Benchmark: Benchmark: flatMap vs reduce vs while 2

Script Preparation code:

var n = 1000

Tests:

flatMap
[...Array(n)].flatMap((x,i) => [++i,i++])
reduce
[...Array(n).keys()].reduce((acc, cur) => { acc.push(++cur, cur++); return acc; }, [])
while
let res = [], i=0; while(n>i++) res.push(i, i);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
flatMap
reduce
while

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

**Overview of the Benchmark**

The provided JSON represents a JavaScript microbenchmark test case, specifically designed to compare the performance of three different methods: `flatMap`, `reduce`, and `while`. The test is designed to measure which method is fastest for iterating over an array and performing some operation.

**Test Case Options Compared**

1. **`flatMap`**: This method returns a new array with the results of applying the provided function on every element in this array.
2. **`reduce`**: This method applies a function against an accumulator and each element in the array (from left to right) to reduce it to a single value.
3. **`while`**: This loop iterates over the array using a counter variable, which is incremented on each iteration.

**Pros and Cons of Each Approach**

1. **`flatMap`**:
	* Pros: Can be more efficient than `reduce` because it avoids creating an intermediate accumulator array.
	* Cons: Requires JavaScript 2019+ (ECMAScript) features (`flatMap` was introduced in ECMAScript 2019).
2. **`reduce`**:
	* Pros: Widely supported and has been around since ECMAScript 5 (2009), making it a good fallback option.
	* Cons: Creates an intermediate accumulator array, which can lead to performance issues for very large datasets.
3. **`while`**:
	* Pros: Low overhead, as it only uses basic loop constructs.
	* Cons: Not designed for iterative algorithms like this one; can be slower due to its nature.

**Library Used (if applicable)**

None of the provided test cases use a library specifically, but `flatMap` requires ECMAScript 2019+ features, which is built into modern JavaScript engines. If you're using an older engine or want to ensure compatibility with older browsers, you may need to polyfill `flatMap`.

**Special JS Features or Syntax**

None of the provided test cases use special JavaScript features or syntax beyond what's available in ECMAScript 2019+ (for `flatMap`).

**Other Alternatives**

For similar performance comparisons:

* Consider using a benchmarking library like Benchmark.js, which can simplify setup and provide more features.
* For `reduce`, you could also explore other alternatives like `forEach()` or creating a custom loop.

To further optimize your code, consider factors like:

* Array size: Larger arrays may benefit from optimized iterative algorithms.
* Data distribution: Uniformly distributed data might favor one method over another.
* Engine-specific optimizations: Some engines have specific optimizations for certain methods (e.g., WebKit's optimized `reduce` implementation).

Keep in mind that these are general suggestions and the best approach depends on your specific use case.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36 Edg/101.0.1210.47

Browser/OS: Chrome 101 on Windows

View result in a separate tab

Test name	Executions per second
flatMap	2366.5 Ops/sec
reduce	31136.8 Ops/sec
while	13328.6 Ops/sec

Related benchmarks:

Benchmark: flatMap vs reduce vs while 2 (version: 0)

Comparing performance of: flatMap vs reduce vs while

Created: 2 years ago by: Guest

Jump to the latest result

flatMap

reduce

while

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):