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MongoDBquery~5 mins

Date expressions ($year, $month, $dayOfMonth) in MongoDB - Time & Space Complexity

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Time Complexity: Date expressions ($year, $month, $dayOfMonth)
O(n)
Understanding Time Complexity

When using date expressions like $year, $month, and $dayOfMonth in MongoDB, it's important to know how the time to run queries changes as data grows.

We want to understand how the work done by these expressions grows when there are more documents to process.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.


db.orders.aggregate([
  { $project: {
      year: { $year: "$orderDate" },
      month: { $month: "$orderDate" },
      day: { $dayOfMonth: "$orderDate" }
    }
  }
])

This code extracts the year, month, and day from the orderDate field for each document in the orders collection.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

  • Primary operation: Applying date extraction expressions to each document.
  • How many times: Once per document in the collection.
How Execution Grows With Input

Each document requires the date fields to be extracted once, so the total work grows directly with the number of documents.

Input Size (n)Approx. Operations
1010 date extractions
100100 date extractions
10001000 date extractions

Pattern observation: The work grows in a straight line as the number of documents increases.

Final Time Complexity

Time Complexity: O(n)

This means the time to run the query grows directly in proportion to the number of documents processed.

Common Mistake

[X] Wrong: "Using date expressions is instant and does not depend on data size."

[OK] Correct: Each document must be processed individually, so more documents mean more work and longer time.

Interview Connect

Understanding how operations scale with data size helps you explain query performance clearly and shows you know how databases handle data internally.

Self-Check

"What if we added a $match stage before $project to filter documents? How would the time complexity change?"

Practice

(1/5)
1. What does the MongoDB expression {$year: "$dateField"} return when used in an aggregation pipeline?
easy
A. The month number of the date
B. The year part of the date stored in dateField
C. The full date as a string
D. The day of the week of the date

Solution

  1. Step 1: Understand the $year operator

    The $year expression extracts the year component from a date value.

  2. Step 2: Apply to the field dateField

    Using {$year: "$dateField"} returns the year number from the date stored in dateField.

  3. Final Answer:

    The year part of the date stored in dateField -> Option B

  4. Quick Check:

    $year extracts year [OK]
Hint: Remember $year extracts only the year number from a date [OK]
Common Mistakes:
  • Confusing $year with $month or $dayOfMonth
  • Expecting a full date string instead of just the year
  • Using $year outside aggregation pipeline
2. Which of the following is the correct syntax to extract the month from a date field named createdAt in a MongoDB aggregation pipeline?
easy
A. { $month: "$createdAt" }
B. { $month: createdAt }
C. { month: "$createdAt" }
D. { $month: "createdAt" }

Solution

  1. Step 1: Identify correct field reference syntax

    In MongoDB aggregation, field names must be referenced as strings with a $ prefix, like "$createdAt".

  2. Step 2: Confirm correct operator usage

    The operator to extract month is $month, so the correct syntax is { $month: "$createdAt" }.

  3. Final Answer:

    { $month: "$createdAt" } -> Option A

  4. Quick Check:

    Field names need "$" prefix in aggregation [OK]
Hint: Use "$fieldName" to reference fields inside aggregation [OK]
Common Mistakes:
  • Omitting quotes and $ prefix around field name
  • Using operator without $ sign
  • Passing field name as plain string without $
3. Given the following aggregation stage, what will be the output for a document with dateField value of ISODate("2023-07-15T10:00:00Z")? 
{ $project: { year: { $year: "$dateField" }, month: { $month: "$dateField" }, day: { $dayOfMonth: "$dateField" } } }
medium
A. { year: 2023, month: 7, day: 14 }
B. { year: 2023, month: 6, day: 15 }
C. { year: 2023, month: 7, day: 15 }
D. { year: 2022, month: 7, day: 15 }

Solution

  1. Step 1: Extract year, month, and day from the date

    The date is July 15, 2023. So, year = 2023, month = 7 (July), day = 15.

  2. Step 2: Confirm output matches extracted values

    The output document will have year: 2023, month: 7, day: 15 as projected.

  3. Final Answer:

    { year: 2023, month: 7, day: 15 } -> Option C

  4. Quick Check:

    Date parts match output [OK]
Hint: Remember months are 1-based in MongoDB date expressions [OK]
Common Mistakes:
  • Assuming months start at 0 instead of 1
  • Confusing dayOfMonth with dayOfWeek
  • Misreading the date value
4. You wrote this aggregation stage to get the day of the month from orderDate: 
{ $project: { day: { $dayOfMonth: orderDate } } }
But it throws an error. What is the mistake?
medium
A. Missing quotes and $ before field name in $dayOfMonth
B. Using $project instead of $match
C. Field orderDate is not a date type
D. Incorrect operator; should use $day instead

Solution

  1. Step 1: Check field reference syntax inside $dayOfMonth

    Field names must be referenced as strings with a $ prefix, so it should be "$orderDate".

  2. Step 2: Identify the cause of error

    Using orderDate without quotes and $ causes a syntax error in aggregation.

  3. Final Answer:

    Missing quotes and $ before field name in $dayOfMonth -> Option A

  4. Quick Check:

    Field names need "$" prefix in aggregation [OK]
Hint: Always use "$fieldName" inside aggregation expressions [OK]
Common Mistakes:
  • Forgetting $ and quotes around field names
  • Assuming $day is a valid operator
  • Confusing aggregation stages
5. You want to group sales documents by the year and month of their saleDate field. Which aggregation pipeline stage correctly groups by year and month using date expressions?
hard
A. { $group: { _id: { year: { $year: "$saleDate" }, month: "$month" }, totalSales: { $sum: "$amount" } } }
B. { $group: { _id: { year: "$year", month: "$month" }, totalSales: { $sum: "$amount" } } }
C. { $group: { _id: { year: { $year: saleDate }, month: { $month: saleDate } }, totalSales: { $sum: "$amount" } } }
D. { $group: { _id: { year: { $year: "$saleDate" }, month: { $month: "$saleDate" } }, totalSales: { $sum: "$amount" } } }

Solution

  1. Step 1: Use correct field references with $year and $month

    Field names must be referenced as strings with $ prefix, so "$saleDate" is correct.

  2. Step 2: Verify grouping keys and sum operator

    Grouping by year and month extracted from saleDate and summing amount is done correctly in { $group: { _id: { year: { $year: "$saleDate" }, month: { $month: "$saleDate" } }, totalSales: { $sum: "$amount" } } }.

  3. Final Answer:

    { $group: { _id: { year: { $year: "$saleDate" }, month: { $month: "$saleDate" } }, totalSales: { $sum: "$amount" } } } -> Option D

  4. Quick Check:

    Correct field references and operators used [OK]
Hint: Group by {_id: {year: {$year: "$field"}, month: {$month: "$field"}}} [OK]
Common Mistakes:
  • Using field names without $ and quotes
  • Mixing string field names with expressions
  • Incorrectly mixing aggregation operators
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