The coursesMarks property is present in every object. So I want to push the value inside coursesMarks property, to an array and return the array to the user.
[
{
"coursesMarks": {
"_id": "634a9be567a1f07be02f71d8",
"courseCode": "cse1201",
"courseTitle": "SP"
}
},
{
"coursesMarks": {
"_id": "634a9be567a1f07be02f71db",
"courseCode": "cse1203",
"courseTitle": "DS"
}
}
]
Then expected output is:
[
{
"courses":
{
"_id": "634a9be567a1f07be02f71d8",
"courseCode": "cse1201",
"courseTitle": "SP"
},
{
"_id": "634a9be567a1f07be02f71db",
"courseCode": "cse1203",
"courseTitle": "DS"
}
}
]
I've asked a clarifying question in the comments. But if we assume that the sample data provided is a single document where the array is stored in a field named arr, then a pipeline similar to the following may be what you are looking for:
[
{
$addFields: {
courses: {
$map: {
input: "$arr",
in: "$$this.coursesMarks"
}
}
}
},
{
$unset: "arr"
}
]
Playground example here
Edit
Based on the additional information about the structure of the data, you are looking to $group things in this particular case. Therefore the relevant addition to your pipeline should look something like this:
[
...
{
$group: {
_id: null,
courses: {
$push: "$coursesMarks"
}
}
},
{
$unset: "_id"
}
]
Playground demonstration here. It includes an empty $match stage at the beginning to represent whatever additional matching logic you currently have.
Related
I've been trying to modify a value in multiple arrays for a few arrays and I can't find documentation on how to do this.
My collection looks like this
"rates": [
{
"category": "Web",
"seniorityRates": [
{
"seniority": "junior",
"rate": 100
},
{
"seniority": "intermediate",
"rate": 135
},
{
"seniority": "senior",
"rate": 165
}
]
}
]
I'm just trying to modify "junior" to "beginner", this should be simple.
Thanks to these answers:
How can I update a multi level nested array in MongoDB?
MongoDB updating fields in nested array
I've manage to write that python code (pymongo), but it doesn't works...
result = my_coll.update_many({},
{
"$set":
{
"rates.$[].seniorityRates.$[j].seniority" : new
}
},
upsert=False,
array_filters= [
{
"j.seniority": old
}
]
)
The path 'rates' must exist in the document in order to apply array updates.
It correspond to this command that doesn't work either
db.projects.updateMany({},
{
$set:
{
"rates.$[].seniorityRates.$[j].seniority" : "debutant"
}
},
{ arrayFilters = [
{
"j.seniority": "junior"
}
]
}
)
clone(t={}){const r=t.loc||{};return e({loc:new Position("line"in r?r.line:this.loc.line,"column"in r?r.column:......)} could not be cloned
What am I doing wrong ?
Any help would be very appreciated
The other option could be Sample
db.collection.update({},
{
$set: {
"rates.$[].seniorityRates.$[j].seniority": "debutant"
}
},
{
arrayFilters: [
{
"j.rate": { //As per your data, you can apply the condition o rate field to modify the level
$lte: 100
}
}
]
})
Or
The actual query should work Sample
db.collection.update({},
{
$set: {
"rates.$[].seniorityRates.$[j].seniority": "debutant"
}
},
{
arrayFilters: [
{
"j.seniority": "junior"
}
]
})
The same should work in python, a sample question
So I was just dumb here, I inverted two parameters so I didn't have the correct collection in the python code...
Thanks Gibbs for pointing out where the mistake was in the mongo command.
