1. Introduction

Tutorial Goal

The goal of this tutorial is to equip you with the knowledge and skills necessary to perform advanced queries in MongoDB using aggregation and projection.

Learning Objectives

At the end of this tutorial, you will be able to:
- Understand the concept of aggregation and projection in MongoDB
- Write advanced queries using aggregation pipeline stages
- Control the amount of data returned by your queries using projection
- Use different aggregation operators and pipeline stages

Prerequisites

Before you start, it's recommended that you have a basic understanding of MongoDB, including creating databases, collections, and simple queries. Knowledge of JavaScript would also be beneficial since we'll be using it in our examples.

2. Step-by-Step Guide

Aggregation in MongoDB is a way of grouping data and performing operations on that data, such as counting, summing, averaging, etc. The result of these operations can then be projected (i.e., displayed) as you see fit.

Projection is the way to control which fields from the queried documents are returned. This could be beneficial if you only need a subset of the data contained within your documents.

Aggregation

The aggregation framework in MongoDB allows you to perform complex data analysis and generate reports. The framework aggregates data from multiple documents and performs a variety of operations on the aggregated data to return a computed result.

Projection

Projection is a way to specify the inclusion or exclusion of fields from documents. By default, all fields are returned. However, you can specify the inclusion of certain fields, exclusion of others, or a combination of both.

3. Code Examples

Example 1: Basic Aggregation

db.orders.aggregate([
   {
      $group : {
         _id : "$cust_id",
         total : {
            $sum : "$amount"
         }
      }
   }
])

In this example, the $group stage groups the documents by the cust_id field to calculate a total quantity for each distinct cust_id using the $sum operator. The output will be a list of cust_id and their respective total amount.

Example 2: Projection

db.orders.find( {}, { item: 1, qty: 1 } )

In this example, we are only requesting the item and qty fields from the orders collection. The returned documents will only contain these fields, plus the _id field.

4. Summary

In this tutorial, we have covered the basics of using aggregation and projection in MongoDB for advanced queries. We learned about the aggregation framework, projection, and how to use them to group, sort, and control the amount of data returned by your queries.

To further your learning, you could explore more advanced aggregation operators and pipeline stages, such as $match, $limit, and $lookup.

5. Practice Exercises

1. Write an aggregation query to find the average quantity of each item sold.
2. Write a projection query to return only the customer id and total amount fields from the orders collection.
3. Write an aggregation query to find the total quantity of each item sold, then sort the result in descending order.

Each of these exercises requires the use of concepts covered in this tutorial. Try to complete them on your own, then check your solutions against others. This will help reinforce what you've learned and improve your MongoDB query-writing skills.