Benchmark: flatMap() vs filter().map() 2234234

Script Preparation code:

var arr = [];
var i = 0;
var empty = [];

while (i <= 1E5) arr[i] = i++;

Tests:

filter().map()
arr.filter(x => x % 3).map(x => x/100)
flatMap()
arr.flatMap(x => x % 3 ? x/100 : empty)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter().map()
flatMap()

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.

Let's break down the provided benchmark and its results.

**Benchmark Definition:**

The benchmark measures the performance difference between two approaches:

1. `filter().map()`
2. `flatMap()`

Both approaches are used to process an array (`arr`) that contains numbers from 0 to 100,000 (in increments of 1). The tasks involve filtering out multiples of 3 and then performing a mapping operation on the remaining elements.

**Options Compared:**

The two options being compared are:

* `filter()`: A method that creates a new array containing only the elements that pass the test implemented by the provided function.
* `flatMap()`: A method that creates a new array with the results of applying the provided function to each element in this array.

**Pros and Cons:**

1. **`filter().map()`**:
	* Pros:
		+ Easy to understand and implement, as it's a well-known combination.
		+ Can be optimized by using `Array.prototype.findIndex()` and `Array.prototype.slice()` instead of `Array.prototype.indexOf()`.
	* Cons:
		+ Creates two intermediate arrays (one for filtering and one for mapping), which can lead to higher memory usage.
		+ Requires an additional operation for creating the filtered array.
2. **`flatMap()`**:
	* Pros:
		+ Only creates a single intermediate array, reducing memory overhead.
		+ Can be optimized by using `Array.prototype.findIndex()` and `Array.prototype.push()`.
	* Cons:
		+ May have higher execution overhead due to the need to create an intermediate array.

**Library Used:**

There is no library explicitly mentioned in the benchmark definition. However, it's worth noting that both `filter()`, `map()`, and `flatMap()` are built-in JavaScript methods.

**Special JS Feature/Syntax:**

None of the options used any special JavaScript features or syntax that would require specific knowledge to understand.

**Other Considerations:**

When choosing between these two approaches, consider the trade-off between memory usage and execution overhead. If you prioritize performance over memory efficiency, `flatMap()` might be a better choice. However, if you need to work with large datasets and memory is a concern, `filter().map()` might still be a viable option.

**Other Alternatives:**

If you're interested in exploring alternative approaches, consider the following:

1. **Using `Array.prototype.reduce()`**: Instead of using `map()` or `flatMap()`, you can use `reduce()` to achieve similar results.
2. **Implementing a custom filtering and mapping function**: You can create a custom function that takes advantage of specific browser optimizations or performance characteristics.
3. **Using a library or framework**: Depending on your project's requirements, using a library like Lodash or Ramda might provide additional benefits in terms of readability and maintainability.

Keep in mind that these alternatives may not always outperform the original `filter().map()` and `flatMap()` approaches, but they can offer interesting trade-offs and insights into JavaScript performance optimization.

Related benchmarks:

flatMap() vs filter().map() 2234234 (version: 0)

flatMap vs filter map

Comparing performance of: filter().map() vs flatMap()

Created: 3 years ago by: Guest

Jump to the latest result

filter().map()

flatMap()

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):