Benchmark: Map vs preallocation 2

Script Preparation code:

var array = new Array(1000000).fill(0);

Tests:

Map
const array2 = array.map((item, index) => index);
Preallocation
const array2 = new Array(1000000).fill(0); for (let i = 0; i < array2.length; i++) array2[i] = i;
Preallocation 2
const len = 1000000; const array3 = new Array(len).fill(0); for (let i = 0; i < len; i++) array3[i] = i;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map
Preallocation
Preallocation 2

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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**Overview**

The provided JSON represents a JavaScript benchmark test case, specifically testing the performance of two approaches for mapping over an array: using the `map()` method versus preallocating and then iterating over the array.

**Benchmark Test Case**

The test case consists of three individual tests:

1. **Map**: This test creates a new array using the `map()` method, which applies a transformation function to each element in the original array.
2. **Preallocation**: This test preallocates an array with 1 million elements and then iterates over the array, assigning a value to each element.
3. **Preallocation 2**: Similar to the previous test, but uses `new Array(len).fill(0)` to create the preallocated array.

**Comparison of Approaches**

The two main approaches being compared are:

*   **Map Method**: This approach creates a new array with the desired number of elements and then applies a transformation function to each element using the `map()` method.
*   **Preallocation**: This approach preallocates an array with the desired number of elements and then iterates over the array, assigning a value to each element.

**Pros and Cons**

Here are some pros and cons of each approach:

*   **Map Method**
    *   Pros:
        *   Easier to implement and maintain, as it avoids manual memory management.
        *   Allows for more flexibility in terms of transformation functions.
    *   Cons:
        *   Creates a new array, which can be inefficient if the original array is large.
*   **Preallocation**
    *   Pros:
        *   Can be more efficient for large arrays, as it avoids creating multiple intermediate arrays.
        *   Reduces memory allocation and deallocation overhead.
    *   Cons:
        *   Requires manual memory management using pointers or references to avoid issues like "use after free".
        *   Can be more error-prone due to the complexity of manually managing memory.

**Library and Purpose**

None of the tests use any libraries in this benchmark. The code is simple, straightforward JavaScript, with no external dependencies.

**Special JS Features**

There are no special JavaScript features or syntaxes used in these test cases. They are standard ECMAScript 5+ syntax.

**Alternative Approaches**

Other approaches to mapping over an array might include:

*   **Array.prototype.forEach()**: This method executes a callback function for each element in the array, but does not return a new array.
*   **Array.prototype.reduce()**: This method applies a reduction function to each element in the array and returns a single value.
*   **Closures or loops with manual memory management**: These approaches would require more manual memory management using pointers or references.

**Conclusion**

The Map vs preallocation 2 benchmark test case provides insight into the performance differences between two approaches for mapping over an array: using the `map()` method versus preallocating and then iterating over the array. The choice of approach depends on the specific requirements of the use case, including factors like memory efficiency, flexibility, and ease of implementation.

Related benchmarks:

Map vs preallocation 2 (version: 0)

Comparing performance of: Map vs Preallocation vs Preallocation 2

Created: 3 years ago by: Guest

Jump to the latest result

Map

Preallocation

Preallocation 2

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):