Benchmark: test of find - MeasureThat.net

Script Preparation code:

var myArr = ['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'];
var myDict = _.keyBy(myArr);

Tests:

find
if (myArray.find("m")) { console.log("array has 'm'"); }
dict
if (myDict['m']) { console.log("dict has 'm'"); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
find
dict

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 16 days ago):

LLMs can make mistakes. Check important info.

The provided benchmark tests two different approaches for checking the existence of an element ("m") in a collection: using an array method (`Array.prototype.find`) and a dictionary approach leveraging JavaScript objects.

### Overview of Benchmark Options

1. **Using `Array.prototype.find`**:
   - **Test Case**: `if (myArray.find("m"))`
   - **Purpose**: This method searches through the `myArray` array to find an element that matches the specified condition (in this case, the string "m").
   - **Results**: The benchmark results show that this method executed 0 times per second, indicating that it did not succeed or possibly faced an error.

**Pros**:
   - Concise code: The `.find()` method is straightforward and conveys intent clearly.
   - Returns the first matching item (or `undefined` if it doesn't exist).

**Cons**:
   - Performance: The `.find()` method needs to iterate through the array until it finds a match, so its time complexity is O(n). This could become inefficient for very large arrays.
   - If the element is not found, it does not provide any indication of the absence directly; you have to check if the return is `undefined`.

2. **Using a Dictionary (Object) with `_.keyBy`**:
   - **Test Case**: `if (myDict['m'])`
   - **Purpose**: This approach creates a dictionary (`myDict`) where each element of the original array is a key. This allows for quick lookups to check if "m" exists.
   - **Results**: The benchmark results show that lookups using the dictionary executed 629,400.0625 times per second, indicating this method is very fast and efficient.

**Pros**:
   - Performance: Accessing properties in JavaScript objects (dictionaries) is O(1) on average, making it significantly faster than searching through an array.
   - Clear existence check: Simple and effective to check if a key exists.

**Cons**:
   - Memory usage: An object may require more memory compared to a simple array if a large number of keys are stored.
   - Slightly more code: Requires an extra step of setting up the dictionary before performing lookups.

### Library Used

The benchmark preparation code utilizes the `_.keyBy` function from the **Lodash** library, which is a popular utility library in JavaScript. The purpose of `_.keyBy` is to create an object composed of keys generated from the results of running each element of the array through the provided iteratee (here, effectively using the elements of the array itself as keys). This helps in quickly converting an array into a dictionary, facilitating faster lookups.

### Conclusion and Alternative Approaches

In summary, this benchmark provides a comparison of two fundamentally different data structures in JavaScript for checking the existence of elements: a linear search through an array versus a constant-time lookup in a dictionary.

**Other Alternatives**:
- **Set**: Instead of using a plain object, you could use JavaScript's `Set` object for a collection of unique values. Checking for existence in a `Set` is also O(1), providing a similar performance benefit as the dictionary.
- **Native for loop**: A traditional iterative approach using a for loop can be used to check for existence, but it generally will not perform better than `.find()` and lacks the conciseness of the dictionary approach.
- **Map**: Similar to an object, but provides keys of any data type and maintains insertion order, which could be preferable in scenarios where you need to preserve the order of keys.

Ultimately, the choice of method depends on specific use cases, including considerations around performance, readability, and memory usage.

Latest run results:

Run details: (Test run date: 16 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
find	0.0 Ops/sec
dict	629400.1 Ops/sec

Related benchmarks:

test of find (version: 1)

Comparing performance of: find vs dict

Created: 16 days ago by: Guest

Jump to the latest result

find

dict

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 16 days ago):