Benchmark: Lodash _.union vs native Set() with large arrays

HTML Preparation code:

<script type="text/javascript" src="https://cdn.jsdelivr.net/npm/lodash@4.17.10/lodash.min.js"></script>

Script Preparation code:

var a = new Array(1000).map((x,i) => i);
var b = new Array(500).map((x,i) => 500 - i)

Tests:

_.union
var c = _.union(a, b)
Set() spread into array
var c = [...(new Set(a, b))]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.union
Set() spread into array

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_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36

Browser/OS: Chrome 127 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
_.union	60980.3 Ops/sec
Set() spread into array	134689.7 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 explain what's being tested.

**Benchmark Overview**

The benchmark measures the performance of two approaches: `_.union` from Lodash and creating a new Set using the spread operator (`Set()` with large arrays).

**Lodash _.union**

`.union()` is a function that takes two arrays as input and returns a new array containing all unique elements from both arrays.

**Native Set() with large arrays**

Creating a new Set using the spread operator `(...)` involves creating an iterable object (in this case, an array) and passing it to the Set constructor. The Set constructor then creates a new Set object containing only unique elements from the input iterable.

**Comparison of approaches**

The benchmark compares two approaches:

1. **Lodash _.union**: This approach uses the `_.union()` function from Lodash, which is a specialized library for functional programming in JavaScript.
2. **Native Set() with large arrays**: This approach uses the spread operator to create a new Set object from the input array.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Lodash _.union**
	* Pros:
		+ More concise code
		+ May be faster due to optimized implementation
	* Cons:
		+ Requires an additional library (Lodash) to be included in the benchmark
		+ May not be as performant on older browsers or versions of JavaScript
2. **Native Set() with large arrays**
	* Pros:
		+ No additional libraries required
		+ Should be supported by all modern browsers and versions of JavaScript
	* Cons:
		+ Code can become more verbose due to the spread operator syntax
		+ May not be as performant on very large input sizes (due to creation of intermediate arrays)

**Other considerations**

When choosing between these approaches, consider the following factors:

1. **Code readability**: If conciseness is important, `_.union()` might be a better choice.
2. **Performance**: If performance is critical, native Set() with large arrays might be a better option (although this may not always be the case).
3. **Browser support**: If you need to support older browsers or versions of JavaScript, native Set() with large arrays might be a safer bet.

**Library and syntax**

The `Set()` constructor is a built-in function in modern JavaScript, introduced in ECMAScript 2015 (ES6). The spread operator (`...`) was also introduced in ES6.

In the benchmark code, Lodash library version 4.17.10 is used, which includes the `_union()` function.

Overall, this benchmark provides a useful comparison between two approaches to creating unique arrays in JavaScript, highlighting the trade-offs between conciseness, performance, and browser support.

Related benchmarks:

Lodash _.union vs native Set() with large arrays (version: 0)

Comparing performance of: _.union vs Set() spread into array

Created: 4 months ago by: Guest

Jump to the latest result

_.union

Set() spread into array

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):