I have a collection with the following data structure:
{
_id: ObjectId,
text: 'This contains some text',
type: 'one',
category: {
name: 'Testing',
slug: 'test'
},
state: 'active'
}
What I'm ultimately trying to do is get a list of categories and counts. I'm using the following:
const query = [
{
$match: {
state: 'active'
}
},
{
$project: {
_id: 0,
categories: 1
}
},
{
$unwind: '$categories'
},
{
$group: {
_id: { category: '$categories.name', slug: '$categories.slug' },
count: { $sum: 1 }
}
}
]
This returns all categories (that are active) and the total counts for documents matching each category.
The problem is that I want to introduce two additional $match that should still return all the unique categories, but only affect the counts. For example, I'm trying to add a text search (which is indexed on the text field) and also a match for type.
I can't do this at the top of the pipeline because it would then only return categories that match, not only affect the $sum. So basically it would be like being able to add a $match within the $group only for the $sum. Haven't been able to find a solution for this and any help would be greatly appreciated. Thank you!
You can use $cond inside of your $group statement:
{
$group: {
_id: { category: '$categories.name', slug: '$categories.slug' },
count: { $sum: { $cond: [ { $eq: [ "$categories.type", "one" ] }, 1, 0 ] } }
}
}
Related
I have this collection(some irrelevant fields were omitted for brevity):
clients: {
userId: ObjectId,
clientSalesValue: Number,
currentDebt: Number,
}
Then I have this query that matches all the clients for a specific user, then calculates the sum of all debts and sales and put those results in a separate field each of them:
await clientsCollection.aggregate([
{
$match: { userId: new ObjectId(userId) }
},
{
$group: {
_id: null,
totalSalesValue: { $sum: '$clientSalesValue' },
totalDebts: { $sum: '$currentDebt' },
}
},
{
$unset: ['_id']
}
]).exec();
This works as expected, it returns an array with only one item which is an object, but now I need to also include in that resultant object a field for the amount of debtors, that is for the amount of clients that have currentDebt > 0, how can I do that is the same query? is it possible?
PD: I cannot modify the $match condition, it need to always return all the clients for the corresponding users.
To include a count of how many matching documents have a positive currentDebt, you can use the $sum and $cond operators like so:
await clientsCollection.aggregate([
{
$match: { userId: new ObjectId(userId) }
},
{
$group: {
_id: null,
totalSalesValue: { $sum: '$clientSalesValue' },
totalDebts: { $sum: '$currentDebt' },
numDebtors: {
$sum: {
$cond: [{ $gt: ['$currentDebt', 0] }, 1, 0]
}
},
}
},
{
$unset: ['_id']
}
]).exec();
I have an issue that need to insert index number when get data. First i have this data for example:
[
{
_id : 616efd7e56c9530018e318ac
student : {
name: "Alpha"
email: null
nisn: "0408210001"
gender : "female"
}
},
{
_id : 616efd7e56c9530018e318af
student : {
name: "Beta"
email: null
nisn: "0408210001"
gender : "male"
}
}
]
and then i need the output like this one:
[
{
no:1,
id:616efd7e56c9530018e318ac,
name: "Alpha",
nisn: "0408210001"
},
{
no:2,
id:616efd7e56c9530018e318ac,
name: "Beta",
nisn: "0408210002"
}
]
i have tried this code but almost get what i expected.
{
'$project': {
'_id': 0,
'id': '$_id',
'name': '$student.name',
'nisn': '$student.nisn'
}
}
but still confuse how to add the number of index. Is it available to do it in $project or i have to do it other way? Thank you for the effort to answer.
You can use $unwind which can return an index, like this:
db.collection.aggregate([
{
$group: {
_id: 0,
data: {
$push: {
_id: "$_id",
student: "$student"
}
}
}
},
{
$unwind: {path: "$data", includeArrayIndex: "no"}
},
{
"$project": {
"_id": 0,
"id": "$data._id",
"name": "$data.student.name",
"nisn": "$data.student.nisn",
"no": {"$add": ["$no", 1] }
}
}
])
You can see it works here .
I strongly suggest to use a $match step before these steps, otherwise you will group your entire collection into one document.
You need to run a pipeline with a $setWindowFields stage that allows you to add a new field which returns the position of a document (known as the document number) within a partition. The position number creation is made possible by the $documentNumber operator only available in the $setWindowFields stage.
The partition could be an extra field (which is constant) that can act as the window partition.
The final stage in the pipeline is the $replaceWith step which will promote the student embedded document to the top-level as well as replacing all input documents with the specified document.
