Benchmark: For Each Vs Map - MeasureThat.net

Script Preparation code:

var array = [];
array.forEach( i => array.push(i) );

var manipulateFn = num => {
	return num * 2 * 3;
}

Tests:

map
var newArray = array.map( i => {console.log(manipulateFn(i))});
foreach
var newArray = []; array.forEach( i => { // newArray.push(manipulateFn(i)); console.log(manipulateFn(i)); });
for
var newArray = []; for(let i = 0; i<array.length; i++){ console.log(i); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
foreach
for

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 6 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36

Browser/OS: Chrome 70 on Windows

View result in a separate tab

Test name	Executions per second
map	12501086.0 Ops/sec
foreach	13430807.0 Ops/sec
for	13774787.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its test cases.

**Benchmark Overview**

The benchmark compares three different approaches for manipulating an array of numbers:

1. Using `Array.prototype.map()`
2. Using `Array.prototype.forEach()` with a callback function
3. Using a traditional `for` loop

The goal is to measure which approach performs better in terms of execution speed.

**Options Compared**

We have two main options being compared:

* `map()`: This method creates a new array by applying a provided function to each element of the original array.
* `forEach()`: This method executes a callback function once for each element in an array, without returning any value. Note that `forEach()` does not create a new array, unlike `map()`.
* Traditional `for` loop: This approach uses a manual index variable to iterate over the array elements.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

* `map()`: Pros:
	+ Creates a new array with the transformed values.
	+ Returns an array, which can be used as needed.
	+ Can handle complex transformations.
Cons:
	+ Requires memory allocation for the new array.
	+ May incur more overhead due to function call and object creation.
* `forEach()`: Pros:
	+ Does not create a new array, making it more memory-efficient.
	+ Eliminates the need for explicit loop variable management.
	+ Can be useful when working with asynchronous code or events.
Cons:
	+ Does not return any value, which may limit its usefulness in some cases.
	+ Callback function can make debugging and error handling more challenging.
* Traditional `for` loop: Pros:
	+ Has direct access to the array elements without creating a new scope.
	+ Can be optimized for performance by minimizing overhead.
Cons:
	+ Requires manual index management, which can lead to errors.
	+ May incur higher memory usage due to the need for local variables.

**Library and Special Features**

In this benchmark, no specific libraries or special features are being tested. However, it's worth noting that some modern browsers may provide additional features or optimizations for these array methods.

**Other Considerations**

When choosing an approach, consider the trade-offs between memory usage, performance, and code readability:

* If you need to transform a large dataset, `map()` might be a good choice due to its ease of use and flexibility.
* For smaller datasets or applications with strict resource constraints, `forEach()` could be a better option.
* Traditional `for` loops are often preferred for their direct control over iteration and minimal overhead.

**Alternatives**

Some alternative approaches you might consider when working with arrays include:

* Using `reduce()`: This method reduces the array to a single value by applying a callback function to each element.
* Utilizing ES6 array methods like `filter()` or `every()`, which offer more concise ways to manipulate arrays.
* Leveraging modern browser optimizations, such as Web Workers or SIMD instructions, for large-scale data processing.

In conclusion, understanding the trade-offs between these approaches will help you choose the most suitable method for your specific use case and performance requirements.

Related benchmarks:

For Each Vs Map (version: 0)

Comparing performance of: map vs foreach vs for

Created: 6 years ago by: Registered User

Jump to the latest result

map

foreach

for

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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