Benchmark: Array.sort 1 vs Array.map x1

Script Preparation code:

const shuffleArray = array => {
    const arr = [...array];
    for (let i = arr.length - 1; i > 0; i--) {
        const j = Math.floor(Math.random() * (i + 1));
        const temp = arr[i];
        arr[i] = arr[j];
        arr[j] = temp;
    }
    return arr;
}

var testArr = Array.from({
    length: 5000
}, () => ({val: Math.floor(Math.random() * 4000)}));
var scrambled = shuffleArray(testArr);

​x
 
const shuffleArray = array => {    const arr = [...array];    for (let i = arr.length - 1; i > 0; i--) {        const j = Math.floor(Math.random() * (i + 1));        const temp = arr[i];        arr[i] = arr[j];        arr[j] = temp;    }    return arr;}​var testArr = Array.from({    length: 5000}, () => ({val: Math.floor(Math.random() * 4000)}));var scrambled = shuffleArray(testArr);

Tests:

Array.sort
scrambled.sort((a,b) => b.val - a.val);
scrambled.sort((a,b) => b.val - a.val);
Array.map
testArr.map((t) => t.val)
testArr.map((t) => t.val)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
Array.sort
Array.map

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36

Browser/OS: Chrome 118 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Array.sort	18256.5 Ops/sec
Array.map	86007.8 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

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

Benchmark Definition

The provided JSON defines a JavaScript microbenchmark called Array.sort 1 vs Array.map x1. This benchmark compares the performance of two different approaches to sort an array:

Array.sort: This method sorts the array in place, using a compare function to determine the order of elements.
Array.map: This method creates a new array with the results of applying a provided function to each element of the original array.

Options Compared

The benchmark compares the performance of these two approaches:

Array.sort (first approach)
Array.map (second approach)

Pros and Cons of Each Approach

Array.sort

Pros:

Efficient: Sorting an array in place can be faster than creating a new array, especially for large datasets.
Memory-friendly: Only a single array needs to be allocated.

Cons:

Mutates the original array: The sorting process modifies the original array, which may not be desirable in some cases.
Slow for small arrays: For small arrays, the overhead of sorting can be significant compared to creating and manipulating a new array.

Array.map

Pros:

Creates a new array: This approach creates a new array with the sorted elements, leaving the original array unchanged.
Faster for small arrays: Creating and manipulating a new array can be faster than sorting in place, especially for small arrays.

Cons:

Memory-intensive: Creating a new array requires allocating additional memory.
Slower for large arrays: Sorting in place can be faster for large datasets due to reduced memory allocation and deallocation overhead.

Library Used

None explicitly mentioned, but the shuffleArray function is used to randomly shuffle the test array. This is likely a utility function for generating random data, rather than a library specifically used by the benchmark.

Special JS Features or Syntax

None explicitly mentioned in the provided code snippets, so we can assume that these features are not being used.

Alternative Approaches

Other approaches to sorting an array could include:

Array.prototype.forEach(): This method iterates over the array and performs a callback function on each element.
Reduc(): This method reduces the array to a single value by applying a callback function to each element.
Native sort functions: Some programming languages, like Java or C++, provide built-in sorting functions that can be used.

In JavaScript, alternative approaches might include:

Using Array.prototype.forEach() with a custom loop to achieve similar performance to Array.sort.
Implementing a custom sorting algorithm, such as quicksort or mergesort.
Using a library like Lodash to simplify the implementation of sorting algorithms.

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The provided JSON defines a JavaScript microbenchmark called `Array.sort 1 vs Array.map x1`. This benchmark compares the performance of two different approaches to sort an array:

1. **Array.sort**: This method sorts the array in place, using a compare function to determine the order of elements.
2. **Array.map**: This method creates a new array with the results of applying a provided function to each element of the original array.

**Options Compared**

The benchmark compares the performance of these two approaches:

* `Array.sort` (first approach)
* `Array.map` (second approach)

**Pros and Cons of Each Approach**

### Array.sort

Pros:

* **Efficient**: Sorting an array in place can be faster than creating a new array, especially for large datasets.
* **Memory-friendly**: Only a single array needs to be allocated.

Cons:

* **Mutates the original array**: The sorting process modifies the original array, which may not be desirable in some cases.
* **Slow for small arrays**: For small arrays, the overhead of sorting can be significant compared to creating and manipulating a new array.

### Array.map

Pros:

* **Creates a new array**: This approach creates a new array with the sorted elements, leaving the original array unchanged.
* **Faster for small arrays**: Creating and manipulating a new array can be faster than sorting in place, especially for small arrays.

Cons:

* **Memory-intensive**: Creating a new array requires allocating additional memory.
* **Slower for large arrays**: Sorting in place can be faster for large datasets due to reduced memory allocation and deallocation overhead.

**Library Used**

None explicitly mentioned, but the `shuffleArray` function is used to randomly shuffle the test array. This is likely a utility function for generating random data, rather than a library specifically used by the benchmark.

**Special JS Features or Syntax**

None explicitly mentioned in the provided code snippets, so we can assume that these features are not being used.

**Alternative Approaches**

Other approaches to sorting an array could include:

* **Array.prototype.forEach()**: This method iterates over the array and performs a callback function on each element.
* **Reduc()**: This method reduces the array to a single value by applying a callback function to each element.
* **Native sort functions**: Some programming languages, like Java or C++, provide built-in sorting functions that can be used.

In JavaScript, alternative approaches might include:

* Using `Array.prototype.forEach()` with a custom loop to achieve similar performance to `Array.sort`.
* Implementing a custom sorting algorithm, such as quicksort or mergesort.
* Using a library like Lodash to simplify the implementation of sorting algorithms.

Related benchmarks:

Array.sort 1 vs Array.map x1 (version: 0)

Comparing performance of: Array.sort vs Array.map

Created: one year ago by: Guest

Jump to the latest result

Array.sort

Array.map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

Array.sort

Array.map