Benchmark: slice.map vs map

Script Preparation code:

var data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 0];

Tests:

slice with map
data.slice(0, 6).map(x => x + 1);
map only
data.map((x, i) => { if(i > 6) return null return x + 1 }).filter(Boolean);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
slice with map
map only

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.

I'll do my best to explain the JavaScript benchmark provided by MeasureThat.net.

**Benchmark Overview**

The benchmark is comparing two approaches: using `slice()` followed by `map()` (denoted as "slice with map") and using `map()` alone (denoted as "map only").

**Options Compared**

In this benchmark, we have two main options:

1. **Slice + Map**: This approach uses the `slice()` method to create a new array containing a subset of elements from the original array (`data.slice(0, 6)`). Then, it applies the `map()` function to this new array, which transforms each element by adding 1 (`x => x + 1`).
2. **Map Only**: This approach uses the `map()` function directly on the original array without creating a subset first (`data.map((x, i) => { ... })`). The callback function applies the same transformation as in the "slice with map" approach, but it only includes elements where `i > 6`.

**Pros and Cons**

Here are some pros and cons of each approach:

* **Slice + Map**: This approach can be beneficial if:
	+ You need to create a new array that is a subset of the original data.
	+ The transformation function is relatively simple and doesn't depend on the index `i`.
	+ Performance is critical for large datasets, as `slice()` creates a new array without modifying the original one.
* **Map Only**: This approach can be beneficial if:
	+ You only need to apply a transformation function to specific elements in the array (in this case, where `i > 6`).
	+ The transformation function is complex and depends on the index `i`.
	+ Performance is critical for large datasets, as `map()` modifies the original array.

However, keep in mind that:

* **Slice + Map**: This approach creates a new array, which can be more memory-intensive.
* **Map Only**: This approach modifies the original array, which can lead to unexpected side effects if not carefully managed.

**Library/Function**

In this benchmark, there is no specific JavaScript library or framework being used. However, it's worth noting that some versions of Safari (16 in this case) may optimize certain functions, such as `map()`, to work with a feature called **"iterator traps"**, which can affect performance.

**Special JS Features/Syntax**

There are no special JavaScript features or syntax mentioned in the benchmark. The code uses standard JavaScript syntax and features like arrow functions (`=>`), template literals (`\r\n`), and conditional statements (`if`, `return`).

**Alternatives**

If you're interested in exploring alternative approaches, here are a few options:

1. **Lodash**: A popular JavaScript library that provides a `map()` function with various optimization features.
2. **Array.prototype.filter()**: Instead of using `filter(Boolean)`, consider using the more explicit approach with `filter((x) => x !== null)` or `filter(x => x > 0, (x) => x === undefined)`
3. **Native browser optimizations**: Some browsers may optimize certain functions, like `map()`, to work with specific features or techniques (e.g., "iterator traps").

Keep in mind that the best approach will depend on your specific use case and requirements.

Related benchmarks:

slice.map vs map (version: 0)

Comparing performance of: slice with map vs map only

Created: 3 years ago by: Guest

Jump to the latest result

slice with map

map only

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):