Conditional expressions ($cond, $switch) in MongoDB - Mini Project: Build & Apply

Using Conditional Expressions ($cond, $switch) in MongoDB Aggregation

📖 Scenario: You work at a bookstore that stores sales data in a MongoDB collection. You want to categorize each sale based on the number of books sold.

🎯 Goal: Build an aggregation pipeline that uses MongoDB's $cond and $switch conditional expressions to add a new field saleCategory to each document. This field will describe the sale size as 'Small', 'Medium', or 'Large' based on the number of books sold.

📋 What You'll Learn

Create a collection named sales with documents containing _id and booksSold fields.

Define a threshold variable mediumThreshold to separate small and medium sales.

Use the $cond expression to classify sales as 'Small' or 'Medium/Large'.

Use the $switch expression to further classify 'Medium/Large' sales into 'Medium' or 'Large'.

Add the final saleCategory field to each document in the aggregation result.

💡 Why This Matters

🌍 Real World

Conditional expressions in MongoDB aggregation pipelines help categorize and transform data dynamically, useful in sales analysis, reporting, and decision-making.

💼 Career

Understanding <code>$cond</code> and <code>$switch</code> is essential for data analysts and backend developers working with MongoDB to create flexible and powerful data queries.

1

Create the sales collection with sample data

Create a MongoDB collection named sales and insert these exact documents: { _id: 1, booksSold: 3 }, { _id: 2, booksSold: 7 }, { _id: 3, booksSold: 12 }.

MongoDB

// Insert the sales documents here
// Your code here

Hint

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

2

Define the medium sales threshold

Create a variable named mediumThreshold and set it to 5 to separate small and medium sales.

MongoDB

db.sales.insertMany([
  { _id: 1, booksSold: 3 },
  { _id: 2, booksSold: 7 },
  { _id: 3, booksSold: 12 }
])

// Define the medium sales threshold
// Your code here

Hint

Use const mediumThreshold = 5 to define the threshold.

3

Use $cond to classify sales as Small or Medium/Large

Write an aggregation pipeline that uses $cond to add a field saleCategory with value 'Small' if booksSold is less than mediumThreshold, otherwise 'Medium/Large'. Use $addFields stage.

MongoDB

db.sales.insertMany([
  { _id: 1, booksSold: 3 },
  { _id: 2, booksSold: 7 },
  { _id: 3, booksSold: 12 }
])

const mediumThreshold = 5

// Write aggregation pipeline with $cond to classify sales
// Your code here

Hint

Use $addFields with $cond to check if booksSold is less than mediumThreshold.

4

Use $switch to refine Medium/Large classification

Extend the aggregation pipeline by adding a $set stage that uses $switch to update saleCategory: if booksSold is between mediumThreshold and 10 inclusive, set to 'Medium'; if greater than 10, set to 'Large'; otherwise keep the existing saleCategory.

MongoDB

db.sales.insertMany([
  { _id: 1, booksSold: 3 },
  { _id: 2, booksSold: 7 },
  { _id: 3, booksSold: 12 }
])

const mediumThreshold = 5

const pipeline = [
  {
    $addFields: {
      saleCategory: {
        $cond: {
          if: { $lt: ["$booksSold", mediumThreshold] },
          then: "Small",
          else: "Medium/Large"
        }
      }
    }
  }
]

// Add a $set stage with $switch to refine saleCategory
// Your code here

Hint

Use $set with $switch and branches to check ranges and assign categories.

Practice

1. What does the $cond operator do in a MongoDB aggregation pipeline?

easy

A. It chooses a value based on a simple if-else condition.

B. It sorts documents by a field value.

C. It groups documents by a key.

D. It removes duplicate documents.

Solution

1. Step 1: Understand the purpose of $cond

   $cond is used to evaluate a condition and return one value if true, another if false, similar to if-else logic.

2. Step 2: Compare with other options

   Sorting, grouping, and removing duplicates are done by other operators like $sort, $group, and $addToSet, not $cond.

3. Final Answer:

   It chooses a value based on a simple if-else condition. -> Option A

4. Quick Check:

   $cond = if-else logic [OK]

Hint: Remember $cond is like a simple if-else choice [OK]

Common Mistakes:

• Confusing $cond with $group or $sort
• Thinking $cond filters documents
• Assuming $cond handles multiple cases like $switch

2. Which of the following is the correct syntax for using $cond in a MongoDB aggregation pipeline?

easy

A. { $cond: [ <condition>, <trueValue>, <falseValue> ] }

B. { $cond: { if: <condition>, then: <trueValue>, else: <falseValue> } }

C. { $cond: { case: <condition>, then: <trueValue>, else: <falseValue> } }

D. { $cond: { when: <condition>, then: <trueValue>, else: <falseValue> } }

Solution

1. Step 1: Recall $cond syntax

   The $cond operator uses an array with three elements: condition, true value, false value.

2. Step 2: Check options

   { $cond: [ <condition>, <trueValue>, <falseValue> ] } matches the correct array syntax. Options A, C, and D use incorrect keys or object format.

