Benchmark: flatMap vs filter&map

Script Preparation code:

var arr = [];
let i = 0;

while (i++ <= 10000) {
    arr[i] = {
        id: i,
        name: `id-${i}`
    };
}

Tests:

filter().map()
arr.filter(obj => obj.id % 3).map(obj => obj.name)
arr.flatMap()
arr.flatMap(obj => obj.id % 3 ? obj.name : [])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter().map()
arr.flatMap()

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 dive into the explanation of the benchmark and its options.

**Benchmark Description**

The benchmark is designed to compare the performance of two different methods for mapping over an array in JavaScript: `filter()` followed by `map()`, and `flatMap()`. The test data consists of a large array (`arr`) with 10,000 elements, each containing an `id` and a `name`.

**Options Compared**

There are two options being compared:

1. **Filter() + Map()**: This approach involves filtering the array to only include elements that meet a certain condition (in this case, `obj.id % 3 == 0`) and then mapping over the resulting array to transform each element into its `name` property.
2. **FlatMap()**: This approach involves using the `flatMap()` method to directly map over the entire array and transform each element into its `name` property.

**Pros and Cons of Each Approach**

1. **Filter() + Map()**:
	* Pros:
		+ Can be more readable and easier to understand for developers familiar with the `filter()` and `map()` methods.
		+ Allows for a clear separation of concerns between filtering and mapping.
	* Cons:
		+ Involves an additional iteration over the array, which can lead to performance overhead.
		+ May not be as efficient as using `flatMap()` directly on large datasets.
2. **FlatMap()**:
	* Pros:
		+ Can be more efficient than using `filter()` and then `map()`, as it eliminates the need for an additional iteration over the array.
		+ Can lead to better cache locality, which can improve performance in some cases.
	* Cons:
		+ May be less readable or more difficult to understand for developers unfamiliar with the `flatMap()` method.

**Library and Purpose**

There is no external library being used in this benchmark. However, it's worth noting that `flatMap()` was introduced in ECMAScript 2019 (ES2020) as a replacement for the older `map()` method when working with arrays of arrays or other iterable objects.

**Special JavaScript Feature/Syntax**

The benchmark uses the following special JavaScript feature:

* **Template literals**: The `name` property is assigned using template literals (`obj.name = \`id-\${i}\``), which were introduced in ECMAScript 2015 (ES6) for creating string templates with embedded expressions.

**Other Alternatives**

If you're looking for alternative approaches to mapping over an array, you might consider using:

* **Reduce()**: Instead of using `map()` or `flatMap()`, you could use the `reduce()` method to accumulate a new array containing the transformed elements.
* **Array.prototype.forEach()**: While not as efficient as using `map()` or `flatMap()`, you could use the `forEach()` method to iterate over each element in the array and transform it manually.

In general, for most use cases, using `filter()` followed by `map()` or using `flatMap()` directly will be sufficient. However, if you're working with large datasets or require more control over the transformation process, alternative approaches like those mentioned above may be necessary.

Related benchmarks:

flatMap vs filter&map (version: 0)

Comparing performance of: filter().map() vs arr.flatMap()

Created: 4 years ago by: Guest

Jump to the latest result

filter().map()

arr.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):