Benchmark: native-slice-vs-chunk

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var test = Array.from({
    length: 100000
}, () => Math.random())

Tests:

Native slice
test.slice(0,5000)
lodash chunk
_.chunk(test,5000)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native slice
lodash chunk

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:133.0) Gecko/20100101 Firefox/133.0

Browser/OS: Firefox 133 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
Native slice	887065.6 Ops/sec
lodash chunk	3543.5 Ops/sec

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark and its components.

**Benchmark Overview**

The MeasureThat.net website allows users to create and run JavaScript microbenchmarks, including this specific benchmark: `native-slice-vs-chunk`. The benchmark compares the performance of two approaches: using the native `Array.prototype.slice()` method versus using the `_chunk()` function from the Lodash library.

**Script Preparation Code**

The script preparation code for the benchmark is:
```javascript
var test = Array.from({ length: 100000 }, () => Math.random());
```
This code creates an array of 100,000 random numbers and assigns it to the `test` variable. This array will be used as the input data for the benchmark.

**Html Preparation Code**

The HTML preparation code includes a link to the Lodash library:
```html
<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>
```
This script tag loads the Lodash library, which provides the `_chunk()` function used in one of the benchmark test cases.

**Test Cases**

The benchmark consists of two individual test cases:

1. **Native slice**: This test case measures the performance of using the native `Array.prototype.slice()` method to extract a subset of 5,000 elements from the input array `test`.
```javascript
test.slice(0,5000)
```
2. **Lodash chunk**: This test case measures the performance of using the Lodash `_chunk()` function to divide the input array into chunks of 5,000 elements.
```javascript
_.chunk(test,5000)
```
**Comparison**

The benchmark compares the execution time (measured in executions per second) for both test cases. The results will show which approach is faster and more efficient.

**Pros and Cons**

Here are some pros and cons of each approach:

* **Native slice**: Pros:
	+ Fast and lightweight, as it doesn't require loading an external library.
	+ May be optimized by the browser's JavaScript engine.
Cons:
	+ May not work correctly for all input arrays or sizes.
	+ Can be slower than using a library like Lodash if the array size is large.
* **Lodash chunk**: Pros:
	+ Provides a robust and well-tested implementation that works with various input arrays and sizes.
	+ May offer better performance for larger array sizes due to its optimized algorithm.
Cons:
	+ Requires loading an external library, which can add overhead.
	+ May not be as lightweight or fast as the native `Array.prototype.slice()` method.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of functions for tasks such as array manipulation, string manipulation, and more. The `_chunk()` function is one of its many functions that can divide an input array into smaller chunks.

**Special JS Feature/Syntax**

This benchmark does not use any special JavaScript features or syntax. It only relies on standard JavaScript functionality and the Lodash library for the `chunk` test case.

**Alternatives**

Other alternatives to compare with the native slice and Lodash chunk approaches include:

* Using other array manipulation functions, such as `Array.prototype.slice()` with a custom loop or using `Array.prototype.map()`.
* Implementing custom algorithms for dividing an array into chunks.
* Using different libraries or frameworks that provide similar functionality, such as Ramda or Lisk.
* Testing the performance of the input array's data structure and compression algorithms.

Keep in mind that these alternatives may not be directly comparable to the native `Array.prototype.slice()` method or the Lodash `_chunk()` function, as they may have different performance characteristics or use cases.

Related benchmarks:

native-slice-vs-chunk (version: 0)

Comparing performance of: Native slice vs lodash chunk

Created: 4 years ago by: Guest

Jump to the latest result

Native slice

lodash chunk

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):