Benchmark: Array.includes vs Set.has with large data set

Script Preparation code:

var nums = Array(100000).fill().map((i,n)=>n)

Tests:

Array includes
let smallest=1 while(nums.includes(smallest)){ smallest++ } return smallest
Set has
nums = new Set(nums) let smallest=1 while(nums.has(smallest)){ smallest++ } return smallest

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array includes
Set has

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36

Browser/OS: Chrome 120 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Array includes	2.1 Ops/sec
Set has	118.2 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

The provided benchmark compares the performance of two approaches for checking if an element is present in a large dataset: `Array.includes()` and `Set.has()`. The dataset consists of 100,000 unique numbers generated using `Array(100000).fill().map((i,n)=>n)`.

**Options Compared**

Two options are compared:

1. **Array.includes()**: This method checks if an element is present in the array by iterating through it and checking for a match.
2. **Set.has()**: This method uses a Set data structure to store unique elements, allowing for fast lookups.

**Pros and Cons**

**Array.includes():**

Pros:

* Simple implementation
* Works well with small to medium-sized datasets

Cons:

* Performance degrades significantly as the dataset size increases due to linear search.
* May be slower than `Set.has()` for large datasets.

**Set.has():**

Pros:

* Fast lookups using a Set data structure, making it suitable for large datasets.
* Efficient use of memory, storing only unique elements.

Cons:

* Requires additional memory to store the Set data structure.
* Implementation may be less intuitive for developers without prior experience with Sets.

**Library Used**

The `Set.has()` method uses the built-in `Set` data structure in JavaScript. A Set is a collection of unique values, and the `has()` method checks if an element is present in the set.

**Special JS Feature or Syntax**

No special features or syntax are used in this benchmark. However, it's worth noting that the use of Sets requires a basic understanding of data structures and algorithms in JavaScript.

**Other Alternatives**

1. **Using Array.prototype.indexOf()**: Instead of `Array.includes()`, you can use `Array.prototype.indexOf()` to find the index of an element in the array.
2. **Using LINQ-like libraries**: For larger datasets, libraries like Lodash or Ramda provide more efficient alternatives for working with arrays and Sets.
3. **Native Web Workers**: If performance is critical, using web workers could help offload computationally intensive tasks to separate threads.

**Benchmark Result Interpretation**

The latest benchmark result shows that `Set.has()` performed significantly better than `Array.includes()`, executing approximately 57 times faster on the same dataset. This highlights the advantages of using a Set data structure for fast lookups, especially with large datasets.

Related benchmarks:

Array.includes vs Set.has with large data set (version: 0)

Comparing performance of: Array includes vs Set has

Created: 2 years ago by: Guest

Jump to the latest result

Array includes

Set has

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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