Benchmark: map and join vs reduce small array

Script Preparation code:

var strings = [];
for (var i = 0; i < 5; i++) {
    strings[i] = {
        name: i
    };
}

Tests:

map join
strings.map(s => s.name).join('');
reduce
strings.reduce((a,n) => a+n.name, '');

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map join
reduce

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:139.0) Gecko/20100101 Firefox/139.0

Browser/OS: Firefox 139 on Windows

View result in a separate tab

reduce

15.4M/s

map join

7.0M/s

View exact numbers

Test name	Executions per second
✓ reduce	15,416,443 Ops/sec
map join	7,028,513 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 definition and test cases to understand what's being tested.

**Benchmark Definition**

The website uses a JSON representation of the benchmark, which includes:

1. **Name**: A unique identifier for the benchmark.
2. **Description**: An optional text description of the benchmark.
3. **Script Preparation Code**: A JavaScript code snippet that prepares the input data for the benchmark.
4. **Html Preparation Code**: An optional HTML code snippet used to prepare the environment for the benchmark.

In this case, the Script Preparation Code defines an array `strings` with five elements, each containing a `name` property.

**Individual Test Cases**

The website includes two test cases:

1. **map join**
	* Benchmark Definition: `strings.map(s => s.name).join('')`
	* Purpose: To measure the performance of concatenating an array of strings using the `join()` method and mapping over the array to extract a property.
2. **reduce**
	* Benchmark Definition: `strings.reduce((a,n) => a+n.name, '')`
	* Purpose: To measure the performance of reducing an array of objects to a single string using the `reduce()` method.

**Library**

There is no explicit library mentioned in the benchmark definition. However, both test cases use built-in JavaScript methods (`map()`, `join()`, and `reduce()`), which are part of the ECMAScript standard.

**Special JS Feature or Syntax**

Neither of the test cases uses any special JavaScript features or syntax that would require additional explanation.

**Other Alternatives**

To measure similar performance, alternative benchmarks could be created using different methods, such as:

1. Using a different method to concatenate strings, like `toString()` or template literals.
2. Using a different method to reduce the array of objects, like `every()` or `forEach()`.
3. Adding additional complexity to the input data, such as nested arrays or objects.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **map join**: This approach is simple and straightforward. The `join()` method is efficient for concatenating strings in most browsers.
	* Pros: Easy to implement and maintain.
	* Cons: May not be as efficient as other methods, especially for large arrays or complex string concatenation.
2. **reduce**: This approach can be more efficient than `map join` when working with large arrays or complex data structures.
	* Pros: Can handle larger datasets and more complex data structures.
	* Cons: May require additional setup and configuration.

Ultimately, the choice of benchmarking approach depends on the specific requirements of the test case and the performance characteristics of the target browser.

map and join vs reduce small array (version: 0)

Comparing performance of: `map join vs reduce`

Created: 3 years ago by: Guest

Go to the latest result

map join

reduce

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

map and join vs reduce small array (version: 0)

Comparing performance of: map join vs reduce

Created: 3 years ago by: Guest

Go to the latest result

map join

reduce

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

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Comparing performance of: `map join vs reduce`