Benchmark: Map.get versus Array.find for 1000 elements

Script Preparation code:

data = [...Array(1000)].map((_, id) => ({ id, data: Math.random() }))
map = new Map(data.map(v => [v.id, v]))

Tests:

Map.get
const res = map.get(50)
Array.find
const res = data.find(({ id }) => id === 50)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map.get
Array.find

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its components.

**Benchmark Definition**
The benchmark is defined in JSON format, which describes two individual test cases: `Map.get` and `Array.find`. The benchmark is designed to measure the performance difference between these two approaches when searching for a specific element in an array.

**Script Preparation Code**
The script preparation code generates an array of 1000 elements using the `Array.from()` method and maps over it to create an object with an ID and some random data. A new Map object is created from this data, where each key-value pair consists of the ID as the key and the corresponding object as the value.

**Options Compared**
The two options being compared are:

1. **`Map.get()`**: This method retrieves the value associated with a given key in a Map object.
2. **`Array.find()`**: This method finds the first element in an array that satisfies a provided testing function.

**Pros and Cons**

* `Map.get()`: Pros:
	+ Fast lookups, with an average time complexity of O(1) in modern JavaScript engines.
	+ Efficient for large datasets.
Cons:
	+ Limited to Map objects only.
	+ May not be as intuitive to use for developers without experience with Maps.
* `Array.find()`:
	+ More widely supported and understood by developers, as it's a common array method.
	+ Can be used in non-Map scenarios, such as searching through arrays or other collections.
Pros:
	+ Widely supported and easily understandable.
Cons:
	+ Slower than `Map.get()`, with an average time complexity of O(n) for large datasets.

**Library and Purpose**
No libraries are explicitly mentioned in the benchmark definition. However, JavaScript's built-in `Map` object is used to store data, and `Array.find()` is a standard array method provided by modern JavaScript engines.

**Special JS Features or Syntax**
None are mentioned specifically in this benchmark.

**Other Considerations**

* The benchmark measures execution speed (`ExecutionsPerSecond`) but not memory usage or other performance metrics.
* The dataset size (1000 elements) might be too small to accurately represent real-world scenarios, and larger datasets may show different results.

**Alternatives**

For `Array.find()`, alternative approaches could include:

1. `filter()` followed by indexing the resulting array: `data.filter(({ id }) => id === 50)[50]`.
2. Using a custom search algorithm that iterates over the array.

For `Map.get()`, alternative approaches could include:

1. Using other lookup methods, like `Array.prototype.indexOf()` or `Set` data structures.
2. Implementing a custom hash-based search algorithm.

Keep in mind that these alternatives might not offer significant performance improvements for this specific benchmark and may introduce additional complexity.

Latest run results:

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

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) SamsungBrowser/25.0 Chrome/121.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 121 on Android

View result in a separate tab

Test name	Executions per second
Map.get	4531271.5 Ops/sec
Array.find	3236547.5 Ops/sec

Related benchmarks:

Map.get versus Array.find for 1000 elements (version: 0)

Comparing performance of: Map.get vs Array.find

Created: one year ago by: Guest

Jump to the latest result

Map.get

Array.find

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):