Benchmark: flatMap vs reduce flattern array

Script Preparation code:

var arr = Array(10_000).fill([1, 2])

Tests:

reduce with concat
arr.reduce((acc, x) => acc.concat(x), [])
flatMap
arr.flatMap(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:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36 Edg/128.0.0.0

Browser/OS: Chrome 128 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
reduce with concat	62.2 Ops/sec
flatMap	4111.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark test and explain what's being tested, compared, and discussed.

**Benchmark Definition**

The first step is to understand what's being measured. The benchmark definition json provides two script preparation codes:

1. `arr.reduce((acc, x) => acc.concat(x), [])`
2. `arr.flatMap(x => x)`

These two scripts are designed to process an array of 10,000 elements, where each element is an array containing two elements: `[1, 2]`.

**What's being tested?**

The test case measures the performance difference between using `reduce` with `concat` and `flatMap`. In JavaScript, both methods can be used to flatten arrays, but they work differently.

**Options compared**

Two options are being compared:

1. **Using `reduce` with `concat`:**
	* The `reduce` method applies a callback function to each element in the array, reducing it to a single value.
	* In this case, the callback function concatenates the elements of the inner array (`[1, 2]`) to the accumulator (`acc`).
	* The `concat` method creates a new array by copying the elements from one or more arrays.
	* This approach can be slower because it involves creating a new array on each iteration.
2. **Using `flatMap`:**
	* The `flatMap` method applies a callback function to each element in the array, returning an array of the results.
	* In this case, the callback function simply returns the inner array (`[1, 2]`) without modifying it.
	* This approach is often faster because it avoids creating new arrays.

**Pros and Cons**

Here are some pros and cons for each approach:

**Using `reduce` with `concat`:**

Pros:

* More control over the processing of elements
* Can be more flexible

Cons:

* Involves creating a new array on each iteration, which can be slow
* May consume more memory

**Using `flatMap`:**

Pros:

* Often faster due to reduced memory allocation and copying
* Simplifies code by avoiding explicit concatenation

Cons:

* Less control over the processing of elements
* May not be suitable for all use cases where explicit flattening is required

**Other considerations**

The benchmark also considers the impact of the JavaScript engine, browser, device platform, operating system, and number of executions per second.

**Library and Special JS Features**

There are no libraries mentioned in the provided code snippet. However, it's worth noting that some libraries like Lodash provide `flatMap` functionality as a utility function.

If special JS features or syntax were used, please let me know, and I'll be happy to explain them.

**Alternatives**

For this specific benchmark test, there are two alternatives:

1. **Using `map` instead of `reduce`:**
	* The `map` method applies a callback function to each element in the array, returning an array of results.
	* This approach is similar to using `flatMap`, but it's not directly comparable because it doesn't flatten the inner arrays.
2. **Using other flattening methods:**
	* Other methods like `forEach`, `for...of` loops, or custom functions might also be used for flattening arrays.

Keep in mind that these alternatives may not provide a direct comparison to the `reduce` with `concat` and `flatMap` approaches.

I hope this explanation helps!

Related benchmarks:

flatMap vs reduce flattern array (version: 0)

Comparing performance of: reduce with concat vs flatMap

Created: one year ago by: Guest

Jump to the latest result

reduce with concat

flatMap

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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