Benchmark: Slice vs Filter - MeasureThat.net

Script Preparation code:

var arr = Array.from(Array(1000).keys());
var arr2;
var index = 100;

Tests:

filter
arr2 = arr.filter(function(i) { return i !== index; });
slice
arr2 = arr.slice(0,index).concat(arr.slice(index+1));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter
slice

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 7 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.95 Safari/537.36

Browser/OS: Chrome 55 on Mac OS X 10.11.6

View result in a separate tab

Test name	Executions per second
filter	3796.4 Ops/sec
slice	299080.7 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, the options compared, their pros and cons, and other considerations.

**Benchmark Overview**

The "Slice vs Filter" benchmark is designed to compare the performance of two approaches: using `Array.prototype.slice()` and `Array.prototype.filter()`. Both methods aim to create a new array containing only the elements in the original array that meet a certain condition (in this case, excluding the element at index `index`).

**Script Preparation Code**

The provided script preparation code is used to set up the test environment:
```javascript
var arr = Array.from(Array(1000).keys()); // Create an array of 1000 elements from 0 to 999
var arr2; // Initialize a variable to store the result
var index = 100; // Set the index value to exclude
```
This code creates an array `arr` with 1000 elements using `Array.from()` and sets up a variable `index` to represent the element to be excluded.

**Html Preparation Code**

Since this is a JavaScript-only benchmark, there is no HTML preparation code provided.

**Benchmark Definition**

The two test cases are defined as follows:

1. **filter**
```javascript
arr2 = arr.filter(function(i) {
  return i !== index;
});
```
This approach uses the `Array.prototype.filter()` method to create a new array containing only the elements that do not match the condition (i.e., excluding the element at index `index`).

2. **slice**
```javascript
arr2 = arr.slice(0, index).concat(arr.slice(index + 1));
```
This approach uses the `Array.prototype.slice()` method to create a new array containing two parts: the first part from index 0 to `index - 1`, and the second part from `index + 1` to the end of the original array. The two parts are then concatenated using the `concat()` method.

**Options Compared**

The benchmark compares two options:

* **Filter**: uses `Array.prototype.filter()`
* **Slice**: uses `Array.prototype.slice()`

**Pros and Cons**

Both approaches have their advantages and disadvantages:

* **Filter**:
	+ Pros: simple and efficient (since it only iterates over the elements that need to be kept)
	+ Cons: can be slower for large arrays due to the overhead of creating a new array
* **Slice**:
	+ Pros: can be faster for large arrays since it avoids the overhead of creating a new array
	+ Cons: requires more memory and can be less efficient if not used carefully (e.g., when dealing with very large arrays)

**Other Considerations**

When choosing between `filter` and `slice`, consider the following:

* If you need to exclude only one element, `filter` might be a better choice since it avoids creating an unnecessary new array.
* If you need to include multiple elements or create a subset of the original array, `slice` might be more suitable.

**Library**

There is no explicit library mentioned in this benchmark. However, both methods are built-in methods on the Array prototype, which means they are part of the JavaScript standard library.

**Special JS Feature/Syntax**

None mentioned.

**Alternatives**

For large datasets or performance-critical applications, you may want to consider alternative approaches:

* **Using a custom function**: instead of relying on built-in methods like `filter()` and `slice()`, you can write your own custom function to achieve the desired result.
* **Using parallel processing**: if the dataset is extremely large, you might be able to speed up the benchmark by using parallel processing techniques (e.g., Web Workers or node clusters).
* **Optimizing the data structure**: depending on the specific requirements and constraints of your application, optimizing the underlying data structure (e.g., using a more efficient data type like `Map` instead of `Array`) might lead to better performance.

Related benchmarks:

Slice vs Filter (version: 0)

Comparing performance of: filter vs slice

Created: 8 years ago by: Guest

Jump to the latest result

filter

slice

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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