Benchmark: Stringify vs join on flat string arrays

Tests:

JSON
const a = [] for(let i = 0; i < 10000; i++) { a.push(i.toString().repeat(10)) } const b = JSON.stringify(a)
join
const a = [] for(let i = 0; i < 10000; i++) { a.push(i.toString().repeat(10)) } const b = a.join()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
JSON
join

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 dive into the explanation of the provided benchmark.

**Benchmark Overview**

The MeasureThat.net website allows users to create and run JavaScript microbenchmarks. The benchmark in question compares two approaches: using `JSON.stringify()` versus joining an array of strings together.

**Test Cases**

There are two test cases:

1. **JSON**: This test case creates an array `a` with 10,000 elements, where each element is a string repeated 10 times using the `toString().repeat(10)` method. The resulting array is then passed to the `JSON.stringify()` function.
2. **join**: This test case is similar to the first one, but instead of using `JSON.stringify()`, it uses the `join()` method to concatenate the strings in the array.

**Library Used: JSON**

The `JSON` library is used in the first test case. `JSON` stands for JavaScript Object Notation, which is a lightweight data interchange format that allows you to represent and exchange data between systems.

In this context, `JSON.stringify()` is used to serialize the array into a string. The resulting string represents the entire array, including its structure and contents. This can be useful in various scenarios, such as storing or transmitting data.

**Pros of using JSON.stringify()**

* It provides a way to represent complex data structures in a human-readable format.
* It's widely supported by most JavaScript implementations.

**Cons of using JSON.stringify()**

* It can be slower than other methods for large datasets due to the overhead of serializing and deserializing the data.
* The resulting string is not as efficient for direct processing or manipulation, such as searching or filtering.

**Pros of using join()**

* It's typically faster than `JSON.stringify()` for joining arrays of strings together.
* It's a built-in method in JavaScript, making it easy to use and access.

**Cons of using join()**

* The resulting string can be very large and may not fit into memory for very large datasets.
* It assumes that the array contains only strings as elements, which might not always be the case.

**Other Alternatives**

If you need to compare or manipulate arrays of strings in JavaScript, other alternatives include:

* Using `Array.prototype.map()`, `Array.prototype.filter()`, and `Array.prototype.reduce()` methods for data processing.
* Utilizing libraries like Lodash or Underscore.js, which provide additional utility functions for working with arrays.
* Employing techniques like string concatenation using the `+` operator or template literals (``${...}``) for joining strings.

In summary, the benchmark compares two approaches to handling large arrays of strings: `JSON.stringify()` and the `join()` method. While both have their advantages and disadvantages, the choice ultimately depends on your specific use case and performance requirements.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36

Browser/OS: Chrome 129 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
JSON	1217.1 Ops/sec
join	1920.0 Ops/sec

Related benchmarks:

Stringify vs join on flat string arrays (version: 0)

Comparing performance of: JSON vs join

Created: one month ago by: Guest

Jump to the latest result

JSON

join

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):