Today I Learned

The aggregation frameworks is a pipeline of steps that runs on your data to convert the output on the format you need it. It provides a set of stages that you can chain together to create pipelines that process your data in a series of steps.

Here are some of the common aggregation stages:

$match: Filters documents based on specified criteria.
$project: Selects or excludes fields from documents.
$group: Groups documents by a specified field and calculates aggregate values.
$sort: Sorts documents by a specified field.
$limit: Limits the number of documents returned.
$skip: Skips a specified number of documents.
$unwind: Unwinds an array field, creating a new document for each element in the array.
$lookup: Joins two collections based on a specified field.
$redact: Redacts fields in documents based on specified criteria.
$bucket: Buckets documents into groups based on a specified field.
$sample: Samples a random subset of documents.
$geoNear: Finds documents near a specified point.

Example: Calculating Average Order Value

Scenario: Let's assume we have a collection named orders with documents representing individual orders. Each document has fields like order_id, customer_id, product_name, and price. We want to calculate the average order value for each customer.

db.orders.aggregate([
  {
    $group: {
      _id: "$customer_id",
      total_spent: { $sum: "$price" },
      total_orders: { $count: {} }
    }
  },
  {
    $project: {
      average_order_value: { $divide: ["$total_spent", "$total_orders"] }
    }
  }
])

Explanation:

$group:
- Groups the documents by customer_id.
- Calculates the total spent for each customer using $sum.
- Counts the total number of orders for each customer using $count.
$project:
- Calculates the average order value by dividing total_spent by total_orders.

Result: The aggregation pipeline will return a list of documents, each containing the customer_id and the calculated average_order_value.