Benchmark: map vs reduce concat

Script Preparation code:

function generateTestArray() {
    const result = [];
    for (let i = 0; i < 10000; ++i) {
        result.push(i);
    }
    return result;
}

Tests:

map
const testArray = generateTestArray() testArray.map(i => ({i}))
reduce concat
const testArray = generateTestArray() testArray.reduce((acc, i) => acc.concat({i}), [])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
reduce concat

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Measuring JavaScript performance is crucial in today's web development landscape. Let's break down the provided benchmark definition and test cases to understand what's being tested, compared, and their pros and cons.

**Benchmark Definition:**

The benchmark tests two different approaches for manipulating an array:

1. `map`: This method creates a new array by executing a provided function on each element of the original array.
2. `reduce concat`: This approach uses the `reduce` method to accumulate elements in an accumulator array, which is then returned as the result.

**Script Preparation Code:**

The script preparation code defines a helper function `generateTestArray()` that creates an array of 10,000 integers. The test cases use this function to create a large array for testing.

```javascript
function generateTestArray() {
    const result = [];
    for (let i = 0; i < 10000; ++i) {
        result.push(i);
    }
    return result;
}
```

**Html Preparation Code:**

The html preparation code is empty in this benchmark definition, which means no HTML-related setup or teardown is required.

**Individual Test Cases:**

There are two test cases:

1. **map**: This test case creates a new array by mapping over the generated test array using an arrow function that returns an object with a single property `i`.
```javascript
const testArray = generateTestArray();
testArray.map(i => ({ i }));
```

2. **reduce concat**: This test case uses the `reduce` method to accumulate elements in an accumulator array, which is then returned as the result.
```javascript
const testArray = generateTestArray();
testArray.reduce((acc, i) => acc.concat({ i }), []);
```

**Library Used:**

The `map()` and `reduce()` methods are part of the built-in JavaScript Array prototype. These methods do not rely on any external libraries.

**Special JS Features/Syntax:**

None mentioned in this benchmark definition.

**Options Compared:**

Two approaches are being compared:

1. **map**: Creates a new array by executing a provided function on each element.
2. **reduce concat**: Uses the `reduce` method to accumulate elements in an accumulator array.

**Pros and Cons of Each Approach:**

1. **map**:
	* Pros:
		+ Creates a new array, which can be beneficial for performance when dealing with large datasets.
		+ Allows for easy iteration over the resulting array.
	* Cons:
		+ Creates unnecessary memory allocations and copies.
2. **reduce concat**:
	* Pros:
		+ Returns an accumulator array that can be further processed.
		+ Can be more memory-efficient than creating a new array using `map`.
	* Cons:
		+ Requires careful handling of the accumulator array to avoid overflows or incorrect results.

**Other Considerations:**

When deciding between these two approaches, consider the specific requirements of your application:

* If you need to process the resulting array immediately and don't care about memory allocation, `map` might be a better choice.
* If you need to accumulate elements in an accumulator array for further processing or want to avoid unnecessary memory allocations, `reduce concat` might be a better fit.

**Alternatives:**

If you're looking for alternative approaches, consider:

1. Using other methods like `forEach()`, `filter()`, or `slice()` to manipulate arrays.
2. Utilizing libraries like Lodash or Ramda for functional programming utilities.
3. Implementing custom array manipulation functions using low-level JavaScript operations.

Keep in mind that the choice of approach depends on your specific use case and performance requirements.

Latest run results:

Run details: (Test run date: 9 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36

Browser/OS: Chrome 121 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
map	22010.9 Ops/sec
reduce concat	7.7 Ops/sec

Related benchmarks:

map vs reduce concat (version: 0)

Comparing performance of: map vs reduce concat

Created: one year ago by: Guest

Jump to the latest result

map

reduce concat

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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