Benchmark: json stringify vs array join (string) v2

Script Preparation code:

function moreData(arr, left) {
  if(left === 0) return arr;
  else {
    arr.push("Lorem ipsum dolor sit amet, consectetur adipiscing");
  	return moreData(arr, left - 1);
  }
}
function makeTestData() { return moreData([], 40); }

Tests:

join
makeTestData().join('-')
JSON.stringify
JSON.stringify(makeTestData());

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
join
JSON.stringify

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 and explain what's being tested, compared, and discussed.

**Benchmark Description**

The benchmark is designed to compare two approaches for serializing data: `array.join()` and `JSON.stringify()`. The test case creates an array of 40 elements with a static string value using the `makeTestData` function. This function uses recursion (`moreData`) to populate the array, which is then joined together into a single string or serialized as JSON.

**Options Compared**

Two options are being compared:

1. **Array.join()**: This method concatenates all elements of an array into a single string using the `join()` method with a specified separator (in this case, an empty string).
2. **JSON.stringify()**: This method converts JavaScript objects or arrays to a JSON string.

**Pros and Cons**

Here are some points to consider for each approach:

*   Array.join():
    *   Pros:
        *   Faster execution times in many cases due to its optimized implementation.
        *   Can be more efficient when working with large datasets.
    *   Cons:
        *   Requires the explicit separator parameter, which can add complexity if not used correctly.
        *   May not handle special characters or edge cases as robustly as JSON.stringify().
*   JSON.stringify():
    *   Pros:
        *   More flexible and robust when dealing with complex data structures or special characters.
        *   Less prone to errors due to its more comprehensive validation process.
    *   Cons:
        *   Typically slower execution times compared to array.join().

**Library Used**

In this benchmark, the `JSON` object is used. This is a built-in JavaScript library that provides methods for parsing and generating JSON data.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntaxes being tested in this benchmark.

**Alternative Approaches**

Some alternative approaches to serializing data include:

*   **template literals**: Instead of `join()` or `stringify()`, you can use template literals (`''`) to concatenate strings with variables.
*   **Buffer API**: In certain situations, using the Buffer API might be a better option for serialization, especially when dealing with binary data.

**Benchmark Preparation Code**

The provided script preparation code is quite interesting. It uses recursion (`moreData`) to populate an array of 40 elements with a static string value. This can help reduce the execution time compared to creating and iterating over the array in a single pass.

```javascript
function moreData(arr, left) {
    if (left === 0) return arr;
    else {
        arr.push("Lorem ipsum dolor sit amet, consectetur adipiscing");
        return moreData(arr, left - 1);
    }
}

function makeTestData() {
    return moreData([], 40);
}
```

Latest run results:

Run details: (Test run date: 2 months 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
join	481577.1 Ops/sec
JSON.stringify	273196.4 Ops/sec

Related benchmarks:

json stringify vs array join (string) v2 (version: 0)

Comparing performance of: join vs JSON.stringify

Created: one year ago by: Guest

Jump to the latest result

join

JSON.stringify

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):