$out and $merge for writing results in MongoDB - Mini Project: Build & Apply

$out and $merge for writing results in MongoDB

📖 Scenario: You work at a small online bookstore. You have a collection called sales that records each book sale with fields like title, author, and copies_sold. You want to create a summary collection that shows total copies sold per author.

🎯 Goal: Build an aggregation pipeline that groups sales by author and sums the copies sold. Then, write the results into a new collection using $out and update an existing collection using $merge.

📋 What You'll Learn

Create an aggregation pipeline on the sales collection.

Group documents by author and sum copies_sold as total_copies.

Use $out to write the grouped results into a new collection called author_sales_summary.

Use $merge to update or insert documents into an existing collection called author_sales_aggregate.

💡 Why This Matters

🌍 Real World

Summarizing sales data by author helps bookstores track popular authors and manage inventory efficiently.

💼 Career

Understanding $out and $merge is essential for database administrators and backend developers who manage data pipelines and reporting in MongoDB.

1

Create the sales collection with sample data

Create a variable called sales and insert these exact documents into it: {"title": "Book A", "author": "Alice", "copies_sold": 5}, {"title": "Book B", "author": "Bob", "copies_sold": 3}, {"title": "Book C", "author": "Alice", "copies_sold": 7}.

MongoDB

// Insert the exact documents into the sales collection
// Your code here

Need a hint?

Use db.sales.insertMany([...]) with the exact documents listed.

2

Create the aggregation pipeline to group by author and sum copies sold

Create a variable called pipeline that contains an array with one stage: a $group stage grouping by _id as "$author" and summing copies_sold into total_copies.

MongoDB

db.sales.insertMany([
  {"title": "Book A", "author": "Alice", "copies_sold": 5},
  {"title": "Book B", "author": "Bob", "copies_sold": 3},
  {"title": "Book C", "author": "Alice", "copies_sold": 7}
])

// Create the aggregation pipeline array with a $group stage
// Your code here

Need a hint?

Use $group with _id: "$author" and total_copies: { $sum: "$copies_sold" }.

3

Use $out to write the aggregation results to author_sales_summary

Run db.sales.aggregate() with the pipeline followed by a $out stage that writes to the collection author_sales_summary.

MongoDB

db.sales.insertMany([
  {"title": "Book A", "author": "Alice", "copies_sold": 5},
  {"title": "Book B", "author": "Bob", "copies_sold": 3},
  {"title": "Book C", "author": "Alice", "copies_sold": 7}
])

const pipeline = [
  {
    $group: {
      _id: "$author",
      total_copies: { $sum: "$copies_sold" }
    }
  }
]

// Add a $out stage to the pipeline and run aggregate
// Your code here

Need a hint?

Add { $out: "author_sales_summary" } as the last stage in the pipeline and run db.sales.aggregate(pipeline).

4

Use $merge to update or insert into author_sales_aggregate

Modify the pipeline by replacing the $out stage with a $merge stage that merges into author_sales_aggregate using _id as the unique key. Then run db.sales.aggregate(pipeline).

MongoDB

db.sales.insertMany([
  {"title": "Book A", "author": "Alice", "copies_sold": 5},
  {"title": "Book B", "author": "Bob", "copies_sold": 3},
  {"title": "Book C", "author": "Alice", "copies_sold": 7}
])

const pipeline = [
  {
    $group: {
      _id: "$author",
      total_copies: { $sum: "$copies_sold" }
    }
  },
  // Replace $out with $merge stage here
]

// Run the aggregation
// Your code here

Need a hint?

Use $merge with into, on, whenMatched, and whenNotMatched options.