Benchmark: spread vs individual vs apply

Script Preparation code:

var data = Array.from({length: 9999}, () => Array.from({length: 6}, () => Math.random()))

function sum(a1, a2, a3, a4, a5, a6) {
    return a1 + a2 + a3 + a4 + a5 + a6;
}

Tests:

spread
let a = 0 for (let i = 0; i < 9999; ++i) { a += sum(...data[i]); } console.log(a)
individual
let a = 0 for (let i = 0; i < 9999; ++i) { let datai = data[i] a += sum(datai[0], datai[1], datai[2], datai[3], datai[4], datai[5]); } console.log(a)
Apply
let a = 0 for (let i = 0; i < 9999; ++i) { a += sum.apply(null, data[i]); } console.log(a)
Individual noprecreated
let a = 0 for (let i = 0; i < 9999; ++i) { let datai = data[i] a += sum(data[i][0], data[i][1], data[i][2], data[i][3], data[i][4], data[i][5]); } console.log(a)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
spread
individual
Apply
Individual noprecreated

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36

Browser/OS: Chrome 121 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
spread	788.7 Ops/sec
individual	1147.1 Ops/sec
Apply	757.7 Ops/sec
Individual noprecreated	278.7 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down what's being tested in this benchmark and explore the different approaches.

**Benchmark Overview**

The benchmark compares three ways to sum up elements from an array of arrays:

1. Using the spread operator (`...`) to flatten the inner array.
2. Accessing individual elements of the inner array by index (e.g., `data[i][0]`).
3. Using the `apply()` method to pass a single array to the `sum()` function.

**Script Preparation Code**

The script preparation code creates an array of arrays, where each inner array has 6 random numbers. The `sum()` function is defined as a simple addition of all elements in the input array.

**Individual Test Cases**

Each test case has a slightly different implementation:

* "spread": Uses the spread operator to flatten the inner array and pass it to the `sum()` function.
	+ Pros: Simple, concise, and easy to read. The spread operator is a modern feature that's widely supported in JavaScript engines.
	+ Cons: May have performance overhead due to the creation of a new array.
* "individual": Accesses individual elements of the inner array by index and passes them to the `sum()` function using separate arguments.
	+ Pros: Can be more efficient than the spread operator approach, as it avoids creating an intermediate array. Also, some older JavaScript engines may optimize this pattern better.
	+ Cons: Requires explicit indexing, which can make the code less readable for complex sums.
* "Apply": Uses the `apply()` method to pass a single array to the `sum()` function. The inner array is passed as the first argument, and the individual elements are provided as subsequent arguments.
	+ Pros: Can be more efficient than the spread operator approach, especially when dealing with large arrays. Also, some older JavaScript engines may optimize this pattern better.
	+ Cons: Requires the use of `apply()`, which can make the code less readable for complex sums. Additionally, some modern browsers may have issues with the number of arguments passed to `apply()`.

**Individual noprecreated**

This test case is similar to "individual", but without creating a new local variable `datai` to hold the inner array. Instead, it directly accesses the inner array elements by index.
	+ Pros: Similar efficiency benefits as "individual".
	+ Cons: Requires explicit indexing, which can make the code less readable for complex sums.

**Library Usage**

None of these test cases use any external libraries.

**Special JS Features or Syntax**

None of the benchmark test cases rely on special JavaScript features or syntax beyond what's required to implement the `sum()` function and array operations.

Related benchmarks:

spread vs individual vs apply (version: 0)

Comparing performance of: spread vs individual vs Apply vs Individual noprecreated

Created: 2 years ago by: Guest

Jump to the latest result

spread

individual

Apply

Individual noprecreated

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):