Benchmark: Map and Filter vs forEach test

Script Preparation code:

var jobIds = [1, 2, 3, 4, 5]
var jobs = {
  1: { status: 2 },
  2: { status: 1 },
  3: { status: 3 },
  4: { status: 2 },
  5: { status: 3 }
}

Tests:

map and filter
var activeJobs = jobIds.map(id => jobs[id]).filter(job => job.status !== 3)
forEach
var activeJobs = [] jobIds.forEach(id => { if (jobs[id].status !== 3) activeJobs.push(jobs[id]) })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map and filter
forEach

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark and explain what is being tested.

**Benchmark Overview**

The benchmark measures the performance difference between two approaches to filter an array of job IDs and retrieve the corresponding job objects:

1. `map` and `filter`: This approach uses the `map()` method to create a new array with the filtered elements, while using the `filter()` method to remove the unwanted elements.
2. `forEach`: This approach uses the `forEach()` method to iterate over the array of job IDs, and then pushes the filtered job objects into a separate array.

**Options Compared**

The two approaches being compared are:

* `map` and `filter`
* `forEach`

**Pros and Cons**

Here's a brief overview of each approach:

1. **`map` and `filter`**:
	* Pros:
		+ Can be more readable and concise, especially for small datasets.
		+ Can take advantage of browser optimizations, such as parallel execution.
	* Cons:
		+ May require more memory allocation and garbage collection, which can impact performance.
		+ Can be slower due to the creation of a new array.
2. **`forEach`**:
	* Pros:
		+ Typically faster and more efficient, especially for large datasets.
		+ Does not create a new array, which reduces memory allocation and garbage collection overhead.
	* Cons:
		+ May require more code to achieve the same result as `map` and `filter`.
		+ Can be less readable due to the need for explicit iteration.

**Library and Special JS Feature**

There is no library being used in this benchmark. However, it's worth noting that both approaches use a modern JavaScript feature: destructuring assignment (`id => jobs[id]`). This syntax was introduced in ECMAScript 2015 (ES6) and provides a concise way to extract values from objects.

**Other Considerations**

When writing benchmarks like this one, several factors can impact performance:

* **Dataset size**: Larger datasets typically require more memory allocation and garbage collection, which can slow down the execution.
* **Browser optimizations**: Modern browsers have various optimization techniques, such as parallel execution or caching, that can affect performance. The `map` and `filter` approach may take advantage of these optimizations.
* **Cache locality**: The order in which elements are accessed in memory can impact performance. The `forEach` approach typically iterates over the array in a linear fashion, while the `map` and `filter` approach creates a new array with filtered elements.

**Alternatives**

If you're looking for alternative approaches or optimizations, consider the following:

* **Using `Array.prototype.reduce()`**: Instead of using `map` and `filter`, you can use `reduce()` to accumulate the filtered elements into a single array.
* **Using `Array.prototype.some()`**: You can use `some()` instead of `filter()` to check if any element in the array meets a condition.

Related benchmarks:

Map and Filter vs forEach test (version: 0)

Comparing performance of: map and filter vs forEach

Created: 5 years ago by: Guest

Jump to the latest result

map and filter

forEach

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):