Benchmark: filter_map vs reduce 2

Script Preparation code:

arr = [];
for (let i = 0; i < 1000; ++i) {
  arr.push({
    foo: Math.random() > 0.5,
    bar: Math.round(Math.random() * 100),
  });
}

Tests:

reduce
const result = arr.reduce((acc, item) => { if (!item.foo) { acc.push(item.bar); } return acc; }, []);
filter_map
const result = arr .filter((item) => !item.foo) .map((item) => item.bar);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce
filter_map

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36

Browser/OS: Chrome 116 on Windows

View result in a separate tab

Test name	Executions per second
reduce	328225.6 Ops/sec
filter_map	194722.3 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks!

**What is being tested?**

The provided benchmark compares two approaches to filter and map an array: `reduce` and `filter`/`map`. Specifically, it tests which approach performs better when filtering out objects that don't have a `foo` property and then mapping over the remaining objects to extract their `bar` properties.

**Options being compared**

The two options being compared are:

1. **`reduce`**: This method applies a reduction function to each element in an array, accumulating a value. In this case, it's used to filter out objects that don't have a `foo` property and accumulate the `bar` properties of the remaining objects.
2. **`filter`/`map`**: This approach uses the `filter` method to remove elements from an array that don't meet a condition (in this case, not having a `foo` property), and then uses the `map` method to apply a transformation function to each element in the filtered array (extracting the `bar` properties).

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

* **`reduce`**:
	+ Pros: Can be more efficient for small arrays, as it avoids the overhead of creating intermediate arrays.
	+ Cons: Can be slower for large arrays due to its accumulator nature, which may require extra memory allocations.
* **`filter`/`map`**:
	+ Pros: Generally faster and more concise, especially for larger arrays.
	+ Cons: Creates an additional intermediate array, which can consume more memory.

**Library usage**

In the provided benchmark, there is no explicit library mentioned. However, it's worth noting that some JavaScript implementations (like V8 in Chrome) have optimized `reduce` methods that use a specialized algorithm to reduce memory allocations during execution.

**Special JS feature or syntax**

There are no special features or syntax used in this benchmark that would require specific knowledge of advanced JavaScript concepts.

**Other alternatives**

If you're interested in exploring alternative approaches, here are some options:

* **`forEach`**: While not explicitly tested in the provided benchmark, `forEach` can be used to iterate over an array and perform operations on each element.
* **`Array.prototype.forEach()` with a callback function**: Similar to `forEach`, but provides more flexibility for customizing the iteration process.

Keep in mind that these alternatives might have different performance characteristics compared to the `reduce` and `filter`/`map` approaches.

Related benchmarks:

filter_map vs reduce 2 (version: 0)

Comparing performance of: reduce vs filter_map

Created: 4 years ago by: Guest

Jump to the latest result

reduce

filter_map

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):