Custom events in Firebase - Time & Space Complexity

Time Complexity: Custom events

O(n)

Understanding Time Complexity

When using Firebase custom events, it's important to know how the number of events affects performance.

We want to understand how the time to send events grows as we send more events.

Scenario Under Consideration

Analyze the time complexity of sending multiple custom events to Firebase Analytics.

for (let i = 0; i < n; i++) {
  firebase.analytics().logEvent('custom_event', { event_number: i });
}

This code sends n custom events, each with a unique number, to Firebase Analytics.

Identify Repeating Operations

We look at what repeats when sending events.

• Primary operation: Calling logEvent to send one event to Firebase.
• How many times: Exactly n times, once per event.

How Execution Grows With Input

Each event requires one call to send it. So, if you double the number of events, you double the calls.

Input Size (n)	Approx. API Calls/Operations
10	10 calls
100	100 calls
1000	1000 calls

Pattern observation: The number of calls grows directly with the number of events sent.

Final Time Complexity

Time Complexity: O(n)

This means the time to send events grows in a straight line with the number of events.

Common Mistake

[X] Wrong: "Sending many events at once only takes the same time as sending one event."

[OK] Correct: Each event requires its own call, so more events mean more time.

Interview Connect

Understanding how event sending scales helps you design efficient analytics and avoid slowdowns in apps.

Self-Check

"What if we batch multiple events into one call? How would the time complexity change?"