Benchmark: FlatMap method vs for loop big 31-10-24

Script Preparation code:

var arr = Array(10_000_000).fill(0);

Tests:

flatMap
arr.flatMap(x => [x, x * 2]);
for loop
const n = arr.length; const acc = new Array(n * 2); for (let i = 0; i < n; i++){ const x = arr[i]; acc[i * 2] = x; acc[i * 2 + 1] = x * 2; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
flatMap
for loop

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 21 days ago):

LLMs can make mistakes. Check important info.

The benchmark presented compares two different approaches for transforming an array in JavaScript: the `flatMap` method versus a traditional `for` loop.

### Options Compared

1. **flatMap Method**:
   - **Benchmark Definition**: 
     ```javascript
     arr.flatMap(x => [x, x * 2]);
     ```
   - **Description**: The `flatMap` method creates a new array with each element being the result of a callback function, which in this case generates two elements for each input element (the element itself and twice its value). The results are then flattened into a single array.

2. **For Loop**:
   - **Benchmark Definition**: 
     ```javascript
     const n = arr.length;
     const acc = new Array(n * 2);
     for (let i = 0; i < n; i++) {
       const x = arr[i];
       acc[i * 2] = x;
       acc[i * 2 + 1] = x * 2;
     }
     ```
   - **Description**: The `for` loop explicitly iterates through each element of the array, populating a new array (`acc`) by setting two values for each element (the element and its double), based on index calculations.

### Pros and Cons

**flatMap Method**:
- **Pros**:
  - More concise and expressive. The use of higher-order functions provides a readably and functional programming style.
  - Built into the JavaScript language, potentially benefiting from optimizations present in modern engines.
- **Cons**:
  - May incur overhead due to function calls and array flattening, which could affect performance, particularly with large datasets.
  - May not be as flexible as a `for` loop for more complex logic.

**For Loop**:
- **Pros**:
  - More control over the operation being performed, which can be beneficial for complex transformations.
  - Generally yields better performance in scenarios where optimal execution speed is critical, as it avoids the overhead associated with function calls.
- **Cons**:
  - More verbose and potentially less readable, especially when dealing with more complex logic.
  - Error-prone, especially in terms of index calculations.

### Other Considerations

- In this benchmark, the test setup initializes an array of 10 million elements filled with zeros, which simulates a large dataset to evaluate the performance difference effectively.
- Result interpretation shows that the execution speed for both methods is quite similar, with the `for loop` achieving approximately 2.66 executions per second and `flatMap` slightly behind at 2.65 executions per second.
  
### Alternatives

When considering alternatives for transforming arrays, there are a few other methods in JavaScript:
- **map + concat**: Instead of `flatMap`, one could use `map` to transform the values and then `concat` to merge the resulting arrays, though this would generally be less efficient than `flatMap` for flattening.
  
   ```javascript
   const result = [].concat(...arr.map(x => [x, x * 2]));
   ```

- **reduce**: For flexibility in operations or accumulation, `reduce` can also be employed, albeit potentially at the cost of readability.
  
   ```javascript
   const result = arr.reduce((acc, x) => {
       acc.push(x, x * 2);
       return acc;
   }, []);
   ```

This benchmark demonstrates the performance characteristics of two popular ways to process arrays in JavaScript, giving developers insights into when one method might be preferred over another based on readability, performance, and specific use cases.

Latest run results:

Run details: (Test run date: 21 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
flatMap	2.7 Ops/sec
for loop	2.7 Ops/sec

Related benchmarks:

FlatMap method vs for loop big 31-10-24 (version: 0)

Compare the performance of for loop vs flatMap method

Comparing performance of: flatMap vs for loop

Created: 21 days ago by: Guest

Jump to the latest result

flatMap

for loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 21 days ago):