📊 Sampling Function: Execute Once Every N Calls

Executes a function once every N calls based on count. Perfect for rate-limiting logs, sampling telemetry, and reducing UI event overhead.

In modern JavaScript development, controlling when and how often a function executes is critical for performance optimization and behavior control. Among techniques like throttling and debouncing, sampling offers a unique mechanism: *execute a function once for every N calls. What Is a Sampling Function? A sampling function ensures that a given function runs only once after every fixed number of calls, say every 4th call. This is particularly useful in scenarios like: Rate-limiting logs in noisy systems. Sampling user interactions for telemetry. Reducing computational overhead in frequently triggered UI events. Unlike throttling (which limits function execution by time) or debouncing (which delays execution until quiet time), sampling is count-based. Code Example Here's a JavaScript implementation of a function: Usage: How It Works Internally, : Tracks how many times the returned function has been called (). Executes the original function only when is divisible evenly by the given count (). It uses closures to maintain internal state across invocations — an elegant and idiomatic pattern in JavaScript. Use Cases Sampling analytics events in high-frequency environments. Noise reduction in event-driven systems (e.g., mouse movement, scroll). Debug logging only every N times to avoid console spam. Throttling vs Sampling Throttling Time-based Limit execution rate Scroll throttling Edge Considerations Sampling is deterministic — e.g., 4th, 8th, 12th call — unlike time-based throttles which may vary depending on delays. It does not delay execution; it suppresses it until the condition is met. State is local to the returned function. Multiple samplers with the same source function have independent counters. Final Thoughts Sampling is a subtle but powerful tool when you need deterministic execution control based on call frequency. It's particularly valuable in analytics-heavy or high-frequency event environments, where precision and control outweigh sheer throughput. -- <!-quiz-start --Q1: When using , on which call numbers does the function execute? [ ] 1st, 2nd, 3rd, 4th [ ] 1st, 5th, 9th, 13th [x] 4th, 8th, 12th, 16th [ ] Every call after the 4th Q2: How does sampling differ from throttling? [ ] Sampling is faster [x] Sampling is count-based while throttling is time-based [ ] Throttling executes more often [ ] There is no difference Q3: What happens when you create two samplers with the same function but different counts? [ ] They share the same counter [ ] The second sampler overrides the first [x] Each sampler has its own independent counter [ ] An error is thrown <!-quiz-end --

📊 Sampling Function: Execute Once Every N Calls

jsutilsmedium

What Is a Sampling Function?

A sampling function ensures that a given function runs only once after every fixed number of calls, say every 4th call. This is particularly useful in scenarios like:

Rate-limiting logs in noisy systems.
Sampling user interactions for telemetry.
Reducing computational overhead in frequently triggered UI events.

Unlike throttling (which limits function execution by time) or debouncing (which delays execution until quiet time), sampling is count-based.

Code Example

Here's a JavaScript implementation of a sampler function:

function sampler(fn, count) {
  let callCount = 0;

  return function(...args) {
    callCount++;
    if (callCount % count === 0) {
      fn.apply(this, args);
    }
  };
}

Usage:

function message() {
  console.log("hello");
}

const sample = sampler(message, 4);

sample(); // no output
sample(); // no output
sample(); // no output
sample(); // logs "hello"
sample(); // no output
sample(); // no output
sample(); // no output
sample(); // logs "hello"

How It Works

Internally, sampler:

Tracks how many times the returned function has been called (callCount).
Executes the original function only when callCount is divisible evenly by the given count (callCount % count === 0).

It uses closures to maintain internal state across invocations — an elegant and idiomatic pattern in JavaScript.

Use Cases

Sampling analytics events in high-frequency environments.
Noise reduction in event-driven systems (e.g., mouse movement, scroll).
Debug logging only every N times to avoid console spam.

Throttling vs Sampling

Feature	Throttling	Sampling
Basis	Time-based	Call-count-based
When used	Limit execution rate	Trigger function every Nth time
Example use case	Scroll throttling	Log sampling

Edge Considerations

Sampling is deterministic — e.g., 4th, 8th, 12th call — unlike time-based throttles which may vary depending on delays.
It does not delay execution; it suppresses it until the condition is met.
State is local to the returned function. Multiple samplers with the same source function have independent counters.

Final Thoughts

Sampling is a subtle but powerful tool when you need deterministic execution control based on call frequency. It's particularly valuable in analytics-heavy or high-frequency event environments, where precision and control outweigh sheer throughput.

Quick Quiz

Test your understanding with 3 quick questions

Q1When using `sampler(fn, 4)`, on which call numbers does the function execute?

Q2How does sampling differ from throttling?

Q3What happens when you create two samplers with the same function but different counts?