Benchmark: groupBy vs partition

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 = 25000;

var data = [];
for (var i = 0; i <= max2; i++) { data.push({ id: i, country: 'US'}); }
for (var i = 0; i <= max2; i++) { data.push({ id: i, country: 'MX'}); }
for (var i = 0; i <= max2; i++) { data.push({ id: i, country: 'CA'}); }

Tests:

groupBy
_.groupBy(data, 'country')
partition
_.partition(data, 'country')

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
groupBy
partition

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and analyze what's being tested.

**Benchmark Overview**

The benchmark compares two approaches: `groupBy` and `partition`. Both methods are part of the Lodash library, a popular utility library for JavaScript. The test data consists of an array of objects with `id` and `country` properties, where each country has three different values (`US`, `MX`, and `CA`).

**`groupBy` Method**

The `groupBy` method groups the input array by a specified property (in this case, `country`). It returns an object with the grouped data, where each key is a unique value from the property, and its corresponding value is an array of objects that have that value for the specified property.

**`partition` Method**

The `partition` method splits the input array into two parts: one part contains elements that satisfy a predicate (in this case, an empty string), and another part contains elements that don't. The returned values are two arrays: the first array contains elements for which the predicate is true, and the second array contains elements for which it's false.

**Comparison**

The benchmark compares the execution time of these two methods on the test data. Specifically:

* `groupBy` groups the data by country and returns an object with grouped data.
* `partition` splits the data into two parts based on the country property.

**Pros and Cons**

Here are some general pros and cons for each approach:

* **`groupBy` Method:**
	+ Pros:
		- Groups data in a straightforward way, making it easy to process further.
		- Can be used with various aggregation functions (e.g., `_.reduce`, `_.map`) to perform additional processing.
	+ Cons:
		- May require additional memory allocation and iteration if the resulting object is too large.
* **`partition` Method:**
	+ Pros:
		- Splitting data into two parts can be more efficient in terms of memory usage and iteration.
		- Can be used to create two separate arrays for further processing or analysis.
	+ Cons:
		- May not be suitable for certain use cases where the resulting split needs to be more complex.

**Lodash Library**

Lodash is a popular utility library that provides various functions, including `groupBy` and `partition`. These functions are often used in data processing, filtering, mapping, and reducing. Lodash's goal is to provide a concise way to perform common operations on arrays and objects.

**Special JS Feature/Syntax**

This benchmark doesn't use any special JavaScript features or syntax beyond the standard ES6/ES7 language features supported by Lodash. However, if you're familiar with advanced topics like async/await or modern web performance optimization techniques (e.g., Webpack's tree shaking), understanding these concepts can help in interpreting benchmark results.

**Alternatives**

If you need to group data or split it into partitions, consider the following alternatives:

* For grouping data:
	+ Use `Array.prototype.reduce()` with a custom callback function.
	+ Utilize libraries like Moment.js for date-related grouping or D3.js for complex data visualization and analysis.
* For splitting data:
	+ Employ standard array methods like `Array.prototype.filter()`, `Array.prototype.forEach()`, or `Array.prototype.forEachIndex()`.
	+ Use specialized libraries like D3.js (again) or more lightweight alternatives like Ramda, which provides a similar `partition` function.

For more information on Lodash functions or related techniques, you can explore the official documentation, GitHub repository, or online resources like MDN Web Docs.

Related benchmarks:

groupBy vs partition (version: 0)

Comparing performance of: groupBy vs partition

Created: 3 years ago by: Guest

Jump to the latest result

groupBy

partition

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):