Benchmark: flatMap vs reduce without spread

Script Preparation code:

var arr = Array(10_000).fill(0)

Tests:

reduce with concat
arr.reduce((acc, x) => { acc.push(x); acc.push(x); return acc; }, [])
flatMap
arr.flatMap(x => [x, x])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce with concat
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 explain what's being tested.

**Benchmark Definition**
The benchmark is testing two approaches: using `reduce` with the spread operator (`...`) to concatenate arrays, and using `flatMap` to achieve the same result.

**Options Compared**

1. **Using reduce with concat**: This approach uses the `reduce` method to iterate over the array and concatenate its elements using the `push` method of the accumulator.
2. **Using flatMap**: This approach uses the `flatMap` method, which is a more concise way to flatten an array of arrays into a single array.

**Pros and Cons**

1. **Using reduce with concat**:
	* Pros: explicit control over iteration, can be more readable for complex transformations.
	* Cons: may be slower due to the overhead of pushing elements onto the accumulator array, and can lead to stack overflow errors if the accumulator is too large.
2. **Using flatMap**:
	* Pros: concise and expressive, avoids creating intermediate arrays, and is generally faster than `reduce` with concat.
	* Cons: may be less readable for complex transformations, and can lead to errors if not used correctly.

**Library**
There is no specific library being tested in this benchmark. The functionality is built-in to JavaScript.

**Special JS Features/Syntax**
The benchmark uses the spread operator (`...`) which was introduced in ECMAScript 2015 (ES6). It allows for more concise and expressive array creation.

**Other Considerations**

* The benchmark uses a large array of 10,000 elements, which is likely chosen to produce a significant difference between the two approaches.
* The test runs on multiple executions per second, which gives an idea of the performance difference between the two approaches.
* The benchmark results in different browsers and devices, which provides insight into how these differences affect performance.

**Alternatives**

Other alternatives for achieving this result could include:

1. Using `forEach` with a callback function to iterate over the array and concatenate its elements.
2. Using a `for` loop to iterate over the array and concatenate its elements.
3. Using a library like Lodash, which provides a `compact` function that can be used to flatten arrays.

However, these alternatives are not tested in this benchmark, and the use of `reduce` with concat and `flatMap` is likely chosen for their concise and expressive nature.

Related benchmarks:

flatMap vs reduce without spread (version: 0)

Comparing performance of: reduce with concat vs flatMap

Created: 3 years ago by: Guest

Jump to the latest result

reduce with concat

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):