Benchmark: native-slice-vs-chunk KE2

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var test = Array.from({
    length: 100000
}, () => Math.random())

var nativeChunk = (input, size) => {
  return input.reduce((arr, item, idx) => {
    return idx % size === 0
      ? [...arr, [item]]
      : [...arr.slice(0, -1), [...arr.slice(-1)[0], item]];
  }, []);
};

Tests:

Native slice
nativeChunk(test,5000)
lodash chunk
_.chunk(test,5000)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native slice
lodash chunk

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):

LLMs can make mistakes. Check important info.

**Benchmark Explanation**

The provided JSON represents a JavaScript microbenchmark test case, specifically comparing the performance of two approaches: native slicing and chunking using the `lodash` library.

**Native Slicing vs Chunking**

In this benchmark, we have two test cases:

1. **Native Slice**: This approach uses a custom function called `nativeChunk`, which takes an input array and a size as arguments. It then iterates through the array, splitting it into chunks of the specified size. The resulting chunks are returned as arrays.
2. **Lodash Chunk**: This approach uses the `chunk` function from the popular JavaScript utility library, Lodash. The `chunk` function takes an input array and a size as arguments, similar to the custom `nativeChunk` function.

**Options Comparison**

The two approaches differ in how they process the input array:

* **Native Slice**:
	+ Pros: Potential performance benefits due to direct implementation without relying on a library.
	+ Cons: May have slower performance due to the overhead of calling a custom function, and may not be optimized for various use cases (e.g., handling edge cases).
* **Lodash Chunk**:
	+ Pros: Well-optimized and tested library implementation, with potential benefits from caching and memoization.
	+ Cons: Relies on an external library, which may introduce additional overhead or dependencies.

**Library Usage**

The `lodash` library is used in the second test case. Lodash is a popular JavaScript utility library that provides various functions for tasks like array manipulation, string processing, and more. In this case, the `chunk` function is used to split the input array into chunks of a specified size.

**Special JavaScript Feature or Syntax**

There are no special JavaScript features or syntaxes mentioned in the benchmark definition or test cases.

**Other Alternatives**

If you're interested in exploring alternative approaches, here are a few options:

* **Built-in `Array.prototype.slice()` and `Array.prototype.splice()`**: You can use these built-in methods to achieve similar results as the custom `nativeChunk` function. However, this approach may be slower due to the overhead of calling built-in functions.
* **Other chunking libraries**: There are other JavaScript libraries available that provide chunking functionality, such as `array-chunk` or `chunked-array`. These alternatives may offer different trade-offs in terms of performance, simplicity, and dependencies.

Keep in mind that these alternative approaches may not be optimized for performance or may have different use cases compared to the native slicing approach.

Related benchmarks:

native-slice-vs-chunk KE2 (version: 2)

Comparing performance of: Native slice vs lodash chunk

Created: 2 years ago by: Registered User

Jump to the latest result

Native slice

lodash chunk

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):