Benchmark: Reduce vs map/join

Script Preparation code:

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

Tests:

for
var result = ""; for (var i in Object.keys(strings)) { result += ' '+i+strings[i]; }
reduce
var result = Object.keys(strings).reduce(function(string, i) { return string+' '+i+strings[i]; }, "");
map
var result = Object.keys(strings).map(function(i) { return i+strings[i]; }).join(' ');

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for
reduce
map

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 5 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) Gecko/20100101 Firefox/148.0

Browser/OS: Firefox 148 on Windows

View result in a separate tab

reduce

17K/s

map

15K/s

for

9K/s

View exact numbers

Test name	Executions per second
✓ reduce	16,790 Ops/sec
map	14,538 Ops/sec
for	9,274 Ops/sec

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 and explain what's being tested.

**Benchmark Overview**

The benchmark compares three different approaches to concatenate strings in JavaScript:

1.  **For Loop**: Iterating over an object using a traditional `for` loop.
2.  **Reduce Method**: Using the `Array.prototype.reduce()` method to concatenate strings.
3.  **Map and Join Methods**: Applying the `String.prototype.map()` method to transform values and then joining them with `String.prototype.join()`.

**Options Compared**

Each option is compared in terms of performance, specifically the number of executions per second (ExecutionsPerSecond) measured on a Safari 11 browser running on a Mac OS X 10.13.4 device.

**Pros and Cons of Each Approach**

*   **For Loop**: This approach is straightforward but can be slower due to overhead from object iteration.
    *   Pros: Easy to understand, no additional library required.
    *   Cons: May have performance issues if not optimized properly.
*   **Reduce Method**: The `reduce()` method provides a concise way to perform operations on arrays. It's often faster than the `for` loop approach because it avoids unnecessary iterations.
    *   Pros: More efficient, takes advantage of JavaScript engines' optimization capabilities.
    *   Cons: May have higher memory usage due to array creation.
*   **Map and Join Methods**: The `map()` method transforms elements in an array, while the `join()` method concatenates these transformed values. This approach can be slower than `reduce()` because it involves two additional operations (map and join).
    *   Pros: Easy to read, takes advantage of JavaScript engines' optimization capabilities.
    *   Cons: May have higher memory usage due to array creation.

**Library Used**

The benchmark uses the built-in JavaScript libraries:

*   `Object.keys()`: Returns an array of a given object's own enumerable property names.
*   `Array.prototype.reduce()`: Applies a function against an accumulator and each element in the array (from left to right) to reduce it to a single value.

**Special JS Feature/Syntax**

This benchmark does not explicitly use any special JavaScript features or syntax, such as ES6 modules, async/await, or arrow functions. It relies on standard JavaScript syntax for all test cases.

**Alternatives**

Other alternatives to consider when concatenating strings in JavaScript include:

*   **Using template literals**: A feature introduced in ECMAScript 2015 that allows embedding expressions inside string literals.
    ```javascript
const result = `${i}${strings[i]}`;
```
*   **Using `Array.prototype.forEach()` and a callback function**: An alternative to the `for` loop approach, which can be more readable but may have performance issues if not optimized properly.
    ```javascript
strings.forEach((value) => {
  result += value;
});
```

Reduce vs map/join (version: 0)

Comparing performance of: `for vs reduce vs map`

Created: 8 years ago by: Guest

Go to the latest result

for

reduce

map

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Reduce vs map/join (version: 0)

Comparing performance of: for vs reduce vs map

Created: 8 years ago by: Guest

Go to the latest result

for

reduce

map

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `for vs reduce vs map`