Benchmark: flatMap vs filter.map

Script Preparation code:

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

Tests:

filter().map()
arr.filter(x => x !== 0 && x % 3).map(x => Math.sqrt(x/100))
flatMap()
arr.flatMap(x => (x !== 0 && x % 3) ? Math.sqrt(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:

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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 explain what's being tested, compared, and analyzed.

**Benchmark Overview**

The benchmark is comparing two approaches to perform a mathematical operation on an array of numbers: `filter()` followed by `map()`, and `flatMap()`. The goal is to determine which approach is faster in terms of execution speed.

**Options Compared**

There are two options being compared:

1. **Filter() + Map()**: This approach filters out elements that don't meet a certain condition (in this case, numbers that are not divisible by 3 and greater than 0) and then applies the `Math.sqrt()` function to each remaining element.
2. **FlatMap()**: This approach applies the same filtering and squaring operation as the first option, but in a single pass using the `flatMap()` method.

**Pros and Cons**

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

1. **Filter() + Map()**:
	* Pros: Easier to understand and implement for developers familiar with these methods.
	* Cons: Requires two separate method calls, which can lead to overhead due to function invocation and parameter passing.
2. **FlatMap()**:
	* Pros: Reduces the number of method calls, potentially reducing overhead and improving performance.
	* Cons: May be less intuitive for developers unfamiliar with this method.

In general, `flatMap()` is often preferred when dealing with arrays because it can simplify the code and reduce the number of iterations. However, in this specific case, both approaches have similar performance characteristics, as shown by the benchmark results.

**Library Used**

There is no library used in this benchmark. The script and HTML preparation codes are minimalistic and rely on standard JavaScript features.

**Special JS Feature or Syntax**

The `flatMap()` method was introduced in ECMAScript 2019 (ES2020) as a part of the Array.prototype API. It provides a concise way to flatten arrays by mapping over them and then flattening the result.

**Benchmark Preparation Code Explanation**

The script preparation code creates an array `arr` with values from 0 to 100,000. The loop iterates `1E5` times, assigning each value to the corresponding index in the array. This is likely done to provide a substantial array size for the benchmark to measure performance differences.

**Individual Test Cases**

Each test case represents one of the two approaches being compared:

* **Filter() + Map()**: Applies filtering and squaring operations sequentially.
* **FlatMap()**: Applies both filtering and squaring operations in a single pass using `flatMap()`.

The benchmark results show that, on this particular platform (Chrome 109, Mac OS X 10.15.7), the difference between the two approaches is minimal, with `filter().map()` outperforming `flatMap()` by a fraction of a second per execution.

**Other Alternatives**

Some alternative approaches to consider:

* Using other data structures, such as `Set` or `Map`, for filtering and mapping.
* Implementing custom loop-based filtering and squaring operations instead of relying on built-in methods like `filter()`, `map()`, and `flatMap()`.
* Utilizing Web Workers or worker threads to offload computationally expensive operations.

Keep in mind that these alternatives may not necessarily improve performance, as they can introduce additional overhead due to memory allocation, garbage collection, or synchronization.

Related benchmarks:

flatMap vs filter.map (version: 0)

flatMap vs filter map

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

Created: 4 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):