Benchmark: flatmap vs flat and map

Script Preparation code:

var arr = [];
var i = 0;

while (i <= 1E5) arr[i] = i++;

Tests:

map().flat()
arr.map(x => x/100).flat()
flatMap()
arr.flatMap(x => x/100)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map().flat()
flatMap()

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark JSON and explain what's being tested, compared, and considered.

**Benchmark Definition**
The benchmark is designed to compare the performance of two approaches:

1. `flatMap()`: A method on arrays that returns a new array with the results of applying a provided function to each element.
2. `map().flat()`: A chained method call where `map()` applies a function to each element, and then `.flat()` flattens the resulting array.

**Options Compared**
The benchmark is comparing two options:

* Using `flatMap()` directly on the array
* Chaining `map()` followed by `.flat()` on the result of `map()`

**Pros and Cons**

1. **Using `flatMap()`**: This approach can be more efficient because it avoids creating an intermediate array, which can lead to better memory usage.
	* Pros: Often faster due to reduced memory allocation.
	* Cons: Can be less intuitive for developers who are not familiar with this method.
2. **Chaining `map()` and `.flat()`**: This approach creates an intermediate array that needs to be stored in memory, which can lead to increased memory usage.
	* Pros: More explicit and easier to understand for developers who are familiar with this pattern.
	* Cons: Can be slower due to the additional memory allocation.

**Other Considerations**

The benchmark also considers other factors such as:

* Device platform (Desktop vs. not specified): The results show a difference between Desktop and non-Desktop devices, which might indicate hardware or browser differences affecting performance.
* Operating System: The tests were run on Mac OS X 10.15.7.

**Library and Special JS Feature**
There is no specific library used in this benchmark, but there are some nuances related to the `flatMap()` method:

`flatMap()` was introduced in ECMAScript 2019 (ES2020) as a replacement for `map().reduce()`. This method can be useful when you need to iterate over an array and transform its elements, while also accumulating the results.

**Alternatives**

For this specific benchmark, there aren't many alternatives that would provide meaningful comparisons. However, if you were comparing other methods for transforming arrays, some alternatives might include:

* Using `forEach()` with a callback function
* Creating a new array using `Array.prototype.reduce()`
* Using libraries like Lodash or Ramda for functional programming utilities

Keep in mind that the performance differences between these approaches can be significant depending on the specific use case and dataset size.

Related benchmarks:

flatmap vs flat and map (version: 0)

Comparing performance of: map().flat() vs flatMap()

Created: 3 years ago by: Guest

Jump to the latest result

map().flat()

flatMap()

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):