Benchmark: filter then foreach vs foreach conditional

Script Preparation code:

var arr = [];
for (var i = 0; i < 12345; i++) {
  arr[i] = i;
}

var testObj;

var sumForEach = 0,
  sumReduce = 0,
  sumMap = 0,
  sumFilter = 0,
  sumFor = 0;

Tests:

forEach
arr.forEach( (flowConnectionReference) => { if (flowConnectionReference !== 1) { testObj = { "test": flowConnectionReference } } });
reduce
sumReduce = arr.filter((flowConnectionReference) => flowConnectionReference !== 1).forEach(flowConnectionReference => {testObj = {"test": flowConnectionReference}})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
forEach
reduce

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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**Benchmark Overview**

The provided benchmark measures the performance difference between two approaches: `forEach` with an `if` statement and `reduce` with an `if` statement, both of which are used to filter out a specific element from an array. The benchmark creates an array of 12,345 elements and assigns each element a unique value.

**Options Compared**

The options being compared are:

1. `forEach`: A method that iterates over the elements of an array, allowing you to execute a function for each element.
2. `reduce`: A method that reduces an array by performing a binary operation on every pair of elements.

**Pros and Cons of Each Approach**

* `forEach`:
	+ Pros: Simple to use, easy to understand, and suitable for many use cases.
	+ Cons: It can be slower than `reduce` due to the overhead of function invocation and variable scope management.
* `reduce`:
	+ Pros: More efficient than `forEach`, as it avoids function invocation and variable scope management. Additionally, it can reduce memory allocations, making it a better choice for large datasets.
	+ Cons: More complex to use, especially when dealing with edge cases or multiple filters.

**Other Considerations**

* Variable Scope: In both approaches, the variable `testObj` is scoped within the function. However, in `forEach`, it's re-scoped on each iteration, which can lead to performance issues.
* Array Iteration: Both methods iterate over the array, but `forEach` uses a more traditional, explicit loop, while `reduce` uses an accumulator-based approach.

**Library and Special Features**

There is no specific library used in this benchmark. However, both `forEach` and `reduce` are built-in methods of the JavaScript Array prototype.

**Special JS Feature or Syntax (none)**

No special JavaScript features or syntax are used in this benchmark.

**Alternative Approaches**

If you need to filter elements from an array, consider using other approaches:

1. `filter()`: A method that returns a new array with only the elements that pass the test implemented by the provided function.
2. `map()`: A method that creates a new array with the results of applying the provided function on every element in this array.
3. Using arrow functions or regular functions for more complex filtering logic.

Keep in mind that these alternatives may have different performance characteristics and use cases compared to `forEach` and `reduce`.

**Benchmark Preparation Code Explanation**

The script preparation code creates an empty array `arr` with 12,345 elements, each assigned a unique value. It also defines variables `testObj`, `sumForEach`, `sumReduce`, `sumMap`, `sumFilter`, and `sumFor` to store the results of each test.

**Individual Test Cases**

The first test case uses `forEach` with an `if` statement to filter out elements that are not equal to 1. The second test case uses `reduce` with an `if` statement to achieve the same filtering result.

Related benchmarks:

filter then foreach vs foreach conditional (version: 0)

Comparing performance of: forEach vs reduce

Created: 4 years ago by: Guest

Jump to the latest result

forEach

reduce

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):