Benchmark: v晚饭23fwefw - MeasureThat.net

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.20/lodash.min.js'></script>

Script Preparation code:

var a = Array.from(new Array(100), (i,a) => ({id: a}))
var b = Array.from(new Array(10), (b,c) => c)

Tests:

aaaaa
a.map((v) => b.includes(v.id))
vvvvvvv
a.map(v => b.findIndex((id) => _.isEqual(id, v.id)) !== -1)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
aaaaa
vvvvvvv

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 break down the provided benchmarking data for you.

**What is being tested?**

MeasureThat.net is testing two JavaScript microbenchmarks:

1. `a.map((v) => b.includes(v.id))`: This test measures the performance of an array map operation that iterates over a subset of elements ( `a` ) and checks if each element's `id` property exists in another array (`b`). The implementation uses the `includes()` method, which performs a linear search.
2. `a.map(v => b.findIndex((id) => _.isEqual(id, v.id)) !== -1)`: This test measures the performance of an array map operation that iterates over `a` and finds the index of each element's `id` property in `b`. The implementation uses the `findIndex()` method and a custom comparison function `_isEqual()` from the Lodash library.

**Options compared**

The benchmark is comparing two approaches:

1. **Linear search**: The first test (`includes()`) uses a linear search to find if an element's `id` property exists in `b`. This approach has a time complexity of O(n), where n is the size of the array being searched.
2. **Index-based lookup**: The second test (`findIndex()` and `_isEqual()`) uses an index-based lookup to find the index of each element's `id` property in `b`. This approach has a time complexity of O(n) for finding the index, but the comparison function `_isEqual()` may add some overhead.

**Pros and cons**

Here are some pros and cons of each approach:

1. **Linear search (`includes()`)**
	* Pros: Simple to implement, no additional dependencies required.
	* Cons: Time complexity is O(n), which can be slow for large arrays.
2. **Index-based lookup (`findIndex()` and `_isEqual()`)**
	* Pros: Faster time complexity (O(n) + overhead of comparison function), more efficient for larger arrays.
	* Cons: Requires additional dependencies (Lodash library), more complex implementation.

**Other considerations**

The benchmark also mentions the use of Lodash's `isEqual()` function, which is a wrapper around the JavaScript `===` operator that performs a deep equality check. This may add some overhead to the comparison function, but it ensures accurate results for complex data structures.

**Alternatives**

If you need alternative implementations or optimizations, here are a few options:

1. **Use a more efficient linear search algorithm**, such as the "binary search" approach.
2. **Implement an index-based lookup using a hash table**, which can reduce the time complexity to O(1) for large arrays.
3. **Use a different data structure**, such as a Set or a Map, to store the elements of `b` for faster lookups.

Keep in mind that these alternatives may require additional dependencies or more complex implementations.

Related benchmarks:

v晚饭23fwefw (version: 4)

Comparing performance of: aaaaa vs vvvvvvv

Created: 5 years ago by: Registered User

Jump to the latest result

aaaaa

vvvvvvv

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):