Benchmark: Two lambdaless filters vs one lambded v2

Script Preparation code:

var data = Array.from(Array(5000), () => Math.random());
                        
var more = (n) => n > 0.3;                         
var less = (n) => n < 0.6;

Tests:

Two filters
var filtered = data.filter(more).filter(less);
Combined filter
var filtered = data.filter(n => more(n) && less(n));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Two filters
Combined filter

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 9 months ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36

Browser/OS: Chrome 122 on Linux

View result in a separate tab

Test name	Executions per second
Two filters	5966.8 Ops/sec
Combined filter	1958.4 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the provided benchmark definition and test cases.

**Benchmark Definition:**

The website is measuring the performance of different JavaScript approaches for filtering an array of random numbers.

The script preparation code defines two functions, `more` and `less`, which take a number as input and return a boolean indicating whether the number is greater than 0.3 or less than 0.6, respectively.

**Test Cases:**

There are two individual test cases:

1. **"Two filters"`**: This test case uses the traditional callback function approach with multiple filter functions called sequentially.
   ```javascript
var filtered = data.filter(more).filter(less);
```
   The `more` and `less` functions are applied one after the other to the filtered array.

2. **"Combined filter"`**: This test case uses a single function expression that combines both filters using logical AND (`&&`) operators.
   ```javascript
var filtered = data.filter(n => more(n) && less(n));
```
   The `more` and `less` functions are embedded inside the arrow function, which is called on each element of the array.

**Library:**

There is no explicitly mentioned library in the provided benchmark definition. However, it's common to use libraries like Lodash or Ramda for functional programming tasks like filtering arrays.

**Pros and Cons:**

1. **"Two filters"`**:
   - Pros: Easy to understand and implement, especially for those familiar with traditional callback functions.
   - Cons: Requires multiple function calls, which can be slower due to the overhead of creating new contexts and binding variables.

2. **"Combined filter"`**:
   - Pros: More concise and readable, as it combines both filters in a single operation.
   - Cons: May have performance issues if the combined logic is complex or computationally expensive, potentially affecting cache locality and memory access patterns.

Other alternatives to consider:

* Using `Array.prototype.reduce()` or other aggregation functions might provide alternative approaches to combining filter operations.
* Employing more advanced functional programming techniques, such as using `map()`, `reduce()`, or higher-order functions like `forEach()` or `every()`, could potentially yield better performance in certain scenarios.

**Special JS Feature/Syntax:**

The provided benchmark definition uses arrow function expressions (`n => more(n) && less(n)`), which is a modern JavaScript feature introduced in ECMAScript 2015 (ES6). Arrow functions provide concise syntax for defining small, single-expression functions and can improve readability.

Related benchmarks:

Two lambdaless filters vs one lambded v2 (version: 0)

Comparing performance of: Two filters vs Combined filter

Created: 3 years ago by: Guest

Jump to the latest result

Two filters

Combined filter

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):