Benchmark: reduce vs map+reduce

Tests:

Reduce
const people = [ { id: 1, name: "Aaron" }, { id: 2, name: "Amy" }, { id: 3, name: "Andy" }, { id: 4, name: "Arnaud" }, ]; const reduced = people.reduce((acc, curr) => { const { id, ...rest } = curr; acc[id] = { ...rest, }; return acc; }, {});
Map+Reduce
const people = [ { id: 1, name: "Aaron" }, { id: 2, name: "Amy" }, { id: 3, name: "Andy" }, { id: 4, name: "Arnaud" }, ]; const reduced = people .map((p) => { const { id, ...rest } = p; return { [p.id]: rest, }; }) .reduce((acc, curr) => Object.assign(acc, curr), {});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Reduce
Map+Reduce

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.

Let's break down the provided benchmark definition and results.

**Benchmark Definition:**

The benchmark is comparing two approaches to transform an array of objects into a new object with only the `id` property:

1. **Reduce**: The `reduce()` method applies a function against an accumulator and each element in the array (from left to right) to reduce it to a single value.
2. **Map+Reduce**: This approach uses two methods:
	* `map()`: Transforms each element in the array into a new object with only the `id` property.
	* `reduce()`: Accumulates the resulting objects from the `map()` operation into a single object.

**Options being compared:**

The benchmark is comparing the performance of these two approaches:

1. **Reduce**: Uses the `reduce()` method to transform the array directly, which may be more efficient due to its ability to accumulate intermediate results.
2. **Map+Reduce**: Uses a combination of `map()` and `reduce()` methods, which may lead to slower performance due to the overhead of function calls and object creation.

**Pros and Cons:**

1. **Reduce**:
	* Pros:
		+ May be more efficient due to its ability to accumulate intermediate results.
		+ Simplifies the transformation process.
	* Cons:
		+ Can be less intuitive for developers who are not familiar with this approach.
2. **Map+Reduce**:
	* Pros:
		+ Allows for a more modular and reusable code structure.
		+ Can be easier to understand for developers familiar with `map()` and `reduce()`.
	* Cons:
		+ May lead to slower performance due to function calls and object creation.

**Library usage:**

None of the provided benchmark definitions use any external libraries. The JavaScript features used are:

1. **Array.prototype.reduce()**: Used in the "Reduce" approach.
2. **Array.prototype.map()**: Used in the "Map+Reduce" approach.
3. **Object.assign()**: Used in the "Map+Reduce" approach to accumulate the resulting objects.

**Special JS feature or syntax:**

None of the provided benchmark definitions use any special JavaScript features or syntax beyond the standard array and object methods.

**Alternatives:**

Other approaches to transform an array of objects into a new object with only the `id` property could include:

1. **Using a loop**: Implementing a simple loop to iterate through the array and create a new object.
2. **Using a library function**: Utilizing a library function, such as Lodash's `mapValues()` or `reduce()`, to perform the transformation.

Keep in mind that these alternatives may have different performance characteristics and trade-offs compared to the "Reduce" and "Map+Reduce" approaches.

Related benchmarks:

reduce vs map+reduce (version: 0)

Comparing performance of: Reduce vs Map+Reduce

Created: 4 years ago by: Guest

Jump to the latest result

Reduce

Map+Reduce

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):