In an atomic update operation, I would like to (re)calculate a field in a document based on the updated values of other fields in the same document.
Example:
Documents have this structure:
{ _id: xxx, nrValues: 4, sumOfValues: 20, meanValue: 5 }
{ _id: yyy, nrValues: 3, sumOfValues: 12, meanValue: 4 }
The (indexed) meanValue field is needed for fast sort/find operations.
Now I would like to "add" new values to documents like in this pseudocode:
Documents.update( { _id: xxx },
{ $inc: { nrValues: 1, sumOfValues: newValue },
$set: { meanValue: sumOfValues / nrValues } } );
Is there a way to find real code for this pseudocode?
BTW: I know that I could use map/reduce/aggregation to sort/find the documents this way without having an actual meanValue field at all, but I do want this actual field in the document and in my (Meteor based) situation I cannot use map/reduce/aggregation.
Related
This has been extensively covered here, but none of the solutions seems to be working for me. I'm attempting to remove an object from an array using that object's id. Currently, my Schema is:
const scheduleSchema = new Schema({
//unrelated
_id: ObjectId
shifts: [
{
_id: Types.ObjectId,
name: String,
shift_start: Date,
shift_end: Date,
},
],
});
I've tried almost every variation of something like this:
.findOneAndUpdate(
{ _id: req.params.id },
{
$pull: {
shifts: { _id: new Types.ObjectId(req.params.id) },
},
}
);
Database:
Database Format
Within these variations, the usual response I've gotten has been either an empty array or null.
I was able slightly find a way around this and accomplish the deletion by utilizing the main _id of the Schema (instead of the nested one:
.findOneAndUpdate(
{ _id: <main _id> },
{ $pull: { shifts: { _id: new Types.ObjectId(<nested _id>) } } },
{ new: true }
);
But I was hoping to figure out a way to do this by just using the nested _id. Any suggestions?
The problem you are having currently is you are using the same _id.
Using mongo, update method allows three objects: query, update and options.
query object is the object into collection which will be updated.
update is the action to do into the object (add, change value...).
options different options to add.
Then, assuming you have this collection:
[
{
"_id": 1,
"shifts": [
{
"_id": 2
},
{
"_id": 3
}
]
}
]
If you try to look for a document which _id is 2, obviously response will be empty (example).
Then, if none document has been found, none document will be updated.
What happens if we look for a document using shifts._id:2?
This tells mongo "search a document where shifts field has an object with _id equals to 2". This query works ok (example) but be careful, this returns the WHOLE document, not only the array which match the _id.
This not return:
[
{
"_id": 1,
"shifts": [
{
"_id": 2
}
]
}
]
Using this query mongo returns the ENTIRE document where exists a field called shifts that contains an object with an _id with value 2. This also include the whole array.
So, with tat, you know why find object works. Now adding this to an update query you can create the query:
This one to remove all shifts._id which are equal to 2.
db.collection.update({
"shifts._id": 2
},
{
$pull: {
shifts: {
_id: 2
}
}
})
Example
Or this one to remove shifts._id if parent _id is equal to 1
db.collection.update({
"_id": 1
},
{
$pull: {
shifts: {
_id: 2
}
}
})
Example
For example, I want to update half of data whose _id is an odd number. such as:
db.col.updateMany({"$where": "this._id is an odd number"})
Instead of integer, _id is mongo's ObejectId which be regard as hexadecimal "string". It is not supported to code as:
db.col.updateMany(
{"$where": "this._id % 2 = 1"},
{"$set": {"a": 1}}
)
so, what is the correct format?
And what if molding according to _id？
This operation can also be done using two database calls.
Get List of _id from collection.
Push only ODD _id into an array.
Update the collection.
Updating the collection:
db.collection.update(
{ _id: { $in: ['id1', 'id2', 'id3'] } }, // Array with odd _id
{ $set: { urkey : urValue } }
)
Say that I have a document:
{ _id: 1, item: "ABC", supplier: "XYZ", price: 10, available: 23 }
and then I run something like
db.products.update(
{ _id: 1, supplier: "XYZ" },
{ stock_value: {$mul: ["price", "available", 0.8] }}
)
to get a document
{ _id: 1, item: "ABC", supplier: "XYZ", price: 10, available: 23, stock_value: 184 }
I'd like to do this without loading everything into the client. And I need to be able to specify a different constant (e.g. the 0.8) for each supplier.
