Benchmark: forEach vs reduce vs map vs filter vs for tiny

Script Preparation code:

var arr = [];
for (var i = 0; i < 100; i++) {
  arr[i] = i;
}

function someFn(i) {
  return (i * 3 * 8 / 1200 * 0.002 / 40 * 0.2);
}

var sumForEach = 0,
  sumReduce = 0,
  sumMap = 0,
  sumFilter = 0,
  sumFor = 0;

Tests:

forEach
arr.forEach(item => sumForEach += someFn(item));
reduce
sumReduce = arr.reduce((lastValue, item) => { return sumReduce += someFn(item); });
map
arr.map(item => (sumMap += someFn(item)));
filter
arr.filter(item => (sumFilter += someFn(item)));
for
for (var j = 0; j < arr.length; j++) { sumFor += arr[j]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
forEach
reduce
map
filter
for

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 136 on Android

View result in a separate tab

for

46K/s

reduce

34K/s

forEach

33K/s

map

29K/s

filter

29K/s

View exact numbers

Test name	Executions per second
✓ for	45,672 Ops/sec
reduce	33,951 Ops/sec
forEach	32,730 Ops/sec
map	29,215 Ops/sec
filter	28,620 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases to understand what is being tested.

**Benchmark Definition**

The benchmark measures the performance of different JavaScript iteration methods: `forEach`, `reduce`, `map`, `filter`, and a traditional `for` loop. The script preparation code creates an array of 100 elements, each containing a specific calculation using the `someFn` function.

**Library used**

In the provided test cases, no libraries are explicitly mentioned. However, it's likely that the JavaScript engine being tested is a browser engine (e.g., Blink for Chrome) and doesn't require any additional libraries.

**Iteration methods compared**

The benchmark tests the performance of five different iteration methods:

1. `forEach`: Iterates over an array using a callback function.
2. `reduce`: Accumulates values in an array by applying a callback function to each element.
3. `map`: Creates a new array with transformed elements using a callback function.
4. `filter`: Creates a new array with filtered elements using a callback function.
5. Traditional `for` loop: Iterates over an array manually using a `for` loop.

**Pros and cons of each approach**

Here's a brief overview of the pros and cons of each iteration method:

1. `forEach`:
	* Pros: Easy to use, doesn't require explicit indexing.
	* Cons: Can be slower than other methods due to the overhead of callback functions.
2. `reduce`:
	* Pros: Efficient for accumulating values, can handle initial value and iterate-reduce logic in one pass.
	* Cons: Requires understanding of accumulator and callback function usage.
3. `map`:
	* Pros: Creates a new array with transformed elements, can be used for parallel processing.
	* Cons: Can create unnecessary intermediate arrays, can be slower than other methods if not optimized.
4. Traditional `for` loop:
	* Pros: Direct control over iteration, no overhead from callback functions.
	* Cons: Requires explicit indexing and manual iteration management.

**Other considerations**

When choosing an iteration method, consider the following factors:

* Data size and structure
* Performance requirements
* Code readability and maintainability
* Parallel processing needs

**Benchmark results**

The provided benchmark results show the number of executions per second for each iteration method. The `reduce` method seems to be the fastest, followed by `forEach`, `map`, `filter`, and traditional `for` loop.

Keep in mind that these results may not reflect real-world performance differences due to various factors like hardware, browser optimizations, and code complexity.

forEach vs reduce vs map vs filter vs for tiny (version: 0)

same as before but only 100 items

Comparing performance of: `forEach vs reduce vs map vs filter vs for`

Created: 6 years ago by: Guest

Go to the latest result

forEach

reduce

map

filter

for

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

forEach vs reduce vs map vs filter vs for tiny (version: 0)

same as before but only 100 items

Comparing performance of: forEach vs reduce vs map vs filter vs for

Created: 6 years ago by: Guest

Go to the latest result

forEach

reduce

map

filter

for

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `forEach vs reduce vs map vs filter vs for`