Benchmark: Flatmaps with native (large array)

Script Preparation code:

var arr = Array(1000).fill().map(el => Array(10).fill(1));

Tests:

flatMap Concat
const flatMap = (array) => { return [].concat(...array) } flatMap(arr);
flatMap reduce
const flatMap = (array) => { return array.reduce((acc, val) => acc.concat(val)); } flatMap(arr);
flatMap native
const flatMap = (array) => { return array.flatMap(i => i); } flatMap(arr);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
flatMap Concat
flatMap reduce
flatMap native

Fastest: N/A

Slowest: N/A

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

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**Overview of the Benchmark**

The provided benchmark measures the performance of different JavaScript approaches for flattening an array of arrays, specifically for native (i.e., without using any libraries) and two implementation-specific methods.

**Script Preparation Code**

The script preparation code creates a large array `arr` with 1000 sub-arrays, each containing 10 elements. This array will be used as input for the benchmark.

```javascript
var arr = Array(1000).fill().map(el => Array(10).fill(1));
```

**Benchmark Definition**

The benchmark definition consists of three test cases:

1. **flatMap Concat**: Uses the `concat` method to flatten the array.
2. **flatMap reduce**: Uses the `reduce` method with an accumulator function that concatenates elements.
3. **flatMap native**: Uses the `flatMap` method (introduced in ECMAScript 2019) to flatten the array.

Each test case is defined as a JavaScript function that takes the input array `arr` and performs the flattening operation.

**Library Usage**

None of the benchmark definitions uses any external libraries. The implementation-specific methods are built-in to the JavaScript language.

**Special JS Features/Syntax**

The only special feature used in this benchmark is the `flatMap` method, which was introduced in ECMAScript 2019. This method is designed to flatten arrays and improve performance compared to using `concat`.

**Options Compared**

The three test cases compare the following options:

1. **Native implementation**: Using the built-in `flatMap` method.
2. **Concat-based implementation**: Using the `concat` method to flatten the array.

Both implementations have their own strengths and weaknesses, which are discussed below.

**Pros and Cons of Each Approach**

1. **Native implementation (flatMap)**:
	* Pros: Native performance, concise code.
	* Cons: May not be supported in older browsers or environments that don't implement the `flatMap` method.
2. **Concat-based implementation**:
	* Pros: Widely supported across browsers and environments, no dependence on a specific feature.
	* Cons: More verbose code, potentially slower performance due to repeated concatenations.

**Other Considerations**

When choosing between these approaches, consider the following factors:

1. **Browser support**: If you need to support older browsers or environments that don't implement `flatMap`, the concat-based implementation may be a better choice.
2. **Code readability and maintainability**: The native implementation is often more concise and easier to read, while the concat-based implementation can make your code more verbose.
3. **Performance**: While both implementations have their own performance characteristics, the native implementation tends to be faster due to its native nature.

**Alternatives**

If you're looking for alternative approaches or want to explore different flattening methods, consider the following options:

1. **Array.prototype.flat()**: A more modern alternative to `flatMap`, introduced in ECMAScript 2019.
2. **Lodash's `flatten()` function**: A popular utility library that provides a convenient and flexible way to flatten arrays.
3. **Manual concatenation**: You can write your own custom implementation using manual concatenations, but this approach is often less efficient and more prone to errors.

Keep in mind that the choice of flattening method ultimately depends on your specific use case, performance requirements, and the trade-offs you're willing to make between code readability, maintainability, and performance.

Related benchmarks:

Flatmaps with native (large array) (version: 0)

Comparing performance of: flatMap Concat vs flatMap reduce vs flatMap native

Created: 5 years ago by: Guest

Jump to the latest result

flatMap Concat

flatMap reduce

flatMap native

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):