I'm thinking I should just use an aggregation with an $out to the same collection, to overwrite the whole then when the update is done, but I can't do a different aggregate() call for each supplier since I'm overwriting the collection - all other suppliers will be skipped. Is there some sort of "in place" aggregation? or a way to append $out ?
I have two models, one is user
userSchema = new Schema({
userID: String,
age: Number
});
and the other is the score recorded several times everyday for all users
ScoreSchema = new Schema({
userID: {type: String, ref: 'User'},
score: Number,
created_date = Date,
....
})
I would like to do some query/calculation on the score for some users meeting specific requirement, say I would like to calculate the average of score for all users greater than 20 day by day.
My thought is that firstly do the populate on Scores to populate user's ages and then do the aggregate after that.
Something like
Score.
populate('userID','age').
aggregate([
{$match: {'userID.age': {$gt: 20}}},
{$group: ...},
{$group: ...}
], function(err, data){});
Is it Ok to use populate before aggregate? Or I first find all the userID meeting the requirement and save them in a array and then use $in to match the score document?
No you cannot call .populate() before .aggregate(), and there is a very good reason why you cannot. But there are different approaches you can take.
The .populate() method works "client side" where the underlying code actually performs additional queries ( or more accurately an $in query ) to "lookup" the specified element(s) from the referenced collection.
In contrast .aggregate() is a "server side" operation, so you basically cannot manipulate content "client side", and then have that data available to the aggregation pipeline stages later. It all needs to be present in the collection you are operating on.
A better approach here is available with MongoDB 3.2 and later, via the $lookup aggregation pipeline operation. Also probably best to handle from the User collection in this case in order to narrow down the selection:
User.aggregate(
[
// Filter first
{ "$match": {
"age": { "$gt": 20 }
}},
// Then join
{ "$lookup": {
"from": "scores",
"localField": "userID",
"foriegnField": "userID",
"as": "score"
}},
// More stages
],
function(err,results) {
}
)
This is basically going to include a new field "score" within the User object as an "array" of items that matched on "lookup" to the other collection:
{
"userID": "abc",
"age": 21,
"score": [{
"userID": "abc",
"score": 42,
// other fields
}]
}
The result is always an array, as the general expected usage is a "left join" of a possible "one to many" relationship. If no result is matched then it is just an empty array.
To use the content, just work with an array in any way. For instance, you can use the $arrayElemAt operator in order to just get the single first element of the array in any future operations. And then you can just use the content like any normal embedded field:
{ "$project": {
"userID": 1,
"age": 1,
"score": { "$arrayElemAt": [ "$score", 0 ] }
}}
If you don't have MongoDB 3.2 available, then your other option to process a query limited by the relations of another collection is to first get the results from that collection and then use $in to filter on the second:
// Match the user collection
User.find({ "age": { "$gt": 20 } },function(err,users) {
// Get id list
userList = users.map(function(user) {
return user.userID;
});
Score.aggregate(
[
// use the id list to select items
{ "$match": {
"userId": { "$in": userList }
}},
// more stages
],
function(err,results) {
}
);
});
So by getting the list of valid users from the other collection to the client and then feeding that to the other collection in a query is the onyl way to get this to happen in earlier releases.
Suppose, I have the following database:
{
_id: 1,
name: 'Alice',
courses: [
{
_id: 'DB103',
credits: 6
},
{
_id: 'ML203',
credits: 4
}
]
},
{
_id: 2,
name: 'Bob',
courses: []
}
I now want to 'upsert' the document with the course id 'DB103' in both documents. Although the _id field should remain the same, the credits field value should change (i.e. to 4). In the first document, the respective field should be changed, in the second one, {_id: 'DB103', credits: 4} should be inserted into the courses array.
Is there any possibility in MongoDB to handle both cases?
Sure, I could search with $elemMatch in courses for 'DB103' and if I haven't found it, insert, otherwise update the value. But these are two steps and I would like to do both in just one.