I have list of subjects as follows:
[
{ "name": "Algorithms", "category": "Computer Science" },
{ "name": "Android Programming", "category": "Computer Science" },
{ "name": "Polish", "category": "Foreign Languages" },
{ "name": "Portuguese", "category": "Foreign Languages" },
{ "name": "Quechua", "category": "Foreign Languages" },
{ "name": "Health and Medicine", "category": "Science" },
{ "name": "Inorganic Chemistry", "category": "Science" }
]
I am trying to group this based on the category as follows:
[
{
"_id": "Computer Science",
"subjects": [
{
"id": "5d2dfd5e349a9a3a48e538ce",
"name": "Algorithms"
},
{
"id": "5d2dfd5e349a9a3a48e538cf",
"name": "Android Programming"
}
],
"count": 2
},
{
"_id": "Foreign Languages",
"subjects": [
{
"id": "5d2dfd5e349a9a3a48e538d0",
"name": "Polish"
},
{
"id": "5d2dfd5e349a9a3a48e538d1",
"name": "Portuguese"
},
{
"id": "5d2dfd5e349a9a3a48e538d2",
"name": "Quechua"
}
],
"count": 3
},
{
"_id": "Science",
"subjects": [
{
"id": "5d2dfd5e349a9a3a48e538d3",
"name": "Health and Medicine"
},
{
"id": "5d2dfd5e349a9a3a48e538d4",
"name": "Inorganic Chemistry"
}
],
"count": 2
}
]
I also want the categories to be sorted and subjects to be sorted in each category.
This is what I have done so far:
db.coll.aggregate(
{
$group: {
_id: "$category",
subjects: {
$push: {
id: "$_id",
name: "$name"
}
},
count: { $sum: 1 }
}
});
The above works fine in terms of grouping the subjects by categories. But I am not able to do the sorting on top of grouping. I want to sort the categories as well as the subjects in each category.
Run $sort on name before you apply $group and then run next $sort by _id after $group:
db.col.aggregate([
{ $sort: { name: 1 } },
{
$group: {
_id: "$category",
subjects: {
$push: {
id: "$_id",
name: "$name"
}
},
count: { $sum: 1 }
}
},
{ $sort: { _id: 1 } }
]);
Mongo Playground
Related
I have the following data, which describes who is going to do what work.
Basically I want to replace the "workId" and "userId" with objects that contain all the data from their respective documents and retain the "when" data.
I am starting with this data:
{
"schedule": {
"WorkId": "4e51dc1069c27c015ede4e3e",
"daily": [
{
"when": 1,
"U_W": [
{
"workId": "3a60dc1069c27c015ede1111",
"userId": "5f60c3b7f93d8e00a1cdf414"
},
{
"workId": "3a60dc1069c27c015ede1122",
"userId": "5f60c3b7f93d8e00a1cdf415"
}
]
}
]
}
}
Here is the user table
"userSchema": [
{
_id: "5f60c3b7f93d8e00a1cdf414",
Name: "Bob"
},
{
_id: "5f60c3b7f93d8e00a1cdf415",
Name: "Joe"
}
],
Here is the work table
"workSchema": [
{
_id: "3a60dc1069c27c015ede1111",
Name: "shovel"
},
{
_id: "3a60dc1069c27c015ede1122",
Name: "hammer"
}
]
what I want to end up with is this
{
"schedule": {
"WorkId": "4e51dc1069c27c015ede4e3e",
"daily": [
{
"when": 1,
"U_W": [
{
"work": {
"id": "3a60dc1069c27c015ede1111",
"name": "shovel"
},
"user": {
"id": "5f60c3b7f93d8e00a1cdf414",
"name": "bob"
}
},
{
"work": {
"id": "3a60dc1069c27c015ede1122",
"name": "hammer"
},
"user": {
"id": "5f60c3b7f93d8e00a1cdf415",
"name": "joe"
}
}
]
}
]
}
}
Here is my first attempt:
I have it joining the the two documents
How can I get rid of the duplicates ( bob:hammer and joe:shovel ) ?
and how do I include the "when" ?
