Benchmark: my filter.map vs flatmap vs reduce

Script Preparation code:

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

Tests:

filter.map
arr.filter(x => x % 12 && x % 5 && x % 3).map(x => x/100)
flatmap
arr.flatMap(x => x % 12 && x % 5 && x % 3 ? x/100 : [])
reduce
arr.reduce((newArray, x) => { if (x % 12 && x % 5 && x % 3) { newArray.push(x / 100) } return newArray }, [])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter.map
flatmap
reduce

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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**Overview**

The provided JSON represents a JavaScript microbenchmarking test case, where three different approaches are compared: `filter.map`, `flatMap`, and `reduce`. The goal of this benchmark is to measure the performance differences between these three methods for filtering and transforming an array.

**Test Setup**

The test setup creates an array `arr` with 100,000 elements using a while loop. Each element is assigned a value based on a condition (`x % 12 && x % 5 && x % 3`). The arrays are then manipulated using the three different approaches: filtering and mapping with `filter.map`, flat mapping with `flatMap`, and reducing.

**Options Compared**

The three options compared are:

1. **Filtering and Mapping with `filter`**: This approach uses the `filter` method to create a new array with elements that pass the condition (`x % 12 && x % 5 && x % 3`), followed by mapping each element using the expression `(x/100)`.
2. **Flat Mapping with `flatMap`**: This approach uses the `flatMap` method, which is an alias for `Array.prototype.flatMap`, to create a new array with elements that pass the condition (`x % 12 && x % 5 && x % 3`) and then transform each element.
3. **Reducing with `reduce`**: This approach uses the `reduce` method to iterate over the array, creating a new array with elements that pass the condition (`x % 12 && x % 5 && x % 3`) and transforming each element.

**Pros and Cons**

Here are some pros and cons of each approach:

* **Filtering and Mapping with `filter`**:
	+ Pros: This approach is more concise and expressive than flat mapping or reducing.
	+ Cons: Filtering and then mapping can lead to slower performance compared to other approaches, especially for large arrays.
* **Flat Mapping with `flatMap`**:
	+ Pros: Flat mapping can be faster than filtering and mapping because it avoids the overhead of creating a new array.
	+ Cons: The syntax can be less readable than other approaches, making it harder to understand what's happening.
* **Reducing with `reduce`**:
	+ Pros: Reducing can be more efficient for large arrays because it only iterates over each element once.
	+ Cons: The syntax can be more verbose and may require additional logic to handle edge cases.

**Library/Function**

The library used in this benchmark is the JavaScript Array prototype methods (`filter`, `flatMap`, `reduce`). These functions are built-in and don't require any external libraries or dependencies.

**Special JS Feature/Syntax**

This benchmark does not use any special JavaScript features or syntax that's specific to a particular browser or version. The code should work across most modern browsers and JavaScript environments.

**Alternatives**

Other alternatives for filtering and transforming arrays include:

* Using `Array.prototype.forEach` with an arrow function
* Using a custom loop or recursive function
* Using a library like Lodash or Ramda, which provide additional utility functions for array manipulation

However, the benchmarking results will likely be specific to the chosen approach and may not generalize well across other alternatives.

Related benchmarks:

my filter.map vs flatmap vs reduce (version: 0)

Comparing performance of: filter.map vs flatmap vs reduce

Created: 3 years ago by: Guest

Jump to the latest result

filter.map

flatmap

reduce

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):