Back
Featured image of post MongoDB join multiple collections with $lookup
NODEJS MONGODB

MongoDB join multiple collections with $lookup

In this article, we will be using 'Expenses Recorder' to demonstrate how to use $lookup operator in MongoDB aggregation to combine the data in nested collections

We will first introduce the structure and relationships between each collections, then we will be going through how to use $lookup in mongodb aggregation to get our desired output

Documents in User Collection

/* 1 */
{ 
    "_id" : ObjectId("6173e5fe7fc8622cbc56a108"),
    "name" : "Jeff",
    "age" : 20,
    "ref_id" : "457935c0-33ed-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 2 */
{
    "_id" : ObjectId("6173e6067fc8622cbc56a10a"),
    "name" : "Jason",
    "age" : 25,
    "ref_id" : "4a4bcc70-33ed-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

Documents in Expenses Category Collection

/* 1 */
{
    "_id" : ObjectId("6173e6577fc8622cbc56a10c"),
    "label" : "Food",
    "user_ref_id" : "457935c0-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "7a27b0d0-33ed-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 2 */
{
    "_id" : ObjectId("6173e6677fc8622cbc56a10e"),
    "label" : "Entertainment",
    "user_ref_id" : "457935c0-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "84021f00-33ed-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 3 */
{
    "_id" : ObjectId("6173e69d7fc8622cbc56a112"),
    "label" : "Transportation",
    "user_ref_id" : "4a4bcc70-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "a3e28580-33ed-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 4 */
{
    "_id" : ObjectId("6173e6d07fc8622cbc56a114"),
    "label" : "Monthly Installment",
    "user_ref_id" : "4a4bcc70-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "c2a40e80-33ed-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

Documents in Expenses Collection

/* 1 */
{
    "_id" : ObjectId("6173e7677fc8622cbc56a116"),
    "label" : "Mc Donald",
    "value" : 11.5,
    "expenses_category_ref_id" : "7a27b0d0-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "1cacea50-33ee-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 2 */
{
    "_id" : ObjectId("6173e7767fc8622cbc56a118"),
    "label" : "KFC",
    "value" : 15,
    "expenses_category_ref_id" : "7a27b0d0-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "25358420-33ee-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 3 */
{
    "_id" : ObjectId("6173e78a7fc8622cbc56a11a"),
    "label" : "Sushi King",
    "value" : 35,
    "expenses_category_ref_id" : "7a27b0d0-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "312787b0-33ee-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 4 */
{
    "_id" : ObjectId("6173e7e07fc8622cbc56a11c"),
    "label" : "karaoke",
    "value" : 45,
    "expenses_category_ref_id" : "84021f00-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "649c2330-33ee-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 5 */
{
    "_id" : ObjectId("6173e7f87fc8622cbc56a11e"),
    "label" : "Petrol Fee",
    "value" : 65,
    "expenses_category_ref_id" : "a3e28580-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "72f1b940-33ee-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 6 */
{
    "_id" : ObjectId("6173e8047fc8622cbc56a120"),
    "label" : "Car Maintenance Service",
    "value" : 150,
    "expenses_category_ref_id" : "a3e28580-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "7a206860-33ee-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 7 */
{
    "_id" : ObjectId("6173e8147fc8622cbc56a122"),
    "label" : "House Loan",
    "value" : 1500,
    "expenses_category_ref_id" : "c2a40e80-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "83b31f30-33ee-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

/* 8 */
{
    "_id" : ObjectId("6173e8237fc8622cbc56a124"),
    "label" : "Insurance",
    "value" : 230,
    "expenses_category_ref_id" : "c2a40e80-33ed-11ec-aac1-dd97bcc28a8a",
    "ref_id" : "8cc22710-33ee-11ec-aac1-dd97bcc28a8a",
    "__v" : 0
}

Relationship between each Collections

collections relationship

As we can observe the diagram above, collection Expenses Category is actually having child-to-parent relationship where it stored the user-ref-id field which is equivalent to ref-id in User collection.

Moving on, we also have collection Expenses which also having the child-to-parent relationship where it stored the expenses-category-ref-id field which is equivalent to ref-id in Expenses Category collection.


Aggregation $lookup

Controller below is belongs to the route http://localhost:3000/user/:id where the parameter id is the ref_id of the User

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48

//Import your Models here
const User = require('../../models/User')
const ExpensesCategory = require('../../models/ExpensesCategory')
const Expenses = require('../../models/Expenses')

exports.getUser = async (req, res) => {
    try {
        const userId = req.params.id
        const result = await User.aggregate([
            {
                $match: {
                    "ref_id": userId
                }
            },
            {
                $lookup: {
                    from: "expenses-category",
                    let: { "userRefId": "$ref_id" },
                    pipeline: [
                        {
                            $match: {
                                $expr: { $eq: ["$user_ref_id", "$$userRefId"] }
                            }
                        },
                        {
                            $lookup: {
                                from: "expenses",
                                let: { "categoryRefId": "$ref_id" },
                                pipeline: [
                                    {
                                        $match: {
                                            $expr: { $eq: ["$expenses_category_ref_id", "$$categoryRefId"] }
                                        }
                                    },
                                ],
                                as: "expenses"
                            },
                        },
                    ],
                    as: "expenses_categories"
                }
            },
        ])
        res.json(result[0] || {})
    } catch (error) {        
        res.json({error: error.message})
    }
}

