Benchmark: Lodash.js vs Native map test

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

var max1 = 1000; // 100,000 (100 Thousand)
var max2 = 10000000; // 10,000,000 (10 Million)
var max3 = 100000000; // 100,000,000 (100 Million)

var arr1 = [];
for (var i = 0; i <= max1; i++) { arr1.push(i); }

var arr2 = [];
// for (var i = 0; i <= max2; i++) { arr2.push(i); }

var arr3 = [];
//for (var i = 0; i <= max3; i++) { arr3.push(i); }

Tests:

Native
arr1.map(function (element, index) { element = element*2; });
Lodash.js filter
_.map(arr1, function (element, index) { element = element*2; });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native
Lodash.js filter

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and its explanations into understandable parts.

**Benchmark Definition JSON**

The provided benchmark definition consists of two main parts: `Script Preparation Code` and `Html Preparation Code`. The latter includes a script tag referencing the Lodash.js library, which is used in one of the test cases.

**Script Preparation Code**

This section creates three arrays (`arr1`, `arr2`, and `arr3`) with increasing size (1000, 10,000,000, and 100,000,000 elements respectively) using a for loop. The purpose of creating these large arrays is to simulate a scenario where the browser needs to map over a large dataset.

**Html Preparation Code**

This section includes a script tag that loads the Lodash.js library version 4.17.4 from a CDN.

**Test Cases**

There are two individual test cases:

1. **Native**: This test case uses native JavaScript's `map()` function without any additional libraries.
2. **Lodash.js filter**: This test case uses Lodash.js' `_map()` function, which is similar to the native `map()` function but provides additional features and optimizations.

**Options Compared**

The two test cases compare:

* Native JavaScript's `map()` function vs Lodash.js' `_map()` function
* Performance differences between using a library (Lodash.js) and native JavaScript

**Pros and Cons**

**Native JavaScript's `map()` function:**

Pros:

* Lightweight, no additional dependencies
* Fast performance

Cons:

* Limited functionality compared to Lodash.js
* May not provide optimizations for large datasets

**Lodash.js' `_map()` function:**

Pros:

* Provides additional features and optimizations for mapping over large datasets
* Can be more efficient than native `map()` function in some cases

Cons:

* Adds an additional dependency (the Lodash.js library)
* May have a slight performance overhead due to the library's complexity

**Other Considerations**

* The benchmark uses a simple operation (squaring elements) which might not accurately represent real-world use cases.
* The benchmark size is relatively small compared to what might be encountered in a production environment.
* The test cases do not account for caching, memoization, or other optimization techniques that might improve performance in certain scenarios.

**Library: Lodash.js**

Lodash.js is a popular utility library for JavaScript. Its `_map()` function provides a convenient and efficient way to map over arrays. In this benchmark, it's used to compare the performance of native JavaScript's `map()` function against its own implementation.

If you're interested in exploring alternative approaches, here are some options:

* **Using V8's built-in mapping functions**: Modern browsers like Chrome use V8 as their engine, which has built-in support for various mapping functions. You could explore using these built-in functions to see if they outperform native JavaScript's `map()` function.
* **Optimized array libraries**: There are optimized array libraries available that can provide better performance than Lodash.js or native JavaScript's `map()` function. Examples include Array.prototype.map() from the ECMAScript specification, as well as specialized libraries like FastArray and ArrayProto.
* **Custom implementation**: Depending on your specific use case, you might be able to implement a custom mapping algorithm that outperforms both native JavaScript's `map()` function and Lodash.js' `_map()` function.

Related benchmarks:

Lodash.js vs Native map test (version: 0)

Comparing performance of: Native vs Lodash.js filter

Created: 7 years ago by: Guest

Jump to the latest result

Native

Lodash.js filter

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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