Here is the playground that provides the following :
[
{
"_id": ObjectId("5a934e000102030405000000"),
"user_info": {
"Name": "Bob",
"_id": "5f60c3b7f93d8e00a1cdf414"
},
"work_role": {
"Name": "shovel",
"_id": "3a60dc1069c27c015ede1111"
}
},
{
"_id": ObjectId("5a934e000102030405000000"),
"user_info": {
"Name": "Bob",
"_id": "5f60c3b7f93d8e00a1cdf414"
},
"work_role": {
"Name": "hammer",
"_id": "3a60dc1069c27c015ede1122"
}
},
{
"_id": ObjectId("5a934e000102030405000000"),
"user_info": {
"Name": "Joe",
"_id": "5f60c3b7f93d8e00a1cdf415"
},
"work_role": {
"Name": "shovel",
"_id": "3a60dc1069c27c015ede1111"
}
},
{
"_id": ObjectId("5a934e000102030405000000"),
"user_info": {
"Name": "Joe",
"_id": "5f60c3b7f93d8e00a1cdf415"
},
"work_role": {
"Name": "hammer",
"_id": "3a60dc1069c27c015ede1122"
}
}
]
After beating my head against the wall for some time...
I found a pretty cool feature of mongo "references"
eg:
REF_work: { type: Schema.Types.ObjectId, required: true, ref: 'work' },
REF_person: { type: Schema.Types.ObjectId, required: true, ref: 'users' },
then when I call it from my get function I add a populate to the find
assignments.find(query).populate('daily.cp.REF_person').populate('daily.cp.REF_work');
I get exactly what I want:
[
{
"_id": ObjectId("5a934e000102030405000000"),
"REF_person": {
"Name": "Bob",
"_id": "5f60c3b7f93d8e00a1cdf414"
},
"REF_work": {
"Name": "shovel",
"_id": "3a60dc1069c27c015ede1111"
}
},
{
"_id": ObjectId("5a934e000102030405000000"),
"REF_person": {
"Name": "Joe",
"_id": "5f60c3b7f93d8e00a1cdf415"
},
"REF_work": {
"Name": "hammer",
"_id": "3a60dc1069c27c015ede1122"
}
}
]
I have a MongoDB schema that looks like this
const ProductModel = new Schema({
subcategory: {
type : mongoose.Schema.Types.ObjectId,
ref : "Subcategory",
},
product_name: {
type: String
},
description: {
type: String
},
price: {
type: Number
},
});
And a subcategory schema:
const SubcategoryModel = new Schema({
subcategoryName: {
type: String,
}
});
The input query before aggregation looks like this:
[
{
"_id": "111",
"subcategory": {
"_id": "456",
"categoryName": "Sneakers",
},
"product_name": "Modern sneaker",
"description": "Stylish",
"price": 4400
},
{
"_id": "222",
"subcategory": {
"_id": "456",
"categoryName": "Sneakers",
},
"product_name": "Blue shoes",
"description": "Vived colors",
"price": 7500
},
{
"_id": "333",
"subcategory": {
"_id": "123",
"categoryName": "Jackets",
"__v": 0
},
"product_name": "Modern jacket",
"description": "Stylish",
"price": 4400
},
}
]
The final result of the query should look like this:
{
"Sneakers":[
{
"product_name":"Modern sneaker",
"description":"Stylish",
"price":"4400"
},
{
"product_name":"Blue shoes",
"description":"Vived colors",
"price":"7500"
},
"Jackets":{
"...."
}
]
}
Subcategory before aggregation:
"subcategories": [
{
"_id": "123",
"categoryName": "Jackets",
},
{
"_id": "456",
"categoryName": "Sneakers",
}
]
I'm trying to populate the subcategory, And then group the products by their subcategoryName field.
You can use this aggregation query:
First $lookup to do the join between Product and Subcategory creating the array subcategories.
Then deconstructs the array using $unwind.
$group by the name of subproduct adding the entire object using $$ROOT.
The passes the fields you want using $project.
And replaceRoot to get key value into arrays as Sneakers and Jackets.
db.Product.aggregate([
{
"$lookup": {
"from": "Subcategory",
"localField": "subcategory.categoryName",
"foreignField": "categoryName",
"as": "subcategories"
}
},
{
"$unwind": "$subcategories"
},
{
"$group": {
"_id": "$subcategories.categoryName",
"data": {
"$push": "$$ROOT"
}
}
},
{
"$project": {
"data": {
"product_name": 1,
"description": 1,
"price": 1
}
}
},
{
"$replaceRoot": {
"newRoot": {
"$arrayToObject": [
[
{
"k": "$_id",
"v": "$data"
}
]
]
}
}
}
])
Example here
With your provided data, result is:
[
{
"Sneakers": [
{
"description": "Stylish",
"price": 4400,
"product_name": "Modern sneaker"
},
{
"description": "Vived colors",
"price": 7500,
"product_name": "Blue shoes"
}
]
},
{
"Jackets": [
{
"description": "Stylish",
"price": 4400,
"product_name": "Modern jacket"
}
]
}
]
I have got two collections, chapters and courses with one-to-one association,
db={
"chapters": [
{
"_id": 10,
"course_id": 1,
"author": "John"
},
{
"_id": 20,
"course_id": 2,
"author": "John"
},
{
"_id": 30,
"course_id": 3,
"author": "Timmy"
},
{
"_id": 40,
"course_id": 4,
"author": "John"
},
],
"courses": [
{
"_id": 1,
"published": true,
"name": "course 1"
},
{
"_id": 2,
"published": false,
"name": "course 2"
},
{
"_id": 3,
"published": true,
"name": "course 3"
},
{
"_id": 4,
"published": true,
"name": "course 4"
}
]
}
How do I query all chapters with the published course (published=true) and the author is "John"?
