Benchmark: Reduce vs map/join on list of objects

Script Preparation code:

var strings = [];
for (var i=0; i<1000; i++) {
  strings[i] = {
    id: i
  };
}

Tests:

for
var result = ""; for (var i=0; i<strings.length; i++) { result = result+','+strings[i].id; }
reduce
var result = strings.reduce(function(string, i) { return string+','+i; }, ""); result=result.substring(1);
map
var result = strings.map(el => el.id).join(',');
for of
var result = ""; for (var i of strings) { result += ','+i; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for
reduce
map
for of

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 dive into the world of JavaScript microbenchmarks and explore what's being tested on MeasureThat.net.

**Benchmark Definition**

The benchmark definition is a JSON object that describes the test scenario. In this case, it's testing four different approaches to concatenate an array of objects:

* `for`
* `reduce`
* `map`
* `for...of`

Here's a brief description of each approach:

1. **`for`**: This is a traditional loop construct where you iterate over the array using an index (`i`) and access each element individually.
2. **`reduce`**: This is a method that applies a function to each element in the array, accumulating a result. In this case, it's used to concatenate the `id`s of the objects in the array.
3. **`map`**: This method creates a new array with the results of applying a given function to every element in the original array. In this case, it's used to create an array of just the `id`s of the objects.
4. **`for...of`**: This is a newer loop construct that allows you to iterate over arrays and objects using a more concise syntax.

**Options Compared**

The benchmark is comparing the performance of these four approaches on the same input data:

* An array of 1000 objects, each with an `id` property.
* The concatenation result is not important; only the execution time is measured.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

1. **`for`**:
	* Pros: Simple, well-known syntax, works everywhere.
	* Cons: Can be slow and inefficient for large arrays.
2. **`reduce`**:
	* Pros: Efficient, concise syntax, can handle complex transformations.
	* Cons: May have higher overhead due to function calls and accumulator management.
3. **`map`**:
	* Pros: Efficient, concise syntax, can handle complex transformations.
	* Cons: Creates a new array, which can be memory-intensive.
4. **`for...of`**:
	* Pros: Concise syntax, modern and widely adopted.
	* Cons: May not work in older browsers or environments.

**Library and Special JS Features**

None of the test cases use any external libraries or special JavaScript features (e.g., async/await, Promises).

**Other Considerations**

When choosing an approach for concatenating arrays of objects, consider factors like:

* Performance: `reduce` and `map` are generally faster than traditional loops.
* Memory usage: `map` creates a new array, while `reduce` accumulates the result in memory.
* Code readability: Use the approach that best fits your use case and coding style.

**Alternatives**

If you need to concatenate arrays of objects, you might also consider using other approaches like:

* Using `Array.prototype.reduce()` or `Array.prototype.map()`
* Utilizing a library like Lodash or Ramda
* Implementing a custom concatenation function

Keep in mind that the performance and memory trade-offs mentioned earlier still apply.

Related benchmarks:

Reduce vs map/join on list of objects (version: 0)

Comparing performance of: for vs reduce vs map vs for of

Created: 4 years ago by: Guest

Jump to the latest result

for

reduce

map

for of

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):