I'm using updateOne method like this:
Photo.updateOne(
{
"_id": photoId
},
{
"$pull": {
comments: {
_id: ObjectID(commentId),
"user.id": user.id
}
},
"$inc": { "commentCount": -1 },
},
)
Photo model which contains comments as a array and commentCount as a number. When I run the code it's working but if the photo doesn't have the comment (which I'm trying to pull) it's still incrementing commentCount by -1. What I want is, if the code does not pull any comment in photo comments, don't update the commentCount too. How can I add this rule to my code?
Thanks for help.
You can also add both fields comments._id and comments.use.id conditions in query part, if comment is not available then it will skip update and pull part.
Photo.updateOne(
{
_id: photoId,
comments: {
$elemMatch: {
_id: ObjectID(commentId),
"user.id": user.id
}
}
},
{
"$pull": {
comments: {
_id: ObjectID(commentId),
"user.id": user.id
}
},
"$inc": { "commentCount": -1 }
}
)
There is no such feature existing in Mongo, What you can do if you're using Mongo v4.2+ is use pipelined update, as the name suggests this gives you the power to use a pipeline within an update, hence allowing us to have conditions based on previous results.
Photo.updateOne(
{ "_id": photoId },
[
{
$set: {
comments: {
$filter: {
input: "$comments",
as: "comment",
cond: {
$and: [
{$ne: ["$$comment._id", ObjectID(commentId)]},
{$ne: ["$$comment.user.id", user.id]} //really necessary?
]
}
}
}
}
},
{
$set: {
commentCount: {$size: "$comments"}
}
}
]
)
For lesser versions you'll have to split it into 2 calls. no way around it.
-------------- EDIT ---------------
You can update the query to find the document using $elemMatch, if it's not found then it means the comment belonged to someone else and you can throw an error in that case.
Photo.updateOne(
{
_id: photoId,
comments: {
$elemMatch: {
_id: objectID(commentId),
"user.id": user.id
}
}
},
{
"$pull": {
comments: {
_id: ObjectID(commentId),
"user.id": user.id
}
},
"$inc": { "commentCount": -1 }
}
)
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]
}
},
}
},
{
$unset: ['_id']
}
]).exec();
I have two collections: Sharing and Material.
Sharing:
{
from_id: 2
to_id: 1
material_id: material1
}
Material:
{
_id: material1
organization_id: 2
},
{
_id: material2
organization_id: 1
},
{
_id: material3
organization_id: 1
},
--Edit:
There are three materials, 2 belong to organization_id(1) and 1 belongs to organization_id(2). The organization_id does not match 1 in material1 (and instead belongs to material2), but in the Sharing collection, the to_id does match 1. If the match exists, I'd like to find the Material document _id which is equal to the material_id of Sharing AND find the Material documents where the organization_id is equal to 1.
I'd like to check if a field in Sharing (to_id) has a value that is equal to a field in Material (organization_id) AND check if organization_id is equal to 1. If there is a document that exists from this, do another check to find whether the _id of Material is equal to the material_id of Sharing and return all documents & the total count.
If there is no equal value, I'd like to omit that result and send the object with only organization_id equal to 1 and get the total count of this result.
Right now, I do it in a very inefficient way using .map() to find this. Below is my code:
export const getMaterials = async (req, res) => {
const sharing = await Sharing.find({to_id: 1});
let doneLoad;
try {
if (sharing && sharing.length>0) {
const sharingTotal = await Material.find( {$or: [ {organization_id: 1}, {_id: sharing.map((item) => item.material_id)} ] } ).countDocuments();
const sharingMats = await Material.find( {$or: [ {organization_id: 1}, {_id: sharing.map((item) => item.material_id)} ] } );
res.status(200).json({data: sharingMats});
doneLoad= true;
}
else if (!doneLoad) {
const materialTotal = await Material.find({organization_id: 1}).countDocuments();
const materials = await Material.find({organization_id: 1});
res.status(200).json({data: materials});
}
} catch (error) {
res.status(404).json({ message: error.message });
}
}
I have tried using aggregation to get my desired result but I cannot find any solution that fits my requirements. Any help would be great as I am quite new to using mongodb. Thanks.
Edit (desired result):
Materials: [
{
_id: material1,
organization_id: 1
},
{
_id: material2,
organization_id: 1
},
{
_id: material3,
organization_id: 1
}
]
You can use sub-pipeline in a $lookup to perform the filtering. $addFields the count using $size later.
db.Sharing.aggregate([
{
"$match": {
to_id: 1
}
},
{
"$lookup": {
"from": "Material",
"let": {
to_id: "$to_id",
material_id: "$material_id"
},
"pipeline": [
{
"$match": {
$expr: {
$or: [
{
$eq: [
"$$to_id",
"$organization_id"
]
},
{
$eq: [
"$$material_id",
"$_id"
]
}
]
}
}
},
{
"$addFields": {
"organization_id": 1
}
}
],
"as": "materialLookup"
}
},
{
"$addFields": {
"materialCount": {
$size: "$materialLookup"
}
}
}
])
Here is the Mongo playground for your reference.
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'
]
} }
])
I'm trying to analyse some data and I thought my queries would be faster ultimately by storing a relationship between my collections instead. So I wrote something to do the data normalisation, which is as follows:
var count = 0;
db.Interest.find({'PersonID':{$exists: false}, 'Data.DateOfBirth': {$ne: null}})
.toArray()
.forEach(function (x) {
if (null != x.Data.DateOfBirth) {
var peep = { 'Name': x.Data.Name, 'BirthMonth' :x.Data.DateOfBirth.Month, 'BirthYear' :x.Data.DateOfBirth.Year};
var person = db.People.findOne(peep);
if (null == person) {
peep._id = db.People.insertOne(peep).insertedId;
//print(peep._id);
}
db.Interest.updateOne({ '_id': x._id }, {$set: { 'PersonID':peep._id }})
++count;
if ((count % 1000) == 0) {
print(count + ' updated');
}
}
})
This script is just passed to mongo.exe.
Basically, I attempt to find an existing person, if they don't exist create them. In either case, link the originating record with the individual person.
However this is very slow! There's about 10 million documents and at the current rate it will take about 5 days to complete.
Can I speed this up simply? I know I can multithread it to cut it down, but have I missed something?
In order to insert new persons into People collection, use this one:
db.Interest.aggregate([
{
$project: {
Name: "$Data.Name",
BirthMonth: "$Data.DateOfBirth.Month",
BirthYear: "$Data.DateOfBirth.Year",
_id: 0
}
},
{
$merge: {
into: "People",
// requires an unique index on {Name: 1, BirthMonth: 1, BirthYear: 1}
on: ["Name", "BirthMonth", "BirthYear"]
}
}
])
For updating PersonID in Interest collection use this pipeline:
db.Interest.aggregate([
{
$lookup: {
from: "People",
let: {
name: "$Data.Name",
month: "$Data.DateOfBirth.Month",
year: "$Data.DateOfBirth.Year"
},
pipeline: [
{
$match: {
$expr: {
$and: [
{ $eq: ["$Name", "$$name"] },
{ $eq: ["$BirthMonth", "$$month"] },
{ $eq: ["$BirthYear", "$$year"] }
]
}
}
},
{ $project: { _id: 1 } }
],
as: "interests"
}
},
{
$set: {
PersonID: { $first: "$interests._id" },
interests: "$$REMOVE"
}
},
{ $merge: { into: "Interest" } }
])
Mongo Playground
I want to pull elements out of the array only if some condition is met
This is my document structure:
{
_id: "userId",
posts: [{
_id: "postId",
comments:[{
_id: "commentId",
userid: "some id of an user" // USER
},{
_id: "commentId2",
userid: "some id of an user2"
}]
}]
}
I want to delete the element from the comments array with the given commentId. This should be done only if userid is USER. If that condition isn't met, that means that comment doesn't belongs to the user that wants to delete it so I decline it.
Tried Attempt :
Post.findOneAndUpdate(
{
_id: mongoose.Types.ObjectId(userId)
},
{
$pull: {
$cond: [
{
"posts.$[post].comments.$[comment].userid": {
$eq: USER
}
},
{
$pull: {
comments: {
_id: mongoose.Types.ObjectId(commentId)
}
}
}
]
}
},
{
arrayFilters: [
{
"comment._id": mongoose.Types.ObjectId(commentId)
},
{
"post._id": mongoose.Types.ObjectId(postId)
}
]
}
)
That code above doesn't work, I'm stuck there & I don't know how to continue. maybe somebody knows how to fix this.
You can try below query :
Post.findOneAndUpdate(
{
_id: mongoose.Types.ObjectId(userId) // Fetches actual document
},
// Any matching object that has these fields/values in comments array will be pulled out
{
$pull: {"posts.$[post].comments": { _id : mongoose.Types.ObjectId(commentId), "userid": USER }}},
{
arrayFilters: [
{
"post._id": mongoose.Types.ObjectId(postId) // Checks which object inside `posts` array needs to be updated
}
]
}
)
Note : Use an option { new : true } in mongoose to return updated document, or in shell use { returnNewDocument : true }