I wrote a MongoDB query to fetch orders that were closed on a given date (matching year and month):
const orders = await OrderModel.find({
$expr: {
$and: [
{ $eq: ['$entityId', entityId] },
{ $ne: ['$closingDate', null] },
{ $eq: [{ $year: '$closingDate' }, date.getFullYear()] },
{ $eq: [{ $month: '$closingDate' }, date.getMonth() + 1] },
],
},
}).lean();
Turns out my local MongoDB version (3.6) is higher than the one on the dev environment (3.4.14), and therefore $expr isn't supported. Is there an alternative for older version I can use?
Note: I read the other thread regarding this topic, but I couldn't extract an answer from that as it covers a different use case.
Whenever you have to work with dates/times then I recommend the moment.js library. Looks like, you want to query the data from the current month. Then you could write it like this:
db.OrderModel.find({
entityId: entityId,
closingDate: {
$gte: moment().startOf('month').toDate(),
$lte: moment().endOf('month').toDate()
}
})
You don't need closingDate: {$ne: null}, it's redundant.
Related
I have a collection in mongodb with a few million documents. there is an attribute(categories) that is an array that contains all the categories that a document belongs to. I am using following query to convert the array into a comma separated string to add it to SQL server through a spoon transformation.
for example
the document has ["a","b","c",...] and i need a,b,c,.... so i can pit it in a column
categories: {
$cond: [
{ $eq: [{ $type: "$categories" }, "array"] },
{
$trim: {
input: {
$reduce: {
input: "$categories",
initialValue: "",
in: { $concat: ["$$value", ",", "$$this"] }
}
}
}
},
"$categories"
]
}
when i run the query i get the following error and i cannot figure out what the problem is.
com.mongodb.MongoQueryException: Query failed with error code 16702 and error message '$concat only supports strings, not array' on server
a few documents had this attribute as string and not array so i added a type check. but still the issue is there. any help on how to narrow down the issue will be very appreciated.
A few other attributes were the same in the same collection and this query is working fine for the rest of them.
I don't see any problem in your aggregation. It shouldn't give this error. Can you try to update your mongodb version?
However, your aggregation is not working properly reduce wasn't working . I converted it to this:
db.collection.aggregate([
{
"$project": {
categories: {
$cond: [
{
$eq: [{ $type: "$categories" }, "array"]
},
{
'$reduce': {
'input': '$categories',
'initialValue': '',
'in': {
'$concat': [
'$$value',
{ '$cond': [{ '$eq': ['$$value', ''] }, '', ', '] },
'$$this'
]
}
}
},
"$categories"
]
}
}
}
])
Edit:
So, if you have nested arrays in the categories field. We can flat our arrays with unwind stage. So if you can add these 3 stages above the $project stage. Our aggregation will work.
{
"$unwind": "$categories"
},
{
"$unwind": "$categories"
},
{
"$group": {
_id: null,
categories: {
$push: "$categories"
}
}
},
Playground
I need to check if an ObjectId exists in a non nested array and in multiple nested arrays, I've managed to get very close using the aggregation framework, but got stuck in the very last step.
My documents have this structure:
{
"_id" : ObjectId("605ce5f063b1c2eb384c2b7f"),
"name" : "Test",
"attrs" : [
ObjectId("6058e94c3994d04d28639616"),
ObjectId("6058e94c3994d04d28639627"),
ObjectId("6058e94c3994d04d28639622"),
ObjectId("6058e94c3994d04d2863962e")
],
"variations" : [
{
"varName" : "Var1",
"attrs" : [
ObjectId("6058e94c3994d04d28639616"),
ObjectId("6058e94c3994d04d28639627"),
ObjectId("6058e94c3994d04d28639622"),
ObjectId("60591791d4d41d0a6817d23f")
],
},
{
"varName" : "Var2",
"attrs" : [
ObjectId("60591791d4d41d0a6817d22a"),
ObjectId("60591791d4d41d0a6817d255"),
ObjectId("6058e94c3994d04d28639622"),
ObjectId("60591791d4d41d0a6817d23f")
],
},
],
"storeId" : "9acdq9zgke49pw85"
}
Let´s say I need to check if this if this _id exists "6058e94c3994d04d28639616" in all arrays named attrs.
My aggregation query goes like this:
db.product.aggregate([
{
$match: {
storeId,
},
},
{
$project: {
_id: 0,
attrs: 1,
'variations.attrs': 1,
},
},
{
$project: {
attrs: 1,
vars: '$variations.attrs',
},
},
{
$unwind: '$vars',
},
{
$project: {
attr: {
$concatArrays: ['$vars', '$attrs'],
},
},
},
]);
which results in this:
[
{
attr: [
6058e94c3994d04d28639616,
6058e94c3994d04d28639627,
6058e94c3994d04d28639622,
6058e94c3994d04d2863962e,
6058e94c3994d04d28639616,
6058e94c3994d04d28639627,
6058e94c3994d04d28639622,
60591791d4d41d0a6817d23f,
60591791d4d41d0a6817d22a,
60591791d4d41d0a6817d255,
6058e94c3994d04d28639622,
60591791d4d41d0a6817d23f
]
},
{
attr: [
60591791d4d41d0a6817d22a,
60591791d4d41d0a6817d255,
6058e94c3994d04d28639622,
60591791d4d41d0a6817d23f,
6058e94c3994d04d28639624,
6058e94c3994d04d28639627,
6058e94c3994d04d28639628,
6058e94c3994d04d2863963e
]
}
]
Assuming I have two products in my DB, I get this result. Each element in the outermost array is a different product.
