Benchmark: map vs. map arrow vs for vs. for in vs. forEach

Script Preparation code:

var a = Array(10000).fill(null).map((a, index) => `foo  ${index}`)

Tests:

map
var b = a.map(function(c) { return `${c}+1` ; });
for in
var b = []; for (var i in a) { b.push(`${a[i]}+1`); }
for
var b = []; for (var i = 0; i < a.length; i++) { b.push(`${a[i]}+1`); }
forEach
var b = []; a.forEach(function(c) { b.push(`${c}+1`); });
map arrow
var b = a.map(c => `${c}+1`);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
for in
for
forEach
map arrow

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:146.0) Gecko/20100101 Firefox/146.0

Browser/OS: Firefox 146 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
map	13959.3 Ops/sec
for in	3070.6 Ops/sec
for	15246.9 Ops/sec
forEach	13638.3 Ops/sec
map arrow	13588.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**Benchmark Overview**

The provided benchmark compares the performance of four different approaches to iterate over an array: `map`, `map arrow` (introduced in ECMAScript 2017), `for`, and `forEach`. Each approach is tested against its variants, which are discussed below.

**Approaches Compared**

1. **map**: This approach uses the `Array.prototype.map()` method, which creates a new array with the results of applying a provided function to each element in the original array.
2. **map arrow**: This approach uses an arrow function (introduced in ECMAScript 2017) as the callback function for the `Array.prototype.map()` method. Arrow functions provide a concise syntax for defining small, single-expression functions.
3. **for**: This approach uses a traditional `for` loop to iterate over the array elements.
4. **forEach**: This approach uses the `Array.prototype.forEach()` method, which executes the provided function once for each element in the original array.

**Pros and Cons of Each Approach**

1. **map**:
	* Pros: Efficient use of memory (new array is created, but it's a sparse array with only necessary values).
	* Cons: Creates a new array, which can be memory-intensive for large datasets.
2. **map arrow**:
	* Pros: Concise syntax and slightly faster execution compared to traditional `map` methods.
	* Cons: Creates a new array, just like the original `map` method.
3. **for**:
	* Pros: Can be optimized by the JavaScript engine for performance-critical loops.
	* Cons: Requires manual indexing and can lead to errors if not implemented correctly.
4. **forEach**:
	* Pros: Convenient syntax and doesn't require explicit looping.
	* Cons: May have performance overhead compared to traditional `for` loops.

**Library Used**

None of the provided benchmarks explicitly use a third-party library, but it's worth noting that some libraries like Lodash may offer optimized implementations of these methods.

**Special JS Feature/Syntax**

The benchmark uses arrow functions (introduced in ECMAScript 2017) for the `map` method, which is a new syntax feature. This allows for concise and readable code, making it easier to understand and maintain large applications.

**Other Alternatives**

If you're interested in exploring alternative approaches, consider the following:

1. **Array.prototype.reduce()**: While not directly comparable to the current benchmark, `reduce()` can be used to transform arrays in a more functional programming style.
2. **Iterator methods**: Other iterator methods like `forEach`, `map`, and `filter` provide similar functionality to the current benchmark but may have different performance characteristics.
3. **Native WebAssembly implementations**: Some browsers now support native WebAssembly implementations, which can lead to significant performance improvements for certain types of computations.

Keep in mind that the choice of approach depends on the specific requirements of your project, including performance, memory usage, and code readability.

Related benchmarks:

map vs. map arrow vs for vs. for in vs. forEach (version: 2)

Comparing performance of: map vs for in vs for vs forEach vs map arrow

Created: 3 years ago by: Registered User

Jump to the latest result

map

for in

for

forEach

map arrow

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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