Benchmark: Take two arrays and merge them using an object key (Map vs. object)

Script Preparation code:

var arr1 = Array(10000).fill(null).map((_, i) => ({
    id: i,
    label: `number ${i}`
}));
var arr2 = Array(10000).fill(null).map((_, i) => ({
    id: i*2,
    label: `number ${i*2}`
}));

Tests:

Merge using object (forEach)
function toMap(arr, key) { const result = {}; arr.forEach((entity) => { const k = entity[key]; result[k] = entity; }); return result; } const first = toMap(arr1, 'id'); const second = toMap(arr2, 'id'); const combined = {...first, ...second};
Using Map
function toMap(arr, key) { return new Map(arr.map(item => ([item[key], item]))); } const first = toMap(arr1, 'id'); const second = toMap(arr2, 'id'); const combined = new Map([...arr1, ...arr2]);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Merge using object (forEach)
Using Map

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 options.

**Benchmark Description**

The benchmark tests two approaches for merging two arrays of objects based on a given key: using an object (specifically, `forEach`) and using a Map data structure.

**Options Compared**

1. **Using Object (`forEach`)**: This approach iterates through each element in the first array (`arr1`) and adds it to the resulting object with its corresponding key from the second array (`arr2`). The process is repeated for each element in `arr2`. This method can be slower due to the overhead of function calls and potential string concatenation.
2. **Using Map**: This approach creates a new Map instance, mapping each item in both arrays to their respective keys, creating an entry for each unique key-value pair.

**Pros and Cons**

**Using Object (`forEach`)**

* Pros:
	+ Simple to implement and understand.
	+ Can be useful when the data structure is not optimized for lookups.
* Cons:
	+ Generally slower due to function call overhead and potential string concatenation.
	+ May lead to performance issues if the input arrays are very large.

**Using Map**

* Pros:
	+ Efficient for lookups, as Maps use a hash table for fast key-value pair retrieval.
	+ Can be faster than using objects when dealing with large datasets.
* Cons:
	+ More complex implementation and may require additional setup (e.g., importing the `Map` class).
	+ May not be suitable for smaller input arrays or situations where memory usage is a concern.

**Other Considerations**

Both approaches have their trade-offs in terms of performance, readability, and maintainability. When working with large datasets, using a Map can provide a significant performance boost due to its efficient lookup capabilities.

When choosing between these options, consider the following factors:

* Data structure characteristics: If your data is optimized for lookups (e.g., a hash table), using a Map might be the better choice.
* Performance requirements: If speed is crucial, using a Map could provide significant benefits.
* Code readability and maintainability: Using objects with `forEach` can make code more accessible to developers without prior experience with Maps.

**Library/Feature Used**

The benchmark uses the following libraries/feature:

* JavaScript's built-in `Array.prototype.forEach()` method, which is used in the "Using Object (`forEach`)" approach.
* JavaScript's built-in `Map` class, which is used in the "Using Map" approach.

No special JavaScript features or syntax are required for this benchmark. However, the use of `const` and template literals (e.g., `${i}`) in the script preparation code demonstrates modern JavaScript best practices.

**Alternative Approaches**

Other approaches to merge two arrays based on a given key include:

1. Using a library like Lodash's `mapValues()` method or Ramda's `mapKeys()` function.
2. Implementing a custom join function using array destructuring and the spread operator (`...`).
3. Utilizing a sorting-based approach, where one array is sorted by the common key and then merged with another array based on that key.

Each of these alternatives has its own trade-offs in terms of performance, readability, and maintainability, similar to the "Using Object (`forEach`)" and "Using Map" approaches.

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.0.0 Safari/537.36

Browser/OS: Chrome 104 on Linux

View result in a separate tab

Test name	Executions per second
Merge using object (forEach)	461.4 Ops/sec
Using Map	255.2 Ops/sec

Related benchmarks:

Take two arrays and merge them using an object key (Map vs. object) (version: 1)

Merge two arrays of objects based on a given key

Comparing performance of: Merge using object (forEach) vs Using Map

Created: 2 years ago by: Registered User

Jump to the latest result

Merge using object (forEach)

Using Map

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):