The last bit, which is checking for this key "6058e94c3994d04d28639616", I could not find a way to do it with $group, since I dont have keys to group on.
Or with $match, adding this to the end of the aggregation:
{
$match: {
attr: "6058e94c3994d04d28639616",
},
},
But that results in an empty array. I know that $match does not query arrays like this, but could not find a way to do it with $in as well.
Is this too complicated of a Schema? I cannot have the original data embedded, since it is mutable and I would not be happy to change all products if something changed.
Will this be very expensive if I had like 10000 products?
Thanks in advance
You are trying to compare string 6058e94c3994d04d28639616 with ObjectId. Convert the string to ObjectId using $toObjectId operator when perform $match operation like this:
{
$match: {
$expr: {
$in: [{ $toObjectId: "6058e94c3994d04d28639616" }, "$attr"]
}
}
}
I am new to MongoDB and trying to execute a query. I have a company collection and company IDs array. I would like to get the results where attributes.0.ccode exist and attributes.0.ccode is not empty and will be checked within the ids provided in an array( cdata)
var query = Company.find({ _id: { $in: cdata } },{ "attributes.0.ccode": { $exists: true }, $and: [ { "attributes.0.ccode": { $ne: "" } } ] }).select({"attributes": 1}).sort({});
The error I am getting is
"$err": "Can't canonicalize query: BadValue Unsupported projection option: attributes.0.ccode: { $exists: true }",
"code": 17287
I think it's a bracketing issue but can't figure it out where.
Any help is highly appreciated.
In your code { _id: { $in: cdata } } is interpreted as query, and everything else, starting from ,{ "attributes.0.ccode": { $e.. as a Projection (which field to display). Try to refactor your code so _id: {$in ...} and the rest of the query belong to the same higher - level object. Something like this:
var query = Company.find({
_id: {
$in: cdata
},
"attributes.0.ccode": {
$exists: true
},
$and: [
{
"attributes.0.ccode": {
$ne: ""
}
}
]
}).select({"attributes": 1}).sort({});
The documents in my collection("users") look like this:
{
_id: ObjectID(...),
verifiedFields:
{
email: ["user#example.com", "othermail#example.com"],
phone: [...]
},
profiles:
[
{
_id: ObjectID(...),
fields:
{
email: { value: "user#example.com" }
}
}
]
}
I would like to now select all users who's profiles.field.email.value is contained within their verifiedFields.email. I would like to avoid having to store a boolean verified as the user should be allowed to have multiple profiles with the same fields and this would cause complications later on.
Thanks in advance!
Your query is:
db.users.find({
$expr: {$gt: [{$size: {$setIntersection: ['$profiles.fields.email.value', '$verifiedFields.email']}}, 0]}
})
This query doesn't use indexes, so on performance issue you will need add verified field.
Please, check aggregation pipeline and $expr for better understanding this query. Pipeline used for testing your query was:
db.test.aggregate([
{ $addFields: {a : '$profiles.fields.email.value'}},
{ $addFields: {b: { $setIntersection: ['$a', '$verifiedFields.email']}}},
{ $match: {$expr: {$gt: [{$size: '$b'}, 0]}}}
])
something like this should work:
collection('users').find({
'profiles[0].fields.email.value': {$in: 'verifiedFields.email'}
})
I have a Mongodb document that contains an an array that is deeply imbedded inside the document. In one of my action, I would like to return the entire document but filter out the elements of that array that don't match that criteria.
Here is some simplified data:
{
id: 123 ,
vehicles : [
{name: 'Mercedes', listed: true},
{name: 'Nissan', listed: false},
...
]
}
So, in this example I want the entire document but I want the vehicles array to only have objects that have the listed property set to true.
Solutions
Ideally, I'm looking for a solution using mongo's queries (e.g. `$unwind, $elemMatch, etc...) but I'm also using mongoose so solution that uses Mongoose is OK.
You could use aggregation framework like this:
db.test312.aggregate(
{$unwind:"$vehicles"},
{$match:{"vehicles.name":"Nissan"}},
{$group:{_id:"$_id",vehicles:{$push:"$vehicles"}}}
)
You can use $addToSet on the group after unwinding and matching by listed equals true.
Sample shell query:
db.collection.aggregate([
{
$unwind: "$vehicles"
},
{
$match: {
"vehicles.listed": {
$eq: true
}
}
},
{
$group: {
_id: "$id",
vehicles: {
"$addToSet": {
name: "$vehicles.name",
listed: "$vehicles.listed"
}
}
}
},
{
$project: {
_id: 0,
id: "$_id",
vehicles: 1
}
}
]).pretty();