Benchmark: filter by indices

Script Preparation code:

var length = 100;
var value = 200;
var sublength = 5;
var list = Array.from({length: length}, () => Math.floor(Math.random() * value));
var indices = Array.from({length: sublength}, () => Math.floor(Math.random() * length));

Tests:

for push
var filtered = []; for (idx of indices) { filtered.push(list[idx]) }
reduce push
filtered = indices.reduce((res, idx) => { res.push(list[idx]); return res; }, []);
filter some
filtered = list.filter((item, idx) => { return indices.some((index) => index === idx); });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for push
reduce push
filter some

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

**Benchmark Description**

The benchmark measures the performance of three different ways to filter an array of numbers, based on their indices. The array `list` contains 100 random numbers between 0 and 200, and a subset of 5 indices is randomly selected from this range to be used for filtering. The goal is to filter out all elements that are not in the selected indices.

**Options Compared**

The three options compared are:

1. **For Loop with Push**: Using a traditional `for` loop to iterate over the indices and push corresponding elements into a new array.
2. **Reduce Method with Push**: Utilizing the `reduce()` method to create a new array by pushing elements from the original array onto it, based on the indices.
3. **Filter Method with Some**: Employing the `filter()` method to create a new array containing only the elements that have an index present in the subset of indices.

**Pros and Cons**

* **For Loop with Push**:
	+ Pros: Easy to understand and implement for developers familiar with traditional loops.
	+ Cons: Can be slow due to the overhead of loop control statements, iteration over the indices array, and push operations.
* **Reduce Method with Push**:
	+ Pros: Efficient use of `reduce()` method, which is optimized for performance, and push operations are concise and readable.
	+ Cons: May require more cognitive effort to understand and implement, especially for developers without experience with functional programming concepts.
* **Filter Method with Some**:
	+ Pros: Concise and expressive implementation using the `filter()` method, which is well-suited for this type of operation.
	+ Cons: May be slower than the other options due to the overhead of the `some()` method invocation.

**Library Usage**

None of the test cases explicitly use any external libraries. However, it's worth noting that the `Array.from()` method is used in the script preparation code, which is a modern ES6 feature introduced by the ECMAScript standard.

**Special JS Feature/Syntax**

No special JavaScript features or syntax are being tested in this benchmark. The implementation focuses on showcasing the performance differences between three common array filtering methods.

Now that we've broken down the benchmark, let's discuss alternative approaches:

* **Other Array Filtering Methods**: Besides `reduce()`, `filter()`, and traditional loops with push, other methods like `forEach()` and `map()` can also be used to filter arrays. However, these may not offer significant performance benefits in this specific use case.
* **Caching or Memoization**: In some cases, caching or memoization techniques might be employed to store intermediate results or avoid redundant computations. This could potentially improve performance but is not relevant to the scope of this benchmark.

Overall, this benchmark provides a clear and concise comparison of three common array filtering methods, allowing developers to understand and evaluate their relative performance characteristics.

Related benchmarks:

filter by indices (version: 0)

Comparing performance of: for push vs reduce push vs filter some

Created: 5 years ago by: Guest

Jump to the latest result

for push

reduce push

filter some

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):