Benchmark: isMatch vs every vs int

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

function dec2hex (dec) {
  return dec < 10
    ? '0' + String(dec)
    : dec.toString(16)
}

function generateId (len) {
  var arr = new Uint8Array((len || 40) / 2)
  window.crypto.getRandomValues(arr)
  return Array.from(arr, dec2hex).join('')
}

var a = []
var b = []
for( let i = 0; i < 1000; i++)
{
  a[i] = generateId(16)
  b[i] = generateId(16)
}

Tests:

isMatch
const res = _.isMatch([a], [b])
every
const withEvery = a.every(function(item) { return b.includes(item) })
intersection
const inter = _.intersection(a, b).length

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
isMatch
every
intersection

Fastest: N/A

Slowest: N/A

Latest run results:

No previous 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 what's being tested in the provided JSON data.

**Benchmark Definition**

The benchmark is comparing three different approaches to find the intersection of two arrays: `isMatch`, `every`, and `intersection`. These methods are likely part of the Lodash library, which provides utility functions for JavaScript.

**Options Compared**

1. **`isMatch`**: This method checks if two elements in one array match each other in another array. It's designed to work with objects or arrays of any type.
2. **`every`**: This method returns `true` if every element in an array passes a test. In this case, it's used to check if all elements in the first array (`a`) are present in the second array (`b`) using the `includes` method.
3. **`intersection`**: This method returns the size of the intersection between two arrays.

**Pros and Cons**

1. **`isMatch`**:
	* Pros: works with objects or arrays of any type, can be more efficient for small arrays.
	* Cons: might not be suitable for large arrays due to its object-oriented approach.
2. **`every`**:
	* Pros: easy to understand and implement, can be used in combination with other methods.
	* Cons: requires using the `includes` method, which may have performance implications for large arrays.
3. **`intersection`**:
	* Pros: designed specifically for finding intersections, might be more efficient than manual implementation.
	* Cons: may not be suitable for non-array types or edge cases.

**Lodash Library**

The Lodash library is a popular JavaScript utility library that provides many useful functions for tasks like array manipulation, object transformation, and more. In this benchmark, `isMatch`, `every`, and `intersection` are part of the Lodash library.

**Special JS Feature/Syntax**

There are no special JS features or syntax mentioned in the provided code snippet.

**Alternatives**

If you need to find the intersection of two arrays, you can also use a simple manual implementation using a Set data structure. Here's an example:
```javascript
function intersection(a, b) {
  const setA = new Set(a);
  const setB = new Set(b);
  const result = [];
  for (const item of setA) {
    if (setB.has(item)) {
      result.push(item);
    }
  }
  return result.length;
}
```
This implementation has a time complexity of O(n), making it suitable for large arrays. However, it requires creating two Set instances and using the `has` method, which might have performance implications.

In summary, the benchmark is comparing three different approaches to find the intersection of two arrays: `isMatch`, `every`, and `intersection`. Each approach has its pros and cons, and understanding these differences can help you choose the best solution for your specific use case.

Related benchmarks:

isMatch vs every vs int (version: 0)

Comparing performance of: isMatch vs every vs intersection

Created: 4 years ago by: Guest

Jump to the latest result

isMatch

every

intersection

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):