Let's suppose a collection has N documents and each document has an array field with M subdocuments. For a query that uses a $elemMatch on the field with the M subdocuments to filter and findMany documents of this collection, would…
I want to use a pipeline to update a document by filtering on the keys of sub-documents in an object. eg data: { things: { a1: {}, ... x1: {} } } Where "things" can contain variable keys/properties. I know…
I have a document which has a field as Array of References and it is refering to the same document. I want to populate all the nested fields. The Data will be Acyclic (person -> children -> children ≠ person).…
I've been having trouble trying to query for a deeply nested subdocument while using Mongoose. My DB structure is like this: { "_id": "662aa6ccae109745e30dc664", "username": "username", "email": "[email protected]", "lists": [ { "_id": "662aa6dbae109745e30dc66a" "name": "list", "content": [ { "_id": "662aa6eeae109745e30dc670"…
for example while performing aggregation the last(previous) stage gave me this documents { _id : ObjectId('662a416201ca2363543b6644'), name : 'location-1', startsFrom : 2, endsOn : 5, } { _id : ObjectId('662a416201ca2363543b6644'), name : 'location-1', startsFrom : 1, endsOn : 3, }…
I really don't understand how to improve the performance of my query using index. db.Vendite.aggregate([{$group: { _id: { anno: "$anno", mese: "$mese", cod_age: "$cod_age", cod_int: "$cod_int", cod_cli: "$cod_cli", cod_linea_comm: "$cod_linea_comm", cod_sett_comm: "$cod_sett_comm", _art: "$cod_art"}, vendite_quantita: { $sum: { $add: […
I have this Mongo document { _id: ObjectId('6616851ed50d6d1451fa8176'), phone: "+7(926)458-54-52", name: "Aboba" } I want to find that document if user inputs 7926, but also my filter is filtering another field as well. I am filtering with regex phone or…
I'm trying to retrieve one specific object from an existing array inside the DB document, using wildcards $near and $geometry. I have a model that looks like this: const schema = new mongoose.Schema({ name: {...}, email: {...}, ... locations: […
Here I just need to look up three tables first need to get all subjects from the subject table according to classid and boardid then from the content table we need to get all topic and content details and group…
I have this document structure: { "name": "ab", "grades": [ { "grade": "A", "score": 1 }, { "grade": "A", "score": 12 }, { "grade": "A", "score": 7 } ], "borough": "Manhattan2" } Assignment is to write a query to find…