Result

This case, we are using the 457935c0-33ed-11ec-aac1-dd97bcc28a8a ref_id from the user called Jeff to pass as the route parameter.
The expected result will be => [response.json]

Toggle the output response to show / hide here

Explanations

  1. Import all the necessary Models such as User, Expenses Category and Expenses
  2. Get and access the route parameter :id which is equivalent to the User ref_id
  3. Apply aggregation method from the User collection
  4. [Code Line 10 ~ 14]
    • Find the relavant document by using $match operator and comparing the route param :id with ref_id from User collection
    • This process is equivalent to User.findOne({ref_id: req.param.id})
  5. $lookup syntax
    • from: < the target collection you want to join >
    • let: < declare custom variable from your current Model. “In this case it’s referring User collection” >
    • pipeline < Compare and query the condition to get desired output >
    • as < specific the field name of the array output >
  6. [Code Line 15 ~ 24]
    • First, we apply $lookup operator to join the expenses-category
    • Since, expenses-category model actually storing user_ref_id. We can then declare the variable called userRefId which is referring to the User ref_id and compare them later on
    • In order to use the custom variable we have declared earlier, we need to use the operator called $expr
    • use $match operator to compare and filter out the result based on userRefId variable with the user_ref_id from expenses-category collection under pipeline operation
    • specific the query array output field name called expenses-categories in Line 40
  7. [Code Line 25 ~ 38]
    • Since expenses collection is nested inside expenses-category collection and expenses-category collection is nested inside user collection. We then now need to $lookup one more round from expenses collection to expenses-category collection before we moved out the operation
    • Apply $lookup operator to join the expenses collection
    • Since, expenses model actually storing expenses_category_ref_id. We can then declare the variable known as categoryRefId which is referring to the Expenses Category ref_id and compare them later on
    • use $match operator to compare and filter out the result based on categoryRefId variable with the expenses_category_ref_id from expenses collection under pipeline operation
    • specific the query array output field name called expenses
  8. As now we know the ref_id is actually unique key in every documents while output data type from aggregation is Array. So we can just return the first element of the array or return empty object if the ref_id doesn’t existed.

Clean up Response Output by using $project

If you have seen the output response from the query above response.json. You may realize there are actually some unecessary fields we can skip or remove from our query.

Let’s see how we could handle it by using $project operator. 

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70

//Import your Models here
const User = require('../../models/User')
const ExpensesCategory = require('../../models/ExpensesCategory')
const Expenses = require('../../models/Expenses')

exports.getUser = async (req, res) => {
    try {
        const userId = req.params.id
        const result = await User.aggregate([
            {
                $match: {
                    "ref_id": userId
                }
            },
            {
                $lookup: {
                    from: "expenses-category",
                    let: { "userRefId": "$ref_id" },
                    pipeline: [
                        {
                            $match: {
                                $expr: { $eq: ["$user_ref_id", "$$userRefId"] }
                            }
                        },
                        {
                            $lookup: {
                                from: "expenses",
                                let: { "categoryRefId": "$ref_id" },
                                pipeline: [
                                    {
                                        $match: {
                                            $expr: { $eq: ["$expenses_category_ref_id", "$$categoryRefId"] }
                                        }
                                    },
                                    {
                                        $project: {
                                            _id: 0,
                                            ref_id: 1,
                                            label: 1,
                                            value: 1
                                        }
                                    }
                                ],
                                as: "expenses"
                            },
                        },
                        {
                            $project: {
                                _id: 0,
                                __v: 0,
                                user_ref_id: 0
                            }
                        }
                    ],
                    as: "expenses_categories"
                }
            },
            {
                $project: {
                    _id: 0,
                    __v: 0
                }
            }
        ])

        res.json(result[0] || {})
    } catch (error) {
        res.json({ error: error.message })
    }
}

Result

The expected result will be => [filtered_response.json]

Or you can Toggle the output response to show / hide here

Explanations

  1. The output response is much cleaner after we used $project operator so remove and clean up the fields
  2. 0 is equals to hide while 1 is equals to show
  3. [Code Line 35 ~ 42] Expenses Collection
    • Please take note that the _id field will be always show by default. Therefore, we can always assign 0 to hide this particular field.
    • Then we can assign 1 to only show the necessary fields such as ref_id, label and value
  4. The same concept applies to Expenses Category Collection in [Code Line 47 ~ 52] and User Collection in [Code Line 58 ~ 63]
comments powered by Disqus
© 2024 Jeff's Blog