Benchmark: flatMap() vs filter().map()asdsadsa

Script Preparation code:

var arr = [];
var i = 0;

while (i <= 30) arr[i] = i++;

Tests:

filter().map()
arr.filter(x => x % 3).map(x => x/100)
flatMap()
arr.flatMap(x => x % 3 ? x/100 : [])

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

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

LLMs can make mistakes. Check important info.

Let's break down what is being tested on the provided JSON benchmark.

**Benchmark Definition**

The benchmark defines two different approaches to transforming an array: `flatMap()` vs `filter() .map()`.

**Options Compared**

The options being compared are:

1. **flatMap()**: a method that applies a callback function to each element of the array, returning a new array with the results.
2. **filter() .map()**: a two-step approach where `filter()` removes elements that don't meet a certain condition, and then `map()` transforms the remaining elements.

**Pros and Cons**

**flatMap():**

Pros:

* More concise and expressive code
* Can be more efficient for large arrays since it avoids creating intermediate arrays

Cons:

* May not work as expected if the callback function returns an empty array or throws an error
* Can be less readable for complex transformations

**filter() .map():**

Pros:

* Easier to understand and debug, especially for complex transformations
* More forgiving of errors or unexpected values in the input array

Cons:

* More verbose code
* May create intermediate arrays, which can impact performance for very large inputs

**Other Considerations**

* The benchmark uses a simple array `arr` generated using a while loop, which is not representative of real-world scenarios. A more realistic approach would use an array literal or an external data source.
* The callback functions used in the benchmark are simplified and do not reflect real-world edge cases.

**Library Usage**

There is no explicit library mentioned in the benchmark definition or script preparation code. However, `flatMap()` is a built-in method of the Array prototype in JavaScript, whereas `filter() .map()` is a combination of two separate methods.

**Special JS Feature/Syntax**

The benchmark does not use any special JS feature or syntax beyond the standard `flatMap()` and `filter() .map()` approaches. However, it's worth noting that some browsers may have optimizations for certain array operations, which could affect the results of this benchmark.

**Alternatives**

Other alternatives to compare in a similar benchmark might include:

* Using `reduce()` instead of `flatMap()` or `filter() .map()`
* Comparing performance with different data structures, such as objects or sets
* Evaluating the impact of parallel processing on array transformations
* Benchmarking the performance of different JavaScript engines or interpreters

In conclusion, this benchmark provides a straightforward comparison between two common array transformation approaches in JavaScript. While it has some limitations (e.g., simplified input and callback functions), it can still serve as a useful tool for evaluating the performance differences between `flatMap()` and `filter() .map()`.

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 17_0 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/17.0 Mobile/15E148 Safari/604.1

Browser/OS: Mobile Safari 17 on iOS 17.0

View result in a separate tab

Test name	Executions per second
filter().map()	1618417.1 Ops/sec
flatMap()	3140074.8 Ops/sec

Related benchmarks:

flatMap() vs filter().map()asdsadsa (version: 0)

flatMap vs filter map

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

Created: one year ago by: Guest

Jump to the latest result

filter().map()

flatMap()

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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