Benchmark: map vs queryselectorall

HTML Preparation code:

<div class="name"><div class="name"><div class="name">

Tests:

map
[...document.querySelectorAll('.name')].map(element => { console.log(element); });
queryselectorall
document.querySelectorAll('.name').forEach(element => { console.log(element); });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
queryselectorall

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/91.0.4472.124 Safari/537.36

Browser/OS: Chrome 91 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
map	19843.3 Ops/sec
queryselectorall	24795.7 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down what's being tested in the provided JSON benchmark.

**Benchmark Definition:**

The two test cases are designed to compare the performance of `Array.prototype.map()` and `document.querySelectorAll()`. The goal is to measure which approach is faster when applying a function to every element in an array created from the `.name` elements in the HTML.

**Options being compared:**

1. **map**: This method creates a new array with the results of applying the provided function to each element in the original array.
2. **querySelectorAll**: This method returns a NodeList (a live HTML collection of node(s)) that can be used to access all elements that match the specified CSS selector.

**Pros and Cons:**

* `map`:
	+ Pros:
		- Creates a new array, which can be useful for operations that involve filtering or sorting.
		- Allows for more functional programming style (i.e., declarative programming).
	+ Cons:
		- Creates an additional copy of the original data, potentially impacting performance and memory usage.
		- May incur overhead due to the creation of a new array object.
* `querySelectorAll`:
	+ Pros:
		- Returns a live collection of nodes, which can be more efficient than creating a new array.
		- Can be used for more complex queries, such as selecting multiple elements or attribute-based filtering.
	+ Cons:
		- Does not create a new array; instead, it returns a NodeList that must be iterated over explicitly (using `forEach`, `forEachElement`, etc.).
		- May incur overhead due to the need to parse the CSS selector and iterate over the resulting nodes.

**Other considerations:**

* The benchmark uses Chrome 91 on a Mac OS X 10.15.7 device, which may affect the results due to browser-specific optimizations or platform differences.
* The use of `console.log` statements for logging purposes may impact performance, as it can cause additional overhead and synchronization issues.

**Library/Language features used:**

None, but it's worth noting that modern JavaScript engines (like V8) have improved support for functional programming concepts like `map()` and array methods in general.

**Special JS feature/syntax:**

None mentioned, but the use of the arrow function (`=>`) is a relatively recent addition to JavaScript (introduced in ECMAScript 2015).

Now, let's look at some alternative approaches:

* **Other array methods**: You could also test `forEach`, `filter`, or other array methods to compare their performance with `map` and `querySelectorAll`.
* **Native Web APIs**: Instead of using `.map()` or `.querySelectorAll()`, you could use native Web APIs like `HTMLCollection.prototype.item()` or `CSSRuleList.prototype.item()` to access individual elements.
* **Alternative DOM traversal methods**: You could also test the performance of other DOM traversal methods, such as `document.querySelectorAll` with a different CSS selector or using `Element.contains()` to check for element presence.

Related benchmarks:

map vs queryselectorall (version: 0)

Comparing performance of: map vs queryselectorall

Created: 3 years ago by: Guest

Jump to the latest result

map

queryselectorall

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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