Benchmark: single x multi-pile

Script Preparