Benchmark: filter VS slice for Array

Script Preparation code:

var userData=Array.from({length: 100},()=>Math.random(1));
var segmantSize=3;
var segmentIndex=30;

Tests:

slice
userData.slice((segmentIndex - 1) * segmantSize, segmentIndex * segmantSize);
filter
const first = (segmentIndex - 1) * segmantSize const last = segmentIndex * segmantSize return userData.filter((_, index) => { return first <= index && index < last })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice
filter

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The benchmark definition provides two different approaches to filter a large array: `slice` and `filter`. The script preparation code creates an array of 100 random numbers, and then defines the segment size and index. This setup allows for comparing the performance of these two methods on similar data.

**Options Compared**

The `slice` method uses the `Array.prototype.slice()` method to extract a subset of elements from the original array. The `filter` method uses the `Array.prototype.filter()` method with a callback function that returns `true` if an element falls within the specified range.

**Pros and Cons of Each Approach**

*   **Slice Method**
    *   Pros:
        *   Efficient for fixed-size ranges
        *   Simple to use and understand
    *   Cons:
        *   May not be suitable for variable or dynamic ranges
        *   Can lead to unnecessary copies of the original array
*   **Filter Method**
    *   Pros:
        *   Flexible and adaptable to different range types (e.g., inclusive-exclusive, negative indices)
        *   Reduces the need for explicit bounds handling
    *   Cons:
        *   May be slower due to additional overhead from callback functions

**Library Used**

None are explicitly mentioned in this benchmark. However, `Array.from()` is used to create an array with a specified length and initial value.

**Special JS Feature or Syntax**

The use of template literals (`\r\n` notation) for code formatting is present. This feature allows for more readable code by inserting line breaks between statements.

**Other Considerations**

When comparing these two methods, it's essential to consider the following factors:

*   Array size and complexity
*   Range type (inclusive-exclusive, negative indices)
*   Need for explicit bounds handling

**Alternatives**

Other alternatives to `slice` and `filter` methods include:

*   **Spread Operator (`...`)**: Can be used with `Array.prototype.slice()` or `Array.prototype.filter()` to create a new array with the desired range.
    *   Example: `userData.slice(...segmentIndex * segmantSize, ...segmentIndex * segmantSize + segmantSize)`
*   **Math.min() and Math.max() functions**: Can be used to define the range boundaries for filtering or slicing arrays.
    *   Example: `(Math.min(segmentIndex \* segmantSize, segmentIndex \* segmantSize + segmantSize) - 1) <= index && index < (Math.max(segmentIndex \* segmantSize, segmentIndex \* segmantSize + segmantSize))`
*   **Native Array.prototype.map()**: Can be used to filter or slice arrays by applying a transformation function.
    *   Example: `userData.slice(0, segmentIndex \* segmantSize).map((_, index) => index < segmantSize)`
*   **Custom implementation using indexes and conditional statements**: Can provide fine-grained control over the filtering or slicing process.

Keep in mind that these alternatives might not always be faster or more efficient than the `slice` and `filter` methods, especially for simple range operations.

Related benchmarks:

filter VS slice for Array (version: 0)

Comparing performance of: slice vs filter

Comparing performance of: slice vs filter

Created: 3 years ago by: Guest

Jump to the latest result

slice

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):