Benchmark: for i versus map

Tests:

for i
const array1 = [2, 4, 6, 8, 10]; const array2 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]; const filteredArray2 = []; for (let i = 0; i < array2.length; i++) { if (array1.includes(array2[i])) { filteredArray2.push(array2[i]); } } const orderedArray2 = []; for (let i = 0; i < array1.length; i++) { for (let j = 0; j < filteredArray2.length; j++) { if (array1[i] === filteredArray2[j]) { orderedArray2.push(filteredArray2[j]); break; } } } console.log(orderedArray2);
filter and map
const array1 = [2, 4, 6, 8, 10]; const array2 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]; const filteredArray2 = array2.filter(value => array1.includes(value)); const orderedArray2 = array1.map(value => filteredArray2.find(item => item === value)); console.log(orderedArray2);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for i
filter and map

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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Measuring the performance of JavaScript code is crucial in understanding how different approaches can affect execution speed and efficiency.

**Benchmark Definition**

The benchmark being tested here compares two approaches for filtering an array `array2` based on its presence in another array `array1`. The first approach uses a traditional `for` loop, while the second approach leverages built-in JavaScript methods: `filter()` and `map()`.

**Options Compared**

There are three options being compared:

1. **Traditional For Loop**: This approach uses an explicit `for` loop to iterate through both arrays, checking for presence using `includes()`. It requires manual indexing and looping.
2. **Filter Method**: This approach utilizes the `filter()` method, which creates a new array with all elements that pass a test implemented by a provided function.
3. **Map Method with Find**: This approach uses the `map()` method to create a new array of values from an existing array, followed by the `find()` method to locate the corresponding value in another array.

**Pros and Cons**

Here's a brief analysis of each approach:

1. **Traditional For Loop**:
	* Pros: Easy to understand, control over indexing.
	* Cons: Verbose, may lead to errors due to manual looping.
2. **Filter Method**:
	* Pros: Concise, efficient, and often faster.
	* Cons: May not be as intuitive for complex filtering scenarios.
3. **Map Method with Find**:
	* Pros: Elegant and concise, leverages built-in methods.
	* Cons: Less control over indexing and potential performance overhead due to `find()`.

**Library Usage**

In the provided benchmark definition, there are no explicit library references. However, JavaScript's built-in array methods (`filter()`, `map()`, `includes()`) serve a similar purpose.

**Special JS Feature/Syntax**

There is no special JavaScript feature or syntax being tested in this benchmark. The focus is on comparing different approaches to filtering arrays.

**Other Alternatives**

If you're looking for alternative approaches, consider:

1. **Array.prototype.every()` and `Array.prototype.some()`: These methods can be used for more complex filtering scenarios.
2. **Arrow functions**: Using arrow functions with `filter()` and `map()` can provide a concise solution for simple transformations.
3. **Spreadsheets-like libraries (e.g., Google Sheets API)**: If you're interested in leveraging spreadsheet-like functionality, consider using dedicated libraries like the Google Sheets API.

When working with JavaScript performance benchmarks, keep in mind that:

* Microbenchmarks are essential for understanding performance differences between tiny code snippets.
* Real-world applications often involve larger, more complex scenarios.
* Benchmarking results may vary depending on the specific use case and hardware configuration.

Related benchmarks:

for i versus map (version: 0)

Comparing performance of: for i vs filter and map

Created: 2 years ago by: Guest

Jump to the latest result

for i

filter and map

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):