I will not delete this post as it can help other to know how to do this kind of queries.
this is my schema:
new Schema({
code: { type: String },
toy_array: [
{
date:{
type:Date(),
default: new Date()
}
toy:{ type:String }
]
}
this is my db:
{
"code": "Toystore A",
"toy_array": [
{
_id:"xxxxx", // automatic
"toy": "buzz"
},
{
_id:"xxxxx", // automatic
"toy": "pope"
}
]
},
{
"code": "Toystore B",
"toy_array": [
{
_id:"xxxxx", // automatic
"toy": "jessie"
}
]
}
I am trying to update an object. In this case I want to update the document with code: 'ToystoreA' and add an array of subdocuments to the array named toy_array if the toys does not exists in the array.
for example if I try to do this:
db.mydb.findOneAndUpdate({
code: 'ToystoreA,
/*toy_array: {
$not: {
$elemMatch: {
toy: [{"toy":'woddy'},{"toy":"buzz"}],
},
},
},*/
},
{
$addToSet: {
toy_array: {
$each: [{"toy":'woddy'},{"toy":"buzz"}],
},
},
},
{
new: false,
}
})
they are added and is what I want to avoid.
how can I do it?
[
{
"code": "Toystore A",
"toy_array": [
{
"toy": "buzz"
},
{
"toy": "pope"
}
]
},
{
"code": "Toystore B",
"toy_array": [
{
"toy": "jessie"
}
]
}
]
In this example [{"toy":'woddy'},{"toy":"buzz"}] it should only be added 'woddy' because 'buzz' is already in the array.
Note:when I insert a new toy an insertion date is also inserted, in addition to an _id (it is normal for me).
As you're using $addToSet on an object it's failing for your use case for a reason :
Let's say if your document look like this :
{
_id: 123, // automatically generated
"toy": "buzz"
},
{
_id: 456, // automatically generated
"toy": "pope"
}
and input is :
[{_id: 789, "toy":'woddy'},{_id: 098, "toy":"buzz"}]
Here while comparing two objects {_id: 098, "toy":"buzz"} & {_id: 123, "toy":"buzz"} - $addToSet consider these are different and you can't use $addToSet on a field (toy) in an object. So try below query on MongoDB version >= 4.2.
Query :
db.collection.updateOne({"_id" : "Toystore A"},[{
$addFields: {
toy_array: {
$reduce: {
input: inputArrayOfObjects,
initialValue: "$toy_array", // taking existing `toy_array` as initial value
in: {
$cond: [
{ $in: [ "$$this.toy", "$toy_array.toy" ] }, // check if each new toy exists in existing arrays of toys
"$$value", // If yes, just return accumulator array
{ $concatArrays: [ [ "$$this" ], "$$value" ] } // If No, push new toy object into accumulator
]
}
}
}
}
}])
Test : aggregation pipeline test url : mongoplayground
Ref : $reduce
Note :
You don't need to mention { new: false } as .findOneAndUpdate() return old doc by default, if you need new one then you've to do { new: true }. Also if anyone can get rid of _id's from schema of array objects then you can just use $addToSet as OP was doing earlier (Assume if _id is only unique field), check this stop-mongoose-from-creating-id-property-for-sub-document-array-items.
I've nested JSON like this. I want to retrieve the value of "_value" in second level. i,e. "Living Organisms" This is my JSON document.
{
"name": "Biology Book",
"data": {
"toc": {
"_version": "1",
"ge": [
{
"_name": "The Fundamental Unit of Life",
"_id": "5a",
"ge": [
{
"_value": "Living Organisms",
"_id": "5b"
}
]
}
]
}
}
}
This is what I've tried, using the "_id", I want to retrieve it's "_value"
db.products.aggregate([{"$match":{ "data.toc.ge.ge._id": "5b"}}])
This is the closest I could get to the output you mentioned in the comment above. Hope it helps.
db.collection.aggregate([
{
$match: {
"data.toc.ge.ge._id": "5b"
}
},
{
$unwind: "$data.toc.ge"
},
{
$unwind: "$data.toc.ge.ge"
},
{
$group: {
_id: null,
book: {
$push: "$data.toc.ge.ge._value"
}
}
},
{
$project: {
_id: 0,
first: {
$arrayElemAt: [
"$book",
0
]
},
}
}
])
Output:
[
{
"first": "Living Organisms"
}
]
You can check what I tried here
If you are using Mongoid:
(1..6).inject(Model.where('data.toc.ge.ge._id' => '5b').pluck('data.toc.ge.ge._value').first) { |v| v.values.first rescue v.first rescue v }
# => "Living Organisms"
6 is the number of containers to trim from the output (4 hashes and 2 arrays).