You can use $match, $lookup then $group by author then simply $filter it based on published
db.chapters.aggregate([
{
$match: {
author: "John"
}
},
{
"$lookup": {
"from": "courses",
"localField": "course_id",
"foreignField": "_id",
"as": "course"
}
},
{
$project: {
_id: 1,
course: {
$first: "$course"
},
author: 1
}
},
{
$group: {
_id: "$author",
courseChapters: {
$push: "$$ROOT"
}
}
},
{
$project: {
courseChapters: {
$filter: {
input: "$courseChapters",
as: "cc",
cond: {
$eq: [
"$$cc.course.published",
true
]
}
}
}
}
}
])
Output
[
{
"_id": "John",
"courseChapters": [
{
"_id": 10,
"author": "John",
"course": {
"_id": 1,
"name": "course 1",
"published": true
}
},
{
"_id": 40,
"author": "John",
"course": {
"_id": 4,
"name": "course 4",
"published": true
}
}
]
}
]
Mongoplayground: https://mongoplayground.net/p/x-XghXzZUk4
I have Json which have values like state_city details this contains information like which city belongs to which state -
Need to query it for particular state name which will gives me all cities that belongs to that state.
db.collection.find({
"count": 10,
"state.name": "MP"
})
[
{
"collection": "collection1",
"count": 10,
"state": [
{
"name": "MH",
"city": "Mumbai"
},
{
"name": "MH",
"city": "Pune"
},
{
"name": "UP",
"city": "Kanpur"
},
{
"name": "CG",
"city": "Raipur"
}
]
},
{
"collection": "collection2",
"count": 20,
"state": [
{
"name": "MP",
"city": "Indore"
},
{
"name": "MH",
"city": "Bhopal"
},
{
"name": "UP",
"city": "Kanpur"
},
{
"name": "CG",
"city": "Raipur"
}
]
}
]
You have to use aggregate query to get only matching elements in array :
db.collection.aggregate([{
$unwind: "$content.state"
},
{
$match: {
"content.state.name": "MH",
"count": 10
}
},
{
$group: {
_id: "$content.state.city",
}
},
{
$addFields: {
key: 1
}
},
{
$group: {
_id: "$key",
cities: {
$push: "$_id"
}
}
},
{
$project: {
_id: 0,
cities: 1
}
}
])
This query will return :
{
"cities": [
"Pune",
"Mumbai"
]
}
The following query would be the solution.
db.collection.find({ "count": 10, "state":{"name": "MP"}})
For more complex queries, $elemMatch is also available.
I have a dataset in MongoDB that looks like this:
{ "name": "Tom's", "category": "coffee shop" },
{ "name": "Red Lobster", "category": "restaurant" },
{ "name": "Tom's", "category": "coffee shop" },
{ "name": "Starbucks", "category": "coffee shop" },
{ "name": "Central Park", "category": "park" },
{ "name": "Office", "category": "office" },
{ "name": "Red Lobster", "category": "restaurant" },
{ "name": "Home", "category": "home" },
{ ... } // and so on
How can I find the most common value for specific categories? For example, the most common occurring value for coffee shop and restaurant should be Tom's and Red Lobster, respectively.
My current $aggregate query only seems to list the most common occurring value among ALL of the dataset:
db.collection.aggregate(
{ "$group": { "_id": { "name": "$name" }, "count": { "$sum":1 } }},
{ "$group": { "_id": "$_id.name", "count": { "$sum": "$count" } }},
{ "$sort": { "count":-1 }}
)
You can try the below query.
$group on category and name to get the count for each category and name combination.
$sort the input documents by category and count desc.
$group on category with $first to pick the document with most occurrences.
db.collection_name.aggregate([
{
"$group": {
"_id": {
"category": "$category",
"name": "$name"
},
"count": {
"$sum": 1
}
}
},
{
"$sort": {
"_id.category": 1,
"count": -1
}
},
{
"$group": {
"_id": {
"category": "$_id.category"
},
"name": {
"$first": "$_id.name"
},
"count": {
"$first": "$count"
}
}
}
])