MongoDB Aggregation Pipelines
Hi, aliens! I am Pavan. So in this repository, I will explain all the aggregation stages in depth with basic examples. I will also include links to resources for further learning.
So this repository contains JSON files for various MongoDB aggregation pipelines. These pipelines demonstrate how to use different aggregation stages and operations to process and analyze data.
Table of Contents
- Introduction
- CRUD Operations
-
Aggregation Stages
- $match
- $group
- $project
- $sort
- $limit
- $skip
- $lookup
- $unwind
- $addFields
- $replaceRoot
-
Aggregation Operations
- $sum
- $avg
- $min
- $max
- $first
- $last
- Example Datasets
- Resources for Further Learning
Introduction
Aggregation in MongoDB is a powerful way to process and analyze data stored in collections. It allows you to perform operations like filtering, grouping, sorting, and transforming data.
CRUD Operations
Create
db.orders.insertOne({ "order_id": 26, "cust_id": 1006, "status": "A", "amount": 275, "items": ["apple", "banana"], "date": "2023-01-26" });
Read
db.orders.find().pretty();
Update
db.orders.updateOne( { "order_id": 2 }, { $set: { "status": "C", "amount": 500 }, $currentDate: { "lastModified": true } } );
Delete
db.orders.deleteOne({ "order_id": 1 });
Aggregation Stages
$match
Filters the documents to pass only the documents that match the specified condition(s) to the next pipeline stage.
db.orders.aggregate([ { $match: { "status": "A" } } ]);
$group
Groups input documents by the specified _id expression and for each distinct grouping, outputs a document. The _id field contains the unique group by value.
db.orders.aggregate([ { $group: { _id: "$cust_id", totalSpent: { $sum: "$amount" } } } ]);
$project
Passes along the documents with the requested fields to the next stage in the pipeline.
db.orders.aggregate([ { $project: { "order_id": 1, "items": 1, "_id": 0 } } ]);
$sort
Sorts all input documents and returns them to the pipeline in sorted order.
db.orders.aggregate([ { $sort: { "amount": -1 } } ]);
$limit
Limits the number of documents passed to the next stage in the pipeline.
db.orders.aggregate([ { $limit: 5 } ]);
$skip
Skips the first n documents and passes the remaining documents to the next stage in the pipeline.
db.orders.aggregate([ { $skip: 5 } ]);
$lookup
Performs a left outer join to another collection in the same database to filter in documents from the "joined" collection for processing.
db.orders.aggregate([ { $lookup: { from: "orderDetails", localField: "order_id", foreignField: "order_id", as: "details" } } ]);
$unwind
Deconstructs an array field from the input documents to output a document for each element.
db.orders.aggregate([ { $unwind: "$items" } ]);
$addFields
Adds new fields to documents.
db.orders.aggregate([ { $addFields: { totalWithTax: { $multiply: ["$amount", 1.1] } } } ]);
$replaceRoot
Replaces the input document with the specified document.
db.orders.aggregate([ { $replaceRoot: { newRoot: "$items" } } ]);
Aggregation Operations
$sum
Calculates and returns the sum of numeric values. $sum ignores non-numeric values.
db.orders.aggregate([ { $group: { _id: "$cust_id", totalSpent: { $sum: "$amount" } } } ]);
$avg
Calculates and returns the average value of the numeric values.
db.orders.aggregate([ { $group: { _id: "$cust_id", averageSpent: { $avg: "$amount" } } } ]);
$min
Returns the minimum value from the numeric values.
db.orders.aggregate([ { $group: { _id: "$cust_id", minSpent: { $min: "$amount" } } } ]);
$max
Returns the maximum value from the numeric values.
db.orders.aggregate([ { $group: { _id: "$cust_id", maxSpent: { $max: "$amount" } } } ]);
$first
Returns the first value from the documents for each group.
db.orders.aggregate([ { $group: { _id: "$cust_id", firstOrder: { $first: "$amount" } } } ]);
$last
Returns the last value from the documents for each group.
db.orders.aggregate([ { $group: { _id: "$cust_id", lastOrder: { $last: "$amount" } } } ]);
Example Datasets
Example documents used for performing CRUD and aggregation operations:
[ { "order_id": 1, "cust_id": 1001, "status": "A", "amount": 250, "items": ["apple", "banana"], "date": "2023-01-01" }, { "order_id": 2, "cust_id": 1002, "status": "B", "amount": 450, "items": ["orange", "grape"], "date": "2023-01-02" }, { "order_id": 3, "cust_id": 1001, "status": "A", "amount": 300, "items": ["apple", "orange"], "date": "2023-01-03" }, { "order_id": 4, "cust_id": 1003, "status": "A", "amount": 150, "items": ["banana", "grape"], "date": "2023-01-04" }, { "order_id": 5, "cust_id": 1002, "status": "C", "amount": 500, "items": ["apple", "banana"], "date": "2023-01-05" }, { "order_id": 6, "cust_id": 1004, "status": "A", "amount": 350, "items": ["orange", "banana"], "date": "2023-01-06" }, { "order_id": 7, "cust_id": 1005, "status": "B", "amount": 200, "items": ["grape", "banana"], "date": "2023-01-07" }, { "order_id": 8, "cust_id": 1003, "status": "A", "amount": 100, "items": ["apple", "orange"], "date": "2023-01-08" }, { "order_id": 9, "cust_id": 1004, "status": "C", "amount": 400, "items": ["banana", "grape"], "date": "2023-01-09" }, { "order_id": 10, "cust_id": 1001, "status": "A", "amount": 250, "items": ["apple", "grape"], "date": "2023-01-10" }, { "order_id": 11, "cust_id": 1002, "status": "B", "amount": 350, "items": ["orange", "banana"], "date": "2023-01-11" }, { "order_id": 12, "cust_id": 1003, "status": "A", "amount": 450, "items": ["apple", "orange"], "date": "2023-01-12" }, { "order_id": 13, "cust_id": 1005, "status": "A", "amount": 150, "items": ["banana", "grape"], "date": "2023-01-13" }, { "order_id": 14, "cust_id": 1004, "status": "C ", "amount": 500, "items": ["apple", "banana"], "date": "2023-01-14" }, { "order_id": 15, "cust_id": 1002, "status": "A", "amount": 300, "items": ["orange", "grape"], "date": "2023-01-15" }, { "order_id": 16, "cust_id": 1003, "status": "B", "amount": 200, "items": ["apple", "banana"], "date": "2023-01-16" }, { "order_id": 17, "cust_id": 1001, "status": "A", "amount": 250, "items": ["orange", "grape"], "date": "2023-01-17" }, { "order_id": 18, "cust_id": 1005, "status": "A", "amount": 350, "items": ["apple", "banana"], "date": "2023-01-18" }, { "order_id": 19, "cust_id": 1004, "status": "C", "amount": 400, "items": ["orange", "grape"], "date": "2023-01-19" }, { "order_id": 20, "cust_id": 1001, "status": "B", "amount": 150, "items": ["apple", "orange"], "date": "2023-01-20" }, { "order_id": 21, "cust_id": 1002, "status": "A", "amount": 500, "items": ["banana", "grape"], "date": "2023-01-21" }, { "order_id": 22, "cust_id": 1003, "status": "A", "amount": 450, "items": ["apple", "banana"], "date": "2023-01-22" }, { "order_id": 23, "cust_id": 1004, "status": "B", "amount": 350, "items": ["orange", "banana"], "date": "2023-01-23" }, { "order_id": 24, "cust_id": 1005, "status": "A", "amount": 200, "items": ["grape", "banana"], "date": "2023-01-24" }, { "order_id": 25, "cust_id": 1001, "status": "A", "amount": 300, "items": ["apple", "orange"], "date": "2023-01-25" } ]
Resources for Further Learning
- MongoDB Aggregation Documentation
- MongoDB University Courses
- MongoDB Aggregation Pipeline Builder
Feel free to clone this repository and experiment with the aggregation pipelines provided. If you have any questions or suggestions, please open an issue or submit a pull request.
$group
Groups orders by status and calculates the total amount and average amount for each status.
db.orders.aggregate([ { $group: { _id: "$status", totalAmount: { $sum: "$amount" }, averageAmount: { $avg: "$amount" } } } ]);
$project
Projects the order ID, customer ID, and a calculated field for the total amount with tax (assuming 10% tax).
db.orders.aggregate([ { $project: { "order_id": 1, "cust_id": 1, "totalWithTax": { $multiply: ["$amount", 1.1] } } } ]);
$sort
Sorts orders first by status in ascending order and then by amount in descending order.
db.orders.aggregate([ { $sort: { "status": 1, "amount": -1 } } ]);
$limit
Limits the result to the top 3 orders with the highest amount.
db.orders.aggregate([ { $sort: { "amount": -1 } }, { $limit: 3 } ]);
$skip
Skips the first 5 orders and returns the rest.
db.orders.aggregate([ { $skip: 5 } ]);
$lookup
Joins the orders collection with an orderDetails collection to add order details.
db.orders.aggregate([ { $lookup: { from: "orderDetails", localField: "order_id", foreignField: "order_id", as: "details" } } ]);
$unwind
Deconstructs the items array in each order to output a document for each item.
db.orders.aggregate([ { $unwind: "$items" } ]);
$addFields
Adds a new field discountedAmount which is 90% of the original amount.
db.orders.aggregate([ { $addFields: { discountedAmount: { $multiply: ["$amount", 0.9] } } } ]);
$replaceRoot
Replaces the root document with the items array.
db.orders.aggregate([ { $replaceRoot: { newRoot: "$items" } } ]);
$sum
Calculates the total amount for all orders.
db.orders.aggregate([ { $group: { _id: null, totalAmount: { $sum: "$amount" } } } ]);
$avg
Calculates the average amount spent per order.
db.orders.aggregate([ { $group: { _id: null, averageAmount: { $avg: "$amount" } } } ]);
$min
Finds the minimum amount spent on an order.
db.orders.aggregate([ { $group: { _id: null, minAmount: { $min: "$amount" } } } ]);
$max
Finds the maximum amount spent on an order.
db.orders.aggregate([ { $group: { _id: null, maxAmount: { $max: "$amount" } } } ]);
$first
Gets the first order placed (by date).
db.orders.aggregate([ { $sort: { "date": 1 } }, { $group: { _id: null, firstOrder: { $first: "$$ROOT" } } } ]);
$last
Gets the last order placed (by date).
db.orders.aggregate([ { $sort: { "date": -1 } }, { $group: { _id: null, lastOrder: { $last: "$$ROOT" } } } ]);
So, we have covered basic CRUD operations, all major aggregation stages, and operations, and looked into resources for further learning.
The above is the detailed content of MongoDB Aggregation Pipelines. For more information, please follow other related articles on the PHP Chinese website!

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