Running the following aggregation will yield the desired results:
db.collection.aggregate([
{ $addFields: { _partition: 'students' }},
{ $setWindowFields: {
partitionBy: '$_partition',
sortBy: { _id: -1 },
output: { no: { $documentNumber: {} } }
} },
{ $replaceWith: {
$mergeObjects: [
{ id: '$_id', no: '$no' },
'$student'
]
} }
])
Suppose I want to sort the data based on the current city first and then the remaining country data. Is there any way I achieve that in MongoDB?
Example
[
{ id: 2, name: 'sdf' },
{ id: 3, name: 'sfs' },
{ id: 3, name: 'aaa' },
{ id: 1, name: 'dsd' },
];
What I want as an outcome is the data with id 3 at first and the remaining other.
like
[
{ id: 3, name: 'sfs' },
{ id: 3, name: 'aaa' },
{ id: 1, name: 'dsd' },
{ id: 2, name: 'sdf' },
];
It's just a example,
My actual requirement is to sort the data based on certain category first and then the remaining one
It's not possible within mongodb but you could first fetch the documents from the db and then sort them in Javascript (or whatever other language you're using to present the data).
On a side note, having duplicate values in the "id" field is not a good practice and defies the definition of id itself.
There is no straight way to sort condationaly in MongoDB, as per your example you can try aggregation query,
$facet to separate result for both types of documents
first, to get id: 3 documents
second, to get id is not 3 documents and sort by id in ascending order
$project and $concatArrays to concat both arrays in siquance
$unwind deconstruct all array
$replaceRoot to replace all object to root
db.collection.aggregate([
{
$facet: {
first: [
{ $match: { id: 3 } }
],
second: [
{ $match: { id: { $ne: 3 } } },
{ $sort: { id: 1 } }
]
}
},
{
$project: {
all: { $concatArrays: ["$first", "$second"] }
}
},
{ $unwind: "$all" },
{ $replaceRoot: { newRoot: "$all" } }
])
Playground
Let's say that I have some document with this structure:
_id: ObjectId('444455'),
name: 'test',
email: 'email,
points: {
spendable: 23,
history: [
{
comment: 'Points earned by transaction #1234',
points: 1
},
{
comment: 'Points earned by transaction #456',
points: 3
},
{
comment: 'Points earned by transaction #456',
points: 3
}
]
}
}
Now I have a problem that some documents contains duplicates objects in the points.history array.
Is there a way to easily find all those duplicates by a query?
I already tried this query: Find duplicate records in MongoDB
but that shows the total count of every duplicated line in all documents. I need a overview of the duplicates per document like this:
{
_id: ObjectId('444455') //_id of the document not of the array item itself
duplicates: [
{
comment: 'Points earned by transaction #456
}
]
}, {
_id: ObjectId('444456') //_id of the document not of the array item itself
duplicates: [
{
comment: 'Points earned by transaction #66234
},
{
comment: 'Points earned by transaction #7989
}
]
}
How can I achieve that?
Try below aggregate pipeline
collectionName.aggregate([
{
$unwind: "$points.history"
},
{
$group: {
_id: {
id: "$_id",
comment: "$points.history.comment",
points: "$points.history.points"
},
sum: {
$sum: 1
},
}
},
{
$match: {
sum: {
$gt: 1
}
}
},
{
$project: {
_id: "$_id._id",
duplicates: {
comment: "$_id.comment"
}
}
}
])
So I have 2 models: Question and Answer.
Answer has: questionId, userId, answer (String).
I need an aggregation pipline that will:
match all answers by questionId
see if the current user already voted (is his id in matched documents)
group answers and count them
I implemented 1 and 3 like this:
const q = ObjectId('5d6e52a68558b63fb9302efd');
const user = ObjectId('5d0b3f7daceeb50c477b49e0');
Answer.aggregate([
{ $match: { questionId: q } },
{ $group: { _id: '$answer', count: { $sum: 1 } } },
])
I am missing a step between those 2 aggregation pipelines, where I would iterate thru matched documents, and check if userId matches user.
I would like to get some object like this:
{
didIVote: true,
result: [ { _id: 'YES', count: 5 }, { _id: 'NO', count: 2 } ]
}
Or maybe even like this:
[
{ _id: 'YES', count: 5, didIVote: true },
{ _id: 'NO', count: 2, didIVote: false },
]
In the $group stage, create an array with the users that voted
for each answer.
Add an aditional $project stage to check if the user is in the array.
const q = ObjectId('5d6e52a68558b63fb9302efd');
const user = ObjectId('5d0b3f7daceeb50c477b49e0');
Answer.aggregate([
{ $match: { questionId: q } },
{
$group: {
_id: '$answer',
count: { $sum: 1 },
voted: { $addToSet: "$userId" }
}
},
{
$project: {
count: 1,
didIVote: { $in: [ user, "$voted" ] },
}
}
]);