Benchmark: map/join vs reduce objects

Tests:

map/join
const users = [{name: "Alex", age: 27 }, {name: 'Tom', age: 19}, {name: 'Andrew', age: 33}, {name: 'Steve', age: 13}]; const userNames = users.map(user => user.name).join(', ');
reduce
const users = [{name: "Alex", age: 27 }, {name: 'Tom', age: 19}, {name: 'Andrew', age: 33}, {name: 'Steve', age: 13}]; const userNames = users.reduce((acc, val) => acc + ', ' + val.name, '');

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map/join
reduce

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases.

**Overview**

The benchmark compares the performance of two approaches to concatenate arrays of strings in JavaScript: using `map` followed by `join`, and using `reduce`.

**What is being tested?**

The benchmark tests the execution speed of two different methods:

1. **Map + Join**: This approach uses the `map()` method to extract a property (in this case, `name`) from each object in an array, and then uses the `join()` method to concatenate the resulting strings into a single string.
2. **Reduce**: This approach uses the `reduce()` method to accumulate the concatenation of strings from an array of objects.

**Options compared**

The benchmark compares two options:

1. **Map + Join**: This is the first test case, where the `map()` method is used to extract `name` properties and then `join()` is used to concatenate them.
2. **Reduce**: This is the second test case, where the `reduce()` method is used to accumulate the concatenation of strings.

**Pros and Cons**

**Map + Join**

Pros:

* Easy to read and understand
* Flexible, as you can map over any property or value

Cons:

* May be slower due to function call overhead (e.g., creating a new function for `map()` and another for `join()`)
* Requires more memory allocation for intermediate results

**Reduce**

Pros:

* Can be faster due to fewer function calls and less memory allocation
* More efficient for accumulating values

Cons:

* Less readable, especially for those unfamiliar with accumulator functions
* Limited flexibility in applying transformations to each element

**Other considerations**

The benchmark also considers the following factors:

* **JavaScript version**: Although not explicitly mentioned, modern JavaScript engines like V8 (used by Chrome) likely optimize these operations for performance.
* **Array size**: The benchmark doesn't specify a fixed array size. However, larger arrays might affect performance due to increased memory allocation and garbage collection.

**Libraries and special features**

There are no libraries or special features used in this benchmark beyond standard JavaScript methods (`map()`, `join()`, `reduce()`).

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36

Browser/OS: Chrome 112 on Windows

View result in a separate tab

Test name	Executions per second
map/join	12687193.0 Ops/sec
reduce	29760394.0 Ops/sec

Related benchmarks:

map/join vs reduce objects (version: 0)

Comparing performance of: map/join vs reduce

Created: one year ago by: Guest

Jump to the latest result

map/join

reduce

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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