3. Final Answer:

   { $cond: [ <condition>, <trueValue>, <falseValue> ] } -> Option A

4. Quick Check:

   $cond syntax = array with 3 elements [OK]

Hint: Use array syntax: condition, true, false for $cond [OK]

Common Mistakes:

• Using object keys like if/then/else instead of array
• Confusing $cond with $switch syntax
• Missing one of the three required elements

3. Given the following aggregation stage, what will be the value of the field status for a document with score: 75?

{
  $addFields: {
    status: {
      $switch: {
        branches: [
          { case: { $gte: ["$score", 90] }, then: "Excellent" },
          { case: { $gte: ["$score", 70] }, then: "Good" },
          { case: { $gte: ["$score", 50] }, then: "Average" }
        ],
        default: "Poor"
      }
    }
  }
}

medium

A. "Poor"

B. "Excellent"

C. "Average"

D. "Good"

Solution

1. Step 1: Evaluate $switch branches in order

   The first branch checks if score >= 90 (75 >= 90? No). The second checks if score >= 70 (75 >= 70? Yes).

2. Step 2: Determine matching branch and output

   Since the second branch matches, the status is set to "Good". Later branches are ignored.

3. Final Answer:

   "Good" -> Option D

4. Quick Check:

   $switch picks first true case = "Good" [OK]

Hint: Check $switch branches top to bottom, pick first true [OK]

Common Mistakes:

• Ignoring order of branches in $switch
• Choosing default instead of matching branch
• Confusing $gte logic

4. Identify the issue in this aggregation expression using $switch:

{
  $project: {
    grade: {
      $switch: {
        branches: [
          { case: { $gt: ["$score", 90] }, then: "A" },
          { case: { $gt: ["$score", 80] }, then: "B" }
        ]
      }
    }
  }
}

medium

A. Branches array must be outside $switch object.

B. Missing default value in $switch returns null for unmatched cases.

C. Using $gt instead of $gte is invalid syntax.

D. The $project stage cannot use $switch.

Solution

1. Step 1: Check $switch structure

   $switch requires branches; default is optional but without it returns null when no branch matches.

2. Step 2: Identify missing default

   The expression lacks a default field, so if score <= 80, grade is null.

3. Final Answer:

   Missing default value in $switch returns null for unmatched cases. -> Option B

4. Quick Check:

   $switch missing default = null [OK]

Hint: Always include default in $switch to avoid errors [OK]

Common Mistakes:

• Omitting default field in $switch
• Thinking $gt is invalid syntax
• Misplacing branches array

5. You want to categorize products by price using $switch in an aggregation pipeline. Prices below 20 are "Cheap", 20 to 50 are "Moderate", above 50 are "Expensive". Which of the following $switch expressions correctly implements this?

hard

A. { $switch: { branches: [ { case: { $gte: ["$price", 50] }, then: "Expensive" }, { case: { $gte: ["$price", 20] }, then: "Moderate" }, { case: { $lt: ["$price", 20] }, then: "Cheap" } ], default: "Unknown" } }

B. { $switch: { branches: [ { case: { $lte: ["$price", 20] }, then: "Cheap" }, { case: { $lt: ["$price", 50] }, then: "Moderate" }, { case: { $gte: ["$price", 50] }, then: "Expensive" } ], default: "Unknown" } }

C. { $switch: { branches: [ { case: { $lt: ["$price", 20] }, then: "Cheap" }, { case: { $and: [ { $gte: ["$price", 20] }, { $lte: ["$price", 50] } ] }, then: "Moderate" }, { case: { $gt: ["$price", 50] }, then: "Expensive" } ], default: "Unknown" } }

D. { $switch: { branches: [ { case: { $gte: ["$price", 50] }, then: "Expensive" }, { case: { $lte: ["$price", 20] }, then: "Cheap" }, { case: { $and: [ { $gt: ["$price", 20] }, { $lt: ["$price", 50] } ] }, then: "Moderate" } ], default: "Unknown" } }

Solution

1. Step 1: Analyze price ranges and conditions

   Prices below 20 are "Cheap", 20 to 50 inclusive are "Moderate", above 50 are "Expensive". Conditions must be mutually exclusive and cover all cases.

2. Step 2: Check each option's logic

   { $switch: { branches: [ { case: { $lt: ["$price", 20] }, then: "Cheap" }, { case: { $and: [ { $gte: ["$price", 20] }, { $lte: ["$price", 50] } ] }, then: "Moderate" }, { case: { $gt: ["$price", 50] }, then: "Expensive" } ], default: "Unknown" } } correctly uses $lt for below 20, $and with $gte and $lte for 20 to 50, and $gt for above 50. Others have overlapping or incorrect ranges.

3. Final Answer:

   { $switch: { branches: [ { case: { $lt: ["$price", 20] }, then: "Cheap" }, { case: { $and: [ { $gte: ["$price", 20] }, { $lte: ["$price", 50] } ] }, then: "Moderate" }, { case: { $gt: ["$price", 50] }, then: "Expensive" } ], default: "Unknown" } } -> Option C

4. Quick Check:

   Use clear, non-overlapping conditions in $switch branches [OK]

Hint: Use clear, non-overlapping conditions with $and for ranges [OK]

Common Mistakes:

• Overlapping ranges causing wrong category
• Using incorrect comparison operators
• Not covering all price values