MongoDB Aggregation

You are a MongoDB database engineer. The user wants to build and execute aggregation pipelines with multiple stages and operators to transform, filter, and analyze data.

What to check first

• Run mongosh --version to verify MongoDB Shell is installed
• Confirm your MongoDB server is running with mongosh connection test
• Check your collection exists with db.getCollection("collectionName").countDocuments()

Steps

1. Connect to MongoDB using mongosh and select your database with use myDatabase
2. Start your aggregation pipeline with db.collection.aggregate([]) — the array holds all stages
3. Add a $match stage first to filter documents: { $match: { status: "active" } }
4. Use $group to aggregate values by field: { $group: { _id: "$category", total: { $sum: "$amount" } } }
5. Apply $project to reshape documents and include/exclude fields: { $project: { name: 1, total: 1, _id: 0 } }
6. Sort results with $sort: { $sort: { total: -1 } } — use 1 for ascending, -1 for descending
7. Limit output using $limit: { $limit: 10 } to get top N results
8. Chain stages in order and call .toArray() or .explain() to execute and view results

Code

const { MongoClient } = require("mongodb");

async function runAggregation() {
  const client = new MongoClient("mongodb://localhost:27017");
  
  try {
    await client.connect();
    const db = client.db("ecommerce");
    const orders = db.collection("orders");
    
    // Build aggregation pipeline with multiple stages
    const pipeline = [
      // Stage 1: Filter orders from the last 30 days
      {
        $match: {
          createdAt: {
            $gte: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000)
          },
          status: "completed"
        }
      },
      // Stage 2: Group by customer and calculate totals
      {
        $group: {
          _id: "$customerId",
          totalSpent: { $sum: "$amount" },
          orderCount: { $sum: 1 },
          avgOrderValue: { $avg: "$amount" },
          lastOrder: { $max: "$createdAt" }
        }
      },
      // Stage 3: Filter groups with total > 500
      {
        $match: {
          totalSpent: { $gt: 500 }
        }
      },
      // Stage 4: Reshape output document
      {
        $project: {
          customerId: "$_id",
          totalSpent: { $round: ["$totalSpent

Note: this example was truncated in the source. See the GitHub repo for the latest full version.

Common Pitfalls

• Treating this skill as a one-shot solution — most workflows need iteration and verification
• Skipping the verification steps — you don't know it worked until you measure
• Applying this skill without understanding the underlying problem — read the related docs first

When NOT to Use This Skill

• When a simpler manual approach would take less than 10 minutes
• On critical production systems without testing in staging first
• When you don't have permission or authorization to make these changes

How to Verify It Worked

• Run the verification steps documented above
• Compare the output against your expected baseline
• Check logs for any warnings or errors — silent failures are the worst kind

Production Considerations

• Test in staging before deploying to production
• Have a rollback plan — every change should be reversible
• Monitor the affected systems for at least 24 hours after the change