Benchmark: flatmap vs filter.map pw

Script Preparation code:

var arr = []
var i = 0;

let getRandomText = () => (Math.random() + 1).toString(36).substring(7);

function getRandomFloat(max) {
  return Math.random() * max;
}

function getRandomBool() {
  return Math.random() > 0.5;
}

while (i <= 1E5) {
 arr.push({
  status: getRandomBool(),
  group: getRandomBool() ? "random" : "test",
      id: i+1,
      name: getRandomText(),
      icon: getRandomText(),
   	imgUrl: getRandomText(),
  someProp: getRandomText(),
   oterProp: getRandomText(),
 })
 i++;
}

Tests:

filter.map
arr.filter(({ group, status }) => status && group === 'eTransfer') .map(({ id, name, imgUrl: iconUrl }) => ({ id, name, iconUrl, }));
flatMap
arr.flatMap(({ group, status, id, name, imgUrl: iconUrl }) => { if (status && group === 'test') { return [{ id, name, iconUrl, }] } else { return []; } })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter.map
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 JSON and benchmark.

**Benchmark Purpose**

The test compares two approaches for filtering and mapping an array in JavaScript:

1. `arr.filter()` followed by `map()`
2. `arr.flatMap()`

These approaches are used to transform the `arr` array, which is populated with random data.

**Options Compared**

The options being compared are:

* **`filter()`**: Removes elements from the array that do not match the provided condition. In this case, it filters out elements where `status` is false or `group` is not 'eTransfer'.
* **`flatMap()`**: Flattens an array of values returned by a callback function into a new one-dimensional array. In this case, it returns only elements where `status` is true and `group` is 'test'.

**Pros and Cons**

Here are some pros and cons of each approach:

* **`filter()` followed by `map()`**:
	+ Pros:
		- More efficient when dealing with large arrays, as it only removes a subset of elements.
		- Can be easier to understand for those familiar with array methods.
	+ Cons:
		- Requires two separate operations (filtering and mapping), which can lead to increased overhead.
* **`flatMap()`**:
	+ Pros:
		- Reduces the number of iterations, as it only iterates over the elements that need to be processed.
		- Can be more efficient for large arrays.
	+ Cons:
		- Less intuitive for those not familiar with array methods.

**Library and Special JS Feature**

There is no specific library mentioned in the benchmark. However, `flatMap()` is a relatively new addition to JavaScript (introduced in ECMAScript 2019), so it may require modern browsers or environments that support it.

**Other Considerations**

* **Performance**: Both approaches have their trade-offs when it comes to performance. `flatMap()` can be more efficient for large arrays, but `filter()` followed by `map()` can be faster for smaller arrays.
* **Code Readability**: The choice between `filter()` followed by `map()` and `flatMap()` depends on personal preference and the specific use case.

**Alternatives**

Other alternatives for filtering and mapping arrays include:

* Using a library like Lodash, which provides `filter` and `map` functions as well as more advanced utility functions.
* Using a more traditional approach with loops and conditional statements (e.g., using `for` loops and nested conditional statements).
* Using other array methods, such as `reduce()` or `forEach()`, depending on the specific use case.

Related benchmarks:

flatmap vs filter.map pw (version: 0)

Comparing performance of: filter.map vs flatMap

Created: 3 years ago by: Guest

Jump to the latest result

filter.map

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):