Benchmark: map+filter vs reduce

Tests:

map
const tableData = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]; const ids = new Array(100) .fill(null) .map((_, i) => { return tableData[i]; }) .filter(id => id !== undefined);
reduce
const tableData = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]; const ids = new Array(100).reduce((acc, _, i) => { if(tableData[i]) { acc[i] = tableData[i] || null } return acc; }, []);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
reduce

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Let's dive into the benchmark and explain what's being tested, compared, and their pros and cons.

**Benchmark Overview**

The provided JSON represents a JavaScript microbenchmark comparing two approaches: `map` and `reduce`. The benchmark is designed to measure the performance of these two methods on an array of 100 elements.

**Test Case 1: "map"**

In this test case, we have:
```javascript
const tableData = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1];
const ids = new Array(100).fill(null).map((_, i) => tableData[i]);
```
Here, we create an array of 100 elements and then use the `map` method to create a new array with the same number of elements. Each element in the original array is mapped to itself.

**Test Case 2: "reduce"**

In this test case, we have:
```javascript
const tableData = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1];
const ids = new Array(100).reduce((acc, _, i) => acc[i] = tableData[i] || null, []);
```
Here, we create an array of 100 elements and then use the `reduce` method to create a new array with the same number of elements. The accumulator (`acc`) is initially an empty object, and each element in the original array is added to it using the current index as the key.

**Comparison**

The benchmark compares the performance of these two methods on the specified input data. The test cases are executed multiple times (not shown in this example), and the results are stored in an array of objects.

**Results**

According to the provided results, the `reduce` method performs significantly better than the `map` method, with approximately 20x faster execution time for each iteration.

**Pros and Cons**

* **Map**: Pros:
	+ Easy to read and write
	+ Can be used when you need to perform a transformation on each element of an array without modifying the original array.
* Cons:
	+ Can be slower than `reduce` for large arrays, especially if you need to access elements by index.
* **Reduce**: Pros:
	+ Can be faster than `map` for large arrays, especially when accessing elements by index.
* Cons:
	+ More complex and harder to read/write compared to `map`.
	+ Requires careful consideration of the initial value of the accumulator.

In general, if you need to perform a simple transformation on an array without modifying it, `map` might be a better choice. However, if you need to access elements by index or perform more complex operations, `reduce` might be a better option.

Related benchmarks:

map+filter vs reduce (version: 0)

Comparing performance of: map vs reduce

Created: 5 years ago by: Guest

Jump to the latest result

map

reduce

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):