Benchmark: Array filter vs Set delete

Script Preparation code:

function arrayWithLength(length) {
    return Array(length).fill().map((_, i) => i);
}
var arr10 = arrayWithLength(10);
var arr1000 = arrayWithLength(1000);
var arr1000000 = arrayWithLength(1000000);
var set10 = new Set(arr10);
var set1000 = new Set(arr1000);
var set1000000 = new Set(arr1000000);

Tests:

Filter arr10
arr10.filter(i => i === 5);
Filter set10
set10.delete(5);
Filter arr1000
arr1000.filter(i => i === 500);
Filter set1000
set1000.delete(500);
Filter arr1000000
arr1000000.filter(i => i === 500000);
Filter set1000000
set1000000.delete(500000);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Filter arr10
Filter set10
Filter arr1000
Filter set1000
Filter arr1000000
Filter set1000000

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Filter arr10	12760821.0 Ops/sec
Filter set10	14339590.0 Ops/sec
Filter arr1000	1053713.6 Ops/sec
Filter set1000	13656576.0 Ops/sec
Filter arr1000000	146.1 Ops/sec
Filter set1000000	13733266.0 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Explanation**

The provided benchmark measures the performance of two approaches to filter out elements from an array: using the `filter()` method and deleting individual elements from a `Set` data structure.

**Options Compared**

1. **Array Filter**: The `filter()` method creates a new array with all elements that pass a test implemented by providing a function. This approach modifies the original array.
2. **Set Delete**: Deleting an element from a `Set` removes it from the set, making it more efficient for large datasets.

**Pros and Cons**

* **Array Filter**:
	+ Pros: Easy to implement and understand, works with arrays of any type.
	+ Cons: Creates a new array, which can be memory-intensive for large datasets. The performance is generally slower than using `Set` delete.
* **Set Delete**:
	+ Pros: More efficient for large datasets since it modifies the original set. Faster execution times compared to `Array Filter`.
	+ Cons: Requires a `Set` data structure, which may not be suitable for all use cases (e.g., non-numeric values). The implementation can be less intuitive.

**Library Used**

In this benchmark, the `Set` library is used to create and manipulate sets. Sets are implemented as hash tables in modern JavaScript engines.

**Special JS Feature/Syntax**

None mentioned explicitly, but note that the `filter()` method uses a callback function (e.g., `(i => i === 5)`) which is a common feature of functional programming in JavaScript. The use of arrow functions (`(i => i === 5)`) is also supported.

**Other Alternatives**

For large datasets, other alternatives to `Set` delete could be:

* **Using a custom data structure**, like a balanced binary search tree or a hash table.
* **Parallel processing** techniques, like using multiple CPU cores to process elements in parallel.
* **GPU acceleration**, using libraries that can execute JavaScript on the GPU.

However, these alternatives are typically more complex and may not be suitable for all use cases. The `Set` delete approach is generally a good choice when dealing with large datasets and performance-critical code.

Related benchmarks:

Array filter vs Set delete (version: 0)

Comparing performance of: Filter arr10 vs Filter set10 vs Filter arr1000 vs Filter set1000 vs Filter arr1000000 vs Filter set1000000

Created: 4 years ago by: Guest

Jump to the latest result

Filter arr10

Filter set10

Filter arr1000

Filter set1000

Filter arr1000000

Filter set1000000

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):