Benchmark: reduce vs flatMap test2

Script Preparation code:

var arr = new Array(10000).fill([1,2]);

Tests:

reduce
arr.reduce((res,x) => { x.forEach(item => {res.push(item)}) return res; },[]);
flatMap
arr.flatMap(x => x);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce
flatMap

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.106 YaBrowser/21.6.0.1108 Yowser/2.5 Safari/537.36

Browser/OS: Yandex Browser 21 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
reduce	7418.0 Ops/sec
flatMap	297.1 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON data and explain what's being tested.

**Benchmark Definition**

The benchmark is defined by two test cases: `reduce` and `flatMap`. The benchmark compares the performance of these two approaches for flattening an array of arrays.

**Options Compared**

The options compared are:

* `reduce`: A method that applies a callback function to each element in the array, accumulating a result.
* `flatMap`: A method that returns a new array with the results of applying a provided function to each element in the original array.

**Pros and Cons**

**Reduce**

Pros:

* Can be used for transformations that require accumulation of results
* Allows for more control over the transformation process

Cons:

* Can be slower due to the overhead of iterating over each element in the array
* Requires manual iteration over elements, which can lead to code complexity

**FlatMap**

Pros:

* Optimized for transformations that result in a new array structure
* Reduces code complexity by avoiding manual iteration
* Faster execution time compared to `reduce`

Cons:

* Limited control over the transformation process (the provided function must return an iterable)
* Can be less flexible than `reduce` for certain use cases

**Library and Special JS Features**

There is no explicit library mentioned in the benchmark definition. However, `flatMap` uses a method that is part of the ES6+ standard: the spread operator (`...`) or the `Array.prototype.flatMap()` method.

In this case, the `flatMap` test case uses the `flatMap()` method directly on the `arr` array, which is an optimized implementation for modern browsers and engines. The `reduce` test case uses a custom callback function to achieve the same result.

**Other Alternatives**

If you need to flatten an array of arrays in JavaScript, other alternatives include:

* Using a loop with push() or splice()
* Utilizing a library like Lodash (which provides a `flatten()` method)
* Leveraging a transpiler or compiler that supports ECMAScript 6+ features

For this specific benchmark, using `flatMap` is recommended due to its optimized performance and reduced code complexity. However, if you need more control over the transformation process, `reduce` might be a better choice.

Related benchmarks:

reduce vs flatMap test2 (version: 0)

Comparing performance of: reduce vs flatMap

Created: 3 years ago by: Guest

Jump to the latest result

reduce

flatMap

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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