Benchmark: Set vs Array for unique list (convert set to array)2

Script Preparation code:

var a = Array(1000).fill(null).map((a, b) => b);

Tests:

Unique Array
var b = []; a.forEach(x => { if (!b.includes(x)) b.push(x); }); a.map(x => x);
Set
var c = new Set(); a.forEach(x => c.add(x)); var b = Array.from(a); b.map(x => x);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Unique Array
Set

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Windows

View result in a separate tab

Test name	Executions per second
Unique Array	12203.3 Ops/sec
Set	60140.9 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**Benchmark Definition**

The provided JSON defines two benchmark tests:

1. **Set vs Array for unique list (convert set to array)2**
This test compares the performance of using an array and a set data structure to create a unique list from a large dataset.
2. The second test, "Unique Array" and "Set", are individual microbenchmarks that measure the performance of adding elements to an array and converting it to a unique list using `Array.includes()`, and the performance of using a set to achieve the same result.

**Options Compared**

The two main options compared in these benchmarks are:

1. **Array**: A traditional JavaScript array, which can be used to store collections of values.
2. **Set**: A data structure that stores unique values, allowing for efficient addition, lookup, and removal of elements.

**Pros and Cons**

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

* **Array**:
	+ Pros: Easy to use, flexible, and widely supported.
	+ Cons: Can be slow for large datasets due to the need to iterate through all elements to check for uniqueness.
* **Set**:
	+ Pros: Efficient insertion, lookup, and removal of unique values, making it suitable for large datasets.
	+ Cons: May not be as intuitive or easy to use for small datasets.

**Library/Functionality Used**

In the provided benchmark tests, no specific libraries are used. However, the `Array.from()` function is employed in one of the test cases to convert a set to an array. This function returns a new array from an iterable or an array-like object, which is useful for converting sets to arrays.

**Special JS Feature/Syntax**

The benchmark tests use a JavaScript feature called "arrow functions" (e.g., `x => b`) to define small, anonymous functions. Arrow functions are a shorthand way of defining functions that were previously defined using the `function` keyword. They provide a concise and readable syntax for simple function definitions.

**Other Considerations**

When designing microbenchmarks like these, it's essential to consider factors such as:

* **Dataset size**: The size of the dataset being tested can significantly impact performance.
* **Browser support**: Ensure that the benchmark tests work on multiple browsers, including older versions.
* **Platform**: Test the benchmarks on various devices and platforms to ensure consistency.

**Alternatives**

Other alternatives for creating unique lists include using a `Map` data structure or a library like Lodash's `uniqBy()` function. However, these approaches may introduce additional overhead or complexity compared to using an array or set.

For example, using a `Map` can be useful if you need to perform additional operations on the elements being added to the map:

```javascript
const map = new Map();
a.forEach(x => {
  if (!map.has(x)) map.set(x, x);
});
```

Similarly, Lodash's `uniqBy()` function provides a convenient way to create unique arrays while ignoring certain properties:

```javascript
import _ from 'lodash';

_.uniqBy(a, 'property');
```

In summary, the provided benchmark tests compare the performance of using an array and a set data structure to create unique lists. The choice of approach depends on the specific requirements and constraints of your application.

Related benchmarks:

Set vs Array for unique list (convert set to array)2 (version: 0)

Comparing performance of: Unique Array vs Set

Created: 5 years ago by: Registered User

Jump to the latest result

Unique Array

Set

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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