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 = 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(string, 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:

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Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):

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**Benchmark Overview**

The benchmark tests the performance of three different approaches to concatenating strings: `Reduce`, `Map/Join`, and `For Loop`.

**Test Case 1: For Loop**

* **Library**: None
* **Special JS feature or syntax**: None
* **Description**: The test case uses a simple `for` loop to iterate over the keys of an object (`strings`) and concatenate strings.
* **Pros/Cons**: Pros - easy to understand, straightforward. Cons - may not be efficient for large datasets, as it iterates over the entire array on each iteration.

**Test Case 2: Reduce**

* **Library**: Built-in `Array.prototype.reduce()` method
* **Special JS feature or syntax**: None
* **Description**: The test case uses the `reduce()` method to concatenate strings. It provides an initial value (`""`), a callback function that takes two arguments (the accumulator and the current element), and returns the concatenated string.
* **Pros/Cons**: Pros - efficient, concise code; reduces memory usage by iterating only over the array once. Cons - may be less intuitive for developers without experience with `reduce()`.

**Test Case 3: Map/Join**

* **Library**: Built-in `Array.prototype.map()` and `String.prototype.join()` methods
* **Special JS feature or syntax**: None
* **Description**: The test case uses the `map()` method to create a new array of concatenated strings, and then joins them into a single string using the `join()` method.
* **Pros/Cons**: Pros - easy to understand, clear intent; may be more efficient than `reduce()` for small datasets. Cons - creates an intermediate array, which can lead to memory issues for large datasets.

**Benchmark Results**

The latest benchmark results show that:

* The `Reduce` approach performs the best, with 13726.83 executions per second.
* The `Map/Join` approach follows closely, with 9700.31 executions per second.
* The `For Loop` approach lags behind, with 7139.72 executions per second.

**Alternatives**

Other alternatives to concatenate strings include:

* Using a loop and concatenating strings directly (`string += anotherString;`)
* Utilizing a string builder library (e.g., `StringBuilder` in Java or C#)
* Employing an efficient string concatenation algorithm, such as the one used in the `reduce()` method

Keep in mind that the best approach depends on the specific use case and requirements.

Related benchmarks:

Reduce vs map/join (version: 0)

Comparing performance of: for vs reduce vs map

Created: 7 years ago by: Guest

Jump to the latest result

for

reduce

map

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):