Graph lookup for recursive data in MongoDB - Mini Project: Build & Apply

Graph Lookup for Recursive Data in MongoDB

📖 Scenario: You are managing a company's employee database. Each employee may have a manager, and managers themselves can have their own managers, forming a hierarchy. You want to find all the subordinates under a specific manager, including indirect reports.

🎯 Goal: Build a MongoDB aggregation query using $graphLookup to recursively find all employees reporting to a given manager.

📋 What You'll Learn

Create a MongoDB collection named employees with documents containing _id, name, and manager_id fields.

Add a variable managerId to specify the starting manager's _id for the recursive search.

Write an aggregation pipeline using $graphLookup to find all employees reporting directly or indirectly to the manager with manager_id equal to managerId.

Include the subordinates field in the output documents containing the recursive results.

💡 Why This Matters

🌍 Real World

Companies often need to query hierarchical employee data to understand reporting structures and manage teams effectively.

💼 Career

Knowing how to use recursive queries like <code>$graphLookup</code> in MongoDB is valuable for backend developers and data engineers working with hierarchical or graph data.

1

Create the employees collection with sample data

Create a MongoDB collection called employees and insert these exact documents: { _id: 1, name: "Alice", manager_id: null }, { _id: 2, name: "Bob", manager_id: 1 }, { _id: 3, name: "Charlie", manager_id: 1 }, { _id: 4, name: "David", manager_id: 2 }, { _id: 5, name: "Eve", manager_id: 2 }.

MongoDB

// Insert the employees documents into the employees collection
// Your code here

Need a hint?

Use db.employees.insertMany() with an array of documents.

2

Define the managerId variable for the lookup

Create a variable called managerId and set it to 1 to represent the manager Alice's _id.

MongoDB

db.employees.insertMany([
  { _id: 1, name: "Alice", manager_id: null },
  { _id: 2, name: "Bob", manager_id: 1 },
  { _id: 3, name: "Charlie", manager_id: 1 },
  { _id: 4, name: "David", manager_id: 2 },
  { _id: 5, name: "Eve", manager_id: 2 }
])

// Define the managerId variable
// Your code here

Need a hint?

Use const managerId = 1 to set the variable.

3

Write the aggregation pipeline with $graphLookup

Write an aggregation pipeline on employees that uses $match to find the document with _id equal to managerId, then uses $graphLookup to recursively find all employees where manager_id matches _id in the hierarchy. Store the results in a field called subordinates.

MongoDB

db.employees.insertMany([
  { _id: 1, name: "Alice", manager_id: null },
  { _id: 2, name: "Bob", manager_id: 1 },
  { _id: 3, name: "Charlie", manager_id: 1 },
  { _id: 4, name: "David", manager_id: 2 },
  { _id: 5, name: "Eve", manager_id: 2 }
])

const managerId = 1

// Write the aggregation pipeline with $graphLookup
// Your code here

Need a hint?

Use $graphLookup with from, startWith, connectFromField, connectToField, and as fields.

4

Run the aggregation and assign the result

Run the aggregation pipeline on employees using aggregate(pipeline) and assign the result to a variable called result.

MongoDB

db.employees.insertMany([
  { _id: 1, name: "Alice", manager_id: null },
  { _id: 2, name: "Bob", manager_id: 1 },
  { _id: 3, name: "Charlie", manager_id: 1 },
  { _id: 4, name: "David", manager_id: 2 },
  { _id: 5, name: "Eve", manager_id: 2 }
])

const managerId = 1

const pipeline = [
  { $match: { _id: managerId } },
  {
    $graphLookup: {
      from: "employees",
      startWith: "$_id",
      connectFromField: "_id",
      connectToField: "manager_id",
      as: "subordinates"
    }
  }
]

// Run the aggregation and assign to result
// Your code here

Need a hint?

Use const result = db.employees.aggregate(pipeline) to run the query.