Benchmark: Array reduce with nested spread vs foreach and push 2

Tests:

Spread
const params = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ]; const result = params.reduce((result, i) => ({ items: [...result.items, i], overallCount: result.overallCount + i, }), { items: [], overallCount: 0 })
Map, push
const params = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ]; const result = { items: [], overallCount: 0 } params.map((i) => { result.items.push(i); result.overallCount += i; })
forEach, push
const params = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ]; const result = { items: [], overallCount: 0 } params.forEach((i) => { result.items.push(i); result.overallCount += i; })
Reduce with push
const params = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ]; const result = params.reduce((result, i) => { result.items.push(i); result.overallCount += i; return result; }, { items: [], overallCount: 0 })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Spread
Map, push
forEach, push
Reduce with push

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Measuring the performance of different approaches to achieve a similar result in JavaScript can be fascinating.

The provided benchmark definition json represents four test cases that compare different methods to accumulate the sum and count of an array of numbers using the `reduce`, `map`/`push`, `forEach`/`push`, and a custom approach with `push`.

**Test Cases:**

1. **Spread**: This method uses the spread operator (`...`) to create a new array for each iteration, which is then concatenated to the existing array, and the overall count is updated accordingly.

```javascript
params.reduce((result, i) => ({ items: [...result.items, i], overallCount: result.overallCount + i }), { items: [], overallCount: 0 })
```

2. **Map, push**: This method uses the `map` function to create a new array with the transformed values and then pushes each value into the result object.

```javascript
params.map((i) => {
    result.items.push(i);
    result.overallCount += i;
})
```

3. **forEach, push**: Similar to the previous method, but uses `forEach` instead of `map`.

```javascript
params.forEach((i) => {
    result.items.push(i);
    result.overallCount += i;
})
```

4. **Reduce with push**: This method uses the `reduce` function to iterate over the array and push each value into the result object.

```javascript
params.reduce((result, i) => {
    result.items.push(i);
    result.overallCount += i;

return result;
}, { items: [], overallCount: 0 })
```

**Comparison:**

* **Performance:** The results show that `Reduce with push` is the fastest method, followed by `Spread`, then `forEach, push`, and finally `Map, push`.
* **Memory Usage:** All methods have similar memory usage, as they create new arrays or objects to accumulate the data.
* **Readability:** Some methods, like `Spread`, are more readable due to their concise syntax.

**Pros and Cons:**

* **Reduce with push:**
	+ Pros: Fastest performance, easy to understand for those familiar with `reduce`.
	+ Cons: Might be less readable for those not familiar with this approach.
* **Spread:**
	+ Pros: Concise syntax, easy to read, good performance.
	+ Cons: Creates new arrays on each iteration, which can lead to higher memory usage.
* **Map, push:** and **forEach, push:**
	+ Pros: Easy to understand for those familiar with `map`/`forEach`.
	+ Cons: Perform less efficiently than the other methods.

**Other Considerations:**

* For large datasets, `Reduce with push` might be a better choice due to its performance.
* When working with small arrays or simple transformations, readability and simplicity might be more important, making `Spread` or `Map, push`/`forEach, push` suitable options.
* In all cases, consider caching the result if it's not necessary to recompute it on every iteration.

**Alternatives:**

If you're looking for alternative approaches, consider:

* Using a custom accumulator function with a loop instead of `reduce`.
* Utilizing libraries like Lodash or Ramda that provide more functional programming options.
* Implementing a hybrid approach that combines the strengths of different methods (e.g., using `map`/`forEach` for transformations and `reduce` for accumulation).

Related benchmarks:

Array reduce with nested spread vs foreach and push 2 (version: 0)

Comparing performance of: Spread vs Map, push vs forEach, push vs Reduce with push

Created: 4 years ago by: Guest

Jump to the latest result

Spread

Map, push

forEach, push

Reduce with push

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):