Benchmark: lodash groupBy vs filter 100k v1

HTML Preparation code:

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

Script Preparation code:

var max2 = 100000;

var data = [];
for (var i = 0; i <= max2; i++) {
  data.push({ id: i, name: i < 50000 ? 'first' : 'second' });
}

Tests:

Lodash groupBy
_.groupBy(data, 'name')
Lodash filter
_.filter(data, ({ name}) => name === 'second')

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash groupBy
Lodash filter

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/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Windows

View result in a separate tab

Test name	Executions per second
Lodash groupBy	448.1 Ops/sec
Lodash filter	1127.2 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmarking test cases and explain what's being tested, the different approaches compared, their pros and cons, and other considerations.

**Benchmark Definition**

The benchmark definition is provided in two parts:

1. **Script Preparation Code**: This code generates a large dataset of 100,000 objects with an `id` property and a `name` property that alternates between 'first' and 'second'. The purpose of this script is to create a large array for the subsequent tests.
2. **Html Preparation Code**: This code includes a reference to the Lodash library (version 4.17.5), which will be used in the test cases.

**Individual Test Cases**

There are two individual test cases:

1. **Lodash groupBy**: This test case uses the `_.groupBy` function from the Lodash library to group the dataset by the `name` property.
2. **Lodash filter**: This test case uses the `_.filter` function from the Lodash library to filter the dataset based on a condition that matches 'second' in the `name` property.

**Libraries and Features**

In this benchmark, the following libraries are used:

* Lodash (version 4.17.5): A utility library for functional programming in JavaScript.
	+ Purpose: Provides various functions for data manipulation, such as grouping, filtering, mapping, etc.

The test cases do not use any special JavaScript features or syntax beyond what is typically available in modern browsers.

**Approaches Compared**

The two approaches being compared are:

1. **Lodash groupBy**: This approach groups the dataset by the `name` property using the `_.groupBy` function.
2. **Lodash filter**: This approach filters the dataset based on a condition that matches 'second' in the `name` property using the `_.filter` function.

**Pros and Cons**

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

1. **Lodash groupBy**:
	* Pros: Efficient grouping, can handle large datasets.
	* Cons: Requires creating a new data structure (an object) to store the grouped results, which may incur additional memory overhead.
2. **Lodash filter**:
	* Pros: More straightforward and efficient filtering, as it only needs to iterate over the original dataset once.
	* Cons: May be slower for large datasets due to the need to create a new array with filtered elements.

**Other Considerations**

When choosing between these approaches, consider the specific requirements of your use case:

* If you need to perform complex grouping operations and are willing to pay memory overhead, `_.groupBy` might be a better choice.
* If you need a simple filtering operation that doesn't require creating a new data structure, `.filter` might be more suitable.

**Alternatives**

Other alternatives for achieving similar results could include:

1. Using the native `Array.prototype.reduce()` method instead of `_.groupBy`.
2. Implementing custom grouping and filtering functions using plain JavaScript.
3. Using other libraries or frameworks that provide similar functionality to Lodash, such as Moment.js for date manipulation.

Keep in mind that each approach has its trade-offs in terms of performance, memory usage, and complexity.

Related benchmarks:

lodash groupBy vs filter 100k v1 (version: 0)

Comparing performance of: Lodash groupBy vs Lodash filter

Created: 3 years ago by: Registered User

Jump to the latest result

Lodash groupBy

Lodash filter

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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