00:00.000Z | 2
2021-11-10T17:00:00.000Z | 1
2021-11-10T16:00:00.000Z | 1
2021-11-10T15:00:00.000Z | 1
Having this data (sorted by timestamp), I would have to grab the first 3 documents. The way I'm doing this now, is grabbing 2000 documents and implementing a filter function in the application level.
Another approch would be grabbing the first element, and then filtering by that port id, but that returns me 6 elements, not the first 3.
Do you know any way to perform a query like this in Mongo? Thanks!
Use $setWindowFields
db.collection.aggregate([
{
$setWindowFields: {
partitionBy: "",
sortBy: { timestamp: -1 },
output: {
c: {
$shift: {
output: "$port_id",
by: -1,
default: "Not available"
}
}
}
}
},
{
$set: {
c: {
$cond: {
if: { $eq: [ "$port_id", "$c" ] },
then: 0,
else: 1
}
}
}
},
{
$setWindowFields: {
partitionBy: "",
sortBy: { timestamp: -1 },
output: {
c: {
$sum: "$c",
window: { documents: [ "unbounded", "current" ] }
}
}
}
},
{
$match: { c: 1 }
},
{
$unset: "c"
}
])
mongoplayground
In the pipeline stage before the $group stage computed the document like bellow
cycle_id | entity1 | entity 2
1 | 0 | 1
1 | 1 | 5
2 | 0 | 3
I am able to group them using bellow script
{
"$group" : {
"_id" : "$cycle_id",
"entity1" : {
"$sum" : "$entity1"
},
"entity2" : {
"$sum" : "$entity3"
},
"entity3" : {
"$sum" : "$entity3"
}
}
}
This generated output like bellow:
cycle_id | entity1 | entity 2
1 | 1 | 6
2 | 0 | 3
but what I am looking for is something where I can project it like an array of key-value pair
{
1:{
entity1: 1,
entiry2: 6
},
2:{
entity1: 3,
entiry2: 4
}
}
Is there a way I can achieve the above result. I tried to look around $arrayToObject but wasn't quite successful with that yet.
Thanks,
Nixit
Query :
db.collection.aggregate([
/** Group without any condition and merge all documents (Converted objects) into an object */
{
$group: {
_id: "",
data: {
$mergeObjects: {
$arrayToObject: [ [ { k: { $toString: "$_id" }, v: { "entity1": "$entity1", "entity2": "$entity2" } } ] ]
}
}
}
},
/** Replace `data` field as a root of the document */
{
$replaceRoot: { newRoot: "$data" }
}
])
Test : mongoplayground
Ref : aggregation-pipeline
I have a MongoDb collection genre_count as
user | genre | count
-----+---------------+-------
1 | Western | 2
1 | Adventure | 1
1 | Comedy | 5
2 | Western | 3
2 | Thriller | 1
2 | Romance | 2
I need to extract the genre for each user with maximum count i.e. for user 1 , the genre with maximum count is Comedy with Count 5. I tried using couple of ways as:
db.genre_count.aggregate([
{
$group:{
_id:{
user:"$user",
genre:"$genre"
},
max_val:{
$max: "$count"
}
}
}
])
I thought this would work but it returned the count of the user for each genre so basically it returned me all the records.
Then I tried another solution which worked partially in :
db.genre_count.aggregate([
{
$group:{
_id:{
user:"$user"
},
max_val:{
$max: "$count"
}
}
}
])
But this only returned the maximum value as it has no corresponding genre information for that maximum value. Is there any way I can get the desired result?
To return the maximum count and genre list, you need to use the $max in your group stage to return the maximum "Count" for each group then use $push accumulator operator to return a list of "Genre Name" and "Count" for each group.
From there you need to use the $map operator in your $project stage to return a list of genre_names alongside the maximum count. The $cond here is used to compare each genre count to the maximum value.
db.genre_count.aggregate([
{ '$group': {
'_id': '$user',
'maxCount': { '$max': '$count' },
'genres': {
'$push': {
'name': '$genre',
'count': '$count'
}
}
}},
{ '$project': {
'maxCount': 1,
'genres': {
'$setDifference': [
{ '$map': {
'input': '$genres',
'as': 'genre',
'in': {
'$cond': [
{ '$eq': [ '$$genre.count', '$maxCount' ] },
'$$genre.name',
false
]
}
}},
[false]
]
}
}}
])
I think you can use this aggregate:
db.genre_count.aggregate([
{
$sort: {user:1, count:1}
},
{
$group:
{
_id: "$user",
maxCount: {$max: "$count"},
genre: {$last: "$genre"}
}
}])
This is a simplified version of my source data:
Cars | Manual | Petrol
1 | true | true
2 | true | false
3 | true | true
4 | true | true
5 | false | true
6 | false | true
I am trying to obtain this output:
Total cars: 6
Manual cars: 4
Petrol cars: 5
Is this possible in MongoDB using a single aggregation pipeline?
Yes, you can do this with the $group aggregation step and the $sum operator combined with $cond.
db.collection.aggregate([
$group: {
_id: null, // we want to group into a single document
"Total Cars": { $sum: 1 }, // all documents
"Manual Cars": {
$sum : {
// add a "1" when Manual is true, otherwise add a "0"
$cond: [ { $eq: [ "$Manual", true ] }
1,
0
]
}
},
"Petrol Cars": {
$sum : {
$cond: [ { $eq: [ "$Petrol", true ] }
1,
0
]
}
}
}
]);