If I understand your question correctly, you only care about _value, so it sounds like you might want to use a projection:
db.products.aggregate([{"$match":{ "data.toc.ge.ge._id": "5b"}}, { "$project": {"data.toc.ge.ge._value": 1}}])
I've a problem with a huge MongoDb aggregation pipeline. I've many constraint and I've simplified the problem a lot. Hence, don't discuss the goal for this query.
I've a mongo aggregation that gives something similar to this:
[
{
"content": {
"processes": [
{
"id": "101a",
"title": "delivery"
},
{
"id": "101b",
"title": "feedback"
}
]
}
}
]
To this intermediate result I'm forced to apply a project operation in order to obtain something similar to this:
[
{
"results":
{
"titles": [
{
"id": "101a",
"value": "delivery"
},
{
"id": "101b",
"value": "feedback"
}
]
}
}
]
enter code here
But applying this projections:
"results.titles.id": "$content.processes.id",
"results.titles.value": "$content.processes.title"
I obtain this:
[
{
"results":
{
"titles": {
"id": ["101a", "101b"]
"value": ["delivery", "feedback"]
}
}
}
}
]
Collection are created but not in the proper position.
Is it possible to exploit some operator inside the project operation in order to tell mongo to create an array in a parent position?
Something like this:
"results.titles.$[x].value" : "$content.processes.value"
You can use the dot notation to project entire array:
db.col.aggregate([
{
$project: {
"results.titles": "$content.processes"
}
}
])
and if you need to rename title to value then you have to apply $map operator:
db.col.aggregate([
{
$project: {
"results.titles": {
$map: {
input: "$content.processes",
as: "process",
in: {
id: "$$process.id",
value: "$$process.title"
}
}
}
}
}
])
I am attempting to do a mongodb regex query on a field. I'd like the query to prioritize a full match if it finds one and then partials afterwards.
For instance if I have a database full of the following entries.
{
"username": "patrick"
},
{
"username": "robert"
},
{
"username": "patrice"
},
{
"username": "pat"
},
{
"username": "patter"
},
{
"username": "john_patrick"
}
And I query for the username 'pat' I'd like to get back the results with the direct match first, followed by the partials. So the results would be ordered ['pat', 'patrick', 'patrice', 'patter', 'john_patrick'].
Is it possible to do this with a mongo query alone? If so could someone point me towards a resource detailing how to accomplish it?
Here is the query that I am attempting to use to perform this.
db.accounts.aggregate({ $match :
{
$or : [
{ "usernameLowercase" : "pat" },
{ "usernameLowercase" : { $regex : "pat" } }
]
} })
Given your precise example, this could be accomplished in the following way - if your real world scenario is a little bit more complex you may hit problems, though:
db.accounts.aggregate([{
$match: {
"username": /pat/i // find all documents that somehow match "pat" in a case-insensitive fashion
}
}, {
$addFields: {
"exact": {
$eq: [ "$username", "pat" ] // add a field that indicates if a document matches exactly
},
"startswith": {
$eq: [ { $substr: [ "$username", 0, 3 ] }, "pat" ] // add a field that indicates if a document matches at the start
}
}
}, {
$sort: {
"exact": -1, // sort by our primary temporary field
"startswith": -1 // sort by our seconday temporary
}
}, {
$project: {
"exact": 0, // get rid of the "exact" field,
"startswith": 0 // same for "startswith"
}
}])
Another way would be using $facet which may prove a bit more powerful by enabling more complex scenarios but slower (several people here will hate me, though, for this proposal):
db.accounts.aggregate([{
$facet: { // run two pipelines against all documents
"exact": [{ // this one will capture all exact matches
$match: {
"username": "pat"
}
}],
"others": [{ // this one will capture all others
$match: {
"username": { $ne: "pat", $regex: /pat/i }
}
}]
}
}, {
$project: {
"result": { // merge the two arrays
$concatArrays: [ "$exact", "$others" ]
}
}
}, {
$unwind: "$result" // flatten the resulting array into separate documents
}, {
$replaceRoot: { // restore the original document structure
"newRoot": "$result"
}
}])