Benchmark: flatmap vs filter-map other

Script Preparation code:

var arr = [];
var i = 0;

while (i <= 100) arr[i] = i++;

Tests:

filter -> map
arr.filter(x => x % 3).map(x => x/100)
flatmap
arr.flatMap(x => x % 3 ? x/100 : [])

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:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.71 Safari/537.36

Browser/OS: Chrome 94 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
filter -> map	1195694.1 Ops/sec
flatmap	81940.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

**Benchmark Definition**

The benchmark definition is a JSON object that provides metadata about the test case. In this case, there are two benchmark definitions:

1. `arr.filter(x => x % 3).map(x => x/100)`
2. `arr.flatMap(x => x % 3 ? x/100 : [])`

Both benchmarks operate on an array `arr` initialized with a loop in the script preparation code.

**Options Compared**

The two benchmarks compare two different approaches to process elements in an array:

1. **filter -> map**: This approach uses the `filter()` method to remove elements that don't meet a certain condition, and then applies the `map()` method to transform remaining elements.
2. **flatmap**: This approach uses the `flatMap()` method, which is similar to `filter()` but returns an array of transformed values instead of an array of boolean indicators.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

* **Filter -> Map**:
	+ Pros: Easy to understand and implement. The `filter()` method is typically faster than `flatMap()`.
	+ Cons: May incur additional overhead due to the two separate operations (filtering and mapping).
* **Flatmap**:
	+ Pros: Can be more efficient since it avoids the need for an intermediate array.
	+ Cons: Can be less intuitive, especially for developers unfamiliar with this method.

In general, if you're dealing with a small number of elements or need to perform some simple transformation, `filter -> map` might be a safer choice. However, when working with large datasets or complex transformations, `flatMap` can offer better performance.

**Library**

There is no explicit library mentioned in the benchmark definition. The `flatmap()` method is part of the modern ECMAScript standard (ES6+), so it's likely that the test is targeting a recent JavaScript engine.

**Special JS Feature or Syntax**

There are no special features or syntax used in this benchmark that would be unfamiliar to most developers. However, keep in mind that the `flatMap()` method was introduced in ES6, so if you're testing older browsers or environments, this might not work as expected.

**Other Alternatives**

For an alternative approach, you could also consider using a loop instead of `filter()` and `map()`, like this:
```javascript
arr.forEach(x => {
  if (x % 3 === 0) {
    result.push(x / 100);
  }
});
```
This would avoid the need for methods altogether. However, keep in mind that this approach can be less efficient due to the overhead of the `forEach()` method and the potential for caching issues.

In conclusion, MeasureThat.net provides a simple yet informative benchmarking framework for comparing different approaches to processing arrays in JavaScript. By understanding the options being compared and their pros and cons, developers can gain insights into performance and choose the best approach for their specific use case.

Related benchmarks:

flatmap vs filter-map other (version: 0)

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>

Experimental features:

Fastest: N/A

Slowest: N/A

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