Benchmark: reduce as filter vs filter

Script Preparation code:

var arr = [];
for (var i = 0; i < 12345; i++) {
  arr[i] = i;
}

var reduceResults = [],
  filterResults = [];

Tests:

reduce
arr.reduce((lastValue, item) => { if (item % 2 === 0) reduceResults.push(item); });
filter
filterResults = arr.filter(item => item % 2 === 0);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce
filter

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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**Benchmark Definition**

The provided JSON represents a JavaScript benchmarking test case. In this test, we're comparing two approaches to filter an array: using the `Array.prototype.reduce()` method and using the `Array.prototype.filter()` method.

**Options Compared**

We have two options being compared:

1. **Reduce as Filter (using `reduce()`)**: This approach uses the `reduce()` method to iterate through the array, pushing elements that meet a certain condition (`item % 2 === 0`) into an output array.
2. **Filter (using `filter()`)**: This approach uses the `filter()` method to create a new array containing only elements that meet a certain condition (`item % 2 === 0`).

**Pros and Cons**

Here are some pros and cons of each approach:

**Reduce as Filter**

Pros:

* Can be more flexible, as it allows for arbitrary aggregation logic.
* May be faster for large datasets, since it avoids creating an intermediate array.

Cons:

* Requires a callback function to define the aggregation logic, which can be less readable.
* Has higher overhead due to the need to create and manage an accumulator variable.

**Filter**

Pros:

* More concise and readable, as it directly filters elements without needing to worry about aggregation logic.
* Easier to understand and maintain, especially for small datasets or simple filtering conditions.

Cons:

* Creates an intermediate array, which can lead to higher memory usage and slower performance for very large datasets.
* Less flexible than `reduce()`, as the filtering condition is applied directly to the elements without any additional processing.

**Library Usage**

Neither of these approaches uses a specific library. However, it's worth noting that `Array.prototype.reduce()` and `Array.prototype.filter()` are part of the ECMAScript standard, making them widely supported across different JavaScript engines and environments.

**Special JS Feature or Syntax**

There doesn't seem to be any special JavaScript features or syntax being used in this benchmark. The code is straightforward and uses only basic array methods.

**Other Alternatives**

If you're looking for alternative approaches to filter an array, here are a few examples:

* Using `Array.prototype.every()` (which filters out elements that don't meet the condition) instead of `filter()`
* Using `Array.prototype.some()` (which returns true if at least one element meets the condition) instead of `filter()`
* Using a simple loop or for-each iteration to iterate through the array and filter elements manually
* Using external libraries like Lodash, which provides various filtering methods like `_.filter()`

Related benchmarks:

reduce as filter vs filter (version: 0)

Comparing performance of: reduce vs filter

Created: 5 years ago by: Guest

Jump to the latest result

reduce

filter

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):