Benchmark: continuous array vs sparse array

Script Preparation code:

var continuous = [];
var sparse = [];
var C = 900000;
for(var i=0; i<C; ++i){
  continuous.push(C-i);
}
for(var i=0; i<C; ++i){
  sparse[i * 2] = C - i;
}

Tests:

continuous reduce
var total = continuous.reduce(function(acc, cur){ return acc + cur; });
sparse reduce
var total = sparse.reduce(function(acc, cur){ return acc + cur; });
continuous update
continuous.forEach(function(cur, i, arr){ arr[i] += 100; });
sparse update
sparse.forEach(function(cur, i, arr){ arr[i] += 100; });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
continuous reduce
sparse reduce
continuous update
sparse update

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its test cases.

**Benchmark Definition:**
The benchmark compares the performance of two types of arrays in JavaScript:

1. **Continuous array**: An array where every element is directly accessible by its index, without any holes or gaps.
2. **Sparse array**: An array where some elements are missing, represented as `undefined` values at those indices.

The script preparation code creates a continuous array with 900,000 elements and a sparse array with the same number of elements, but with every other element being `undefined`.

**Script Preparation Code:**
```javascript
var continuous = [];
var sparse = [];
var C = 900000;

for (var i = 0; i < C; ++i++) {
  continuous.push(C - i);
}

for (var i = 0; i < C; ++i) {
  sparse[i * 2] = C - i;
}
```
This code initializes both arrays with the same elements, but the sparse array has every other element being `undefined`.

**Test Cases:**
The benchmark consists of four test cases:

1. **Continuous reduce**: Measures the performance of the `reduce()` method on the continuous array.
2. **Sparse reduce**: Measures the performance of the `reduce()` method on the sparse array.
3. **Continuous update**: Measures the performance of the `forEach()` method with a callback function that updates an element in the continuous array.
4. **Sparse update**: Measures the performance of the `forEach()` method with a callback function that updates an element in the sparse array.

**Options Compared:**
The benchmark compares two options:

1. **Reduce() method**: A built-in JavaScript method that reduces an array to a single value.
2. **ForEach() method**: A built-in JavaScript method that executes a callback function for each element in an array.

**Pros and Cons:**

* **Reduce() method**:
	+ Pros: Efficient, vectorized, and can handle large datasets.
	+ Cons: Can be less intuitive to use, especially for complex operations.
* **ForEach() method**:
	+ Pros: Easy to understand and use, allows for easy iteration and updating of elements.
	+ Cons: Can be slower than the `reduce()` method, especially for large datasets.

**Library Used:**
The benchmark does not explicitly mention any libraries being used. However, it's likely that some underlying framework or runtime environment is providing the JavaScript engine and execution platform.

**Special JS Feature/Syntax:**
None mentioned in this specific benchmark.

**Other Considerations:**

* The benchmark uses a relatively small dataset (900,000 elements) to measure performance.
* The benchmark runs on desktop devices with Chrome 93.
* The benchmark reports executions per second, which provides an idea of the speedup or slowdown between different approaches.

**Alternative Benchmarks:**
If you're interested in exploring other benchmarking options, here are a few alternatives:

1. **Bench.js**: A popular JavaScript benchmarking library that allows for easy creation and comparison of benchmarks.
2. **Benchmarkify**: A utility library that simplifies the process of creating benchmarks and running them.
3. **Google's Benchmark**: A lightweight benchmarking library developed by Google, which provides a simple way to create and run benchmarks.

Keep in mind that different benchmarking libraries may have varying levels of complexity, customization options, and performance characteristics.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.36

Browser/OS: Chrome 93 on Windows

View result in a separate tab

Test name	Executions per second
continuous reduce	114.0 Ops/sec
sparse reduce	95.9 Ops/sec
continuous update	133.8 Ops/sec
sparse update	111.7 Ops/sec

Related benchmarks:

continuous array vs sparse array (version: 0)

Comparing performance of: continuous reduce vs sparse reduce vs continuous update vs sparse update

Created: 8 years ago by: Guest

Jump to the latest result

continuous reduce

sparse reduce

continuous update

sparse update

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):