Benchmark: Map vs Object reduce

Script Preparation code:

var arr = Array.from({
    length: 1000
}, (_, i) => i);

Tests:

Map
arr.reduce((map, i) => map.set(i, i), new Map());
Object assignment
arr.reduce((obj, i) => { obj[i] = i; return obj; }, {});
Object spread
arr.reduce((obj, i) => ({ ...obj, [i]: i }), {});
Object.assign
arr.reduce((obj, i) => Object.assign(obj, { [i]: i }), {});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map
Object assignment
Object spread
Object.assign

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

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Let's dive into the world of JavaScript microbenchmarks!

**Benchmark Overview**

The provided JSON represents a benchmark that compares four different approaches to reduce an array and create an object: `Map`, `Object assignment` (using the spread operator), `Object spread`, and `Object.assign`.

**Approaches Compared**

Here's a brief description of each approach:

1. **Map**: Creates a new Map object and iterates over the array, adding each element as a key-value pair to the map.
2. **Object assignment**: Uses the spread operator (`{...obj}`) to create a shallow copy of the `obj` object and then iterates over the array, assigning each element to the corresponding property in the copied object.
3. **Object spread**: Similar to Object assignment, but uses the spread operator (`{ ...obj }`) instead of the spread syntax (`{ ...obj, [i]: i }`).
4. **Object.assign**: Uses the `Object.assign()` method to create a shallow copy of an object and then iterates over the array, assigning each element as a property in the copied object.

**Pros and Cons**

Here are some pros and cons for each approach:

1. **Map**:
	* Pros: Efficient use of memory, fast lookup times.
	* Cons: May not be suitable for large datasets due to memory constraints.
2. **Object assignment** (with spread operator):
	* Pros: Fast and efficient, can handle large datasets.
	* Cons: Creates a shallow copy of the original object, which might lead to unexpected behavior if the original object has nested objects or arrays.
3. **Object spread**:
	* Pros: Similar performance characteristics to Object assignment, but avoids creating a shallow copy.
	* Cons: May be slightly slower than Object assignment due to the additional operation.
4. **Object.assign**:
	* Pros: Easy to use and intuitive syntax.
	* Cons: May not be suitable for large datasets due to its limited memory allocation.

**Library/Module Used**

None of the above approaches rely on any specific library or module beyond basic JavaScript features. However, it's worth noting that modern browsers may optimize certain implementations (e.g., Object assignment) using internal array and object methods.

**Special JS Features/Syntax**

The benchmark uses a few advanced JavaScript features:

1. **Spread operator (`{...obj}`)**: Introduced in ECMAScript 2015 (ES6), this syntax creates a shallow copy of an object.
2. **Arrow functions**: Used to define the callback function for the `reduce()` method.

**Other Alternatives**

If you're interested in exploring alternative approaches, consider:

1. **Lodash's `_.mapValues()`**: A utility function that maps values to new keys in an object.
2. **Array.prototype.reduce() with a custom accumulator**: You could implement your own reducer function using a custom accumulator and iterate over the array.

Keep in mind that these alternatives might have different performance characteristics or requirements for certain use cases.

I hope this explanation has been helpful! If you have any further questions, feel free to ask.

Related benchmarks:

Map vs Object reduce (version: 0)

Comparing performance of: Map vs Object assignment vs Object spread vs Object.assign

Created: 5 years ago by: Guest

Jump to the latest result

Map

Object assignment

Object spread

Object.assign

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):