Benchmark: sort vs toSorted vs spread-and-sort vs just-spread

Script Preparation code:

var input = [];
for (var i = 0; i < 100000; i++) {
  input[i] = Math.round(Math.random() * 1000000);
}

Tests:

regular sort
var regularSort = input.sort();
toSorted
var sorted = input.toSorted()
spread and sort
var spreadAndSort = [...input].sort()
just spread
var justSpread = [...input]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
regular sort
toSorted
spread and sort
just spread

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 18_3_0 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) CriOS/132.0.6834.100 Mobile/15E148 Safari/604.1

Browser/OS: Chrome Mobile iOS 132 on iOS 18.3.0

View result in a separate tab

Test name	Executions per second
regular sort	155.8 Ops/sec
toSorted	145.9 Ops/sec
spread and sort	141.4 Ops/sec
just spread	15427.1 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Overview**

The benchmark tests four different approaches for sorting an array of numbers:

1. Regular `sort()`
2. Using the `toSorted()` library
3. Spreading the input array using the spread operator (`[...input]`) followed by a regular sort
4. Just spreading the input array without sorting it

**Options Compared**

The benchmark compares two main approaches for each test case:

1. **Sorting**: Regular `sort()`, using the `toSorted()` library, and the combination of spreading and regular sort.
2. **Array Spreading**: Using the spread operator (`[...input]`) in different ways: with and without sorting.

**Pros and Cons**

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

1. **Regular `sort()`**:
	* Pros: Simple, widely supported, and well-documented.
	* Cons: Can be slower than other approaches for large datasets due to its overhead.
2. **Using `toSorted()` library**:
	* Pros: Optimized for sorting performance, may be faster than regular `sort()`.
	* Cons: Requires an external library, which can add dependency and complexity.
3. **Spreading and Regular Sort**:
	* Pros: Can be faster than regular `sort()` due to the spread operator's optimization for array copying.
	* Cons: Requires creating a new array using the spread operator, which can lead to additional memory allocation.
4. **Just Spreading without Sorting**:
	* Pros: Eliminates the overhead of sorting and only allocates memory for the spread operation.
	* Cons: Does not perform any actual sorting, so it may not be useful for this specific benchmark.

**Library: `toSorted()`**

The `toSorted()` library is likely a third-party implementation that provides an optimized sorting algorithm. Its purpose is to provide a faster and more efficient way to sort arrays compared to the regular `sort()` method.

**Special JavaScript Features/Syntax**

None of the test cases use any special JavaScript features or syntax beyond standard language constructs (e.g., array spreading, loops).

**Other Alternatives**

If you want to explore other alternatives for sorting arrays in JavaScript, consider the following:

1. **Array.prototype.map()` + `Array.prototype.reduce()`: This approach uses two built-in methods to sort an array without modifying it.
2. **`lodash.sort()`**: Another popular library that provides a high-performance sorting algorithm.

When choosing a sorting approach, consider factors such as performance, memory usage, and compatibility with older browsers or environments.

Related benchmarks:

sort vs toSorted vs spread-and-sort vs just-spread (version: 0)

Comparing performance of: regular sort vs toSorted vs spread and sort vs just spread

Created: one year ago by: Registered User

Jump to the latest result

regular sort

toSorted

spread and sort

just spread

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):