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MongoDB Aggregation Pipelines

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Release: 2024-07-31 20:32:41
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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"
});
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Read

db.orders.find().pretty();
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Update

db.orders.updateOne(
  { "order_id": 2 },
  {
    $set: { "status": "C", "amount": 500 },
    $currentDate: { "lastModified": true }
  }
);
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Delete

db.orders.deleteOne({ "order_id": 1 });
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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([
  { $match: { "status": "A" } }
]);
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$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" }
    }
  }
]);
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$project

Passes along the documents with the requested fields to the next stage in the pipeline.

db.orders.aggregate([
  { $project: { "order_id": 1, "items": 1, "_id": 0 } }
]);
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$sort

Sorts all input documents and returns them to the pipeline in sorted order.

db.orders.aggregate([
  { $sort: { "amount": -1 } }
]);
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$limit

Limits the number of documents passed to the next stage in the pipeline.

db.orders.aggregate([
  { $limit: 5 }
]);
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$skip

Skips the first n documents and passes the remaining documents to the next stage in the pipeline.

db.orders.aggregate([
  { $skip: 5 }
]);
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$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([
  {
    $lookup: {
      from: "orderDetails",
      localField: "order_id",
      foreignField: "order_id",
      as: "details"
    }
  }
]);
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$unwind

Deconstructs an array field from the input documents to output a document for each element.

db.orders.aggregate([
  { $unwind: "$items" }
]);
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$addFields

Adds new fields to documents.

db.orders.aggregate([
  { $addFields: { totalWithTax: { $multiply: ["$amount", 1.1] } } }
]);
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$replaceRoot

Replaces the input document with the specified document.

db.orders.aggregate([
  { $replaceRoot: { newRoot: "$items" } }
]);
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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" }
    }
  }
]);
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$avg

Calculates and returns the average value of the numeric values.

db.orders.aggregate([
  {
    $group: {
      _id: "$cust_id",
      averageSpent: { $avg: "$amount" }
    }
  }
]);
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$min

Returns the minimum value from the numeric values.

db.orders.aggregate([
  {
    $group: {
      _id: "$cust_id",
      minSpent: { $min: "$amount" }
    }
  }
]);
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$max

Returns the maximum value from the numeric values.

db.orders.aggregate([
  {
    $group: {
      _id: "$cust_id",
      maxSpent: { $max: "$amount" }
    }
  }
]);
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$first

Returns the first value from the documents for each group.

db.orders.aggregate([
  {
    $group: {
      _id: "$cust_id",
      firstOrder: { $first: "$amount" }
    }
  }
]);
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$last

Returns the last value from the documents for each group.

db.orders.aggregate([
  {
    $group: {
      _id: "$cust_id",
      lastOrder: { $last: "$amount" }
    }
  }
]);
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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" }
]
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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" }
    }
  }
]);
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$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] }
    }
  }
]);
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$sort

Sorts orders first by status in ascending order and then by amount in descending order.

db.orders.aggregate([
  { $sort: { "status": 1, "amount": -1 } }
]);
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$limit

Limits the result to the top 3 orders with the highest amount.

db.orders.aggregate([
  { $sort: { "amount": -1 } },
  { $limit: 3 }
]);
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$skip

Skips the first 5 orders and returns the rest.

db.orders.aggregate([
  { $skip: 5 }
]);
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$lookup

Joins the orders collection with an orderDetails collection to add order details.

db.orders.aggregate([
  {
    $lookup: {
      from: "orderDetails",
      localField: "order_id",
      foreignField: "order_id",
      as: "details"
    }
  }
]);
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$unwind

Deconstructs the items array in each order to output a document for each item.

db.orders.aggregate([
  { $unwind: "$items" }
]);
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$addFields

Adds a new field discountedAmount which is 90% of the original amount.

db.orders.aggregate([
  { $addFields: { discountedAmount: { $multiply: ["$amount", 0.9] } } }
]);
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$replaceRoot

Replaces the root document with the items array.

db.orders.aggregate([
  { $replaceRoot: { newRoot: "$items" } }
]);
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$sum

Calculates the total amount for all orders.

db.orders.aggregate([
  {
    $group: {
      _id: null,
      totalAmount: { $sum: "$amount" }
    }
  }
]);
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$avg

Calculates the average amount spent per order.

db.orders.aggregate([
  {
    $group: {
      _id: null,
      averageAmount: { $avg: "$amount" }
    }
  }
]);
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$min

Finds the minimum amount spent on an order.

db.orders.aggregate([
  {
    $group: {
      _id: null,
      minAmount: { $min: "$amount" }
    }
  }
]);
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$max

Finds the maximum amount spent on an order.

db.orders.aggregate([
  {
    $group: {
      _id: null,
      maxAmount: { $max: "$amount" }
    }
  }
]);
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$first

Gets the first order placed (by date).

db.orders.aggregate([
  { $sort: { "date": 1 } },
  {
    $group: {
      _id: null,
      firstOrder: { $first: "$$ROOT" }
    }
  }
]);
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$last

Gets the last order placed (by date).

db.orders.aggregate([
  { $sort: { "date": -1 } },
  {
    $group: {
      _id: null,
      lastOrder: { $last: "$$ROOT" }
    }
  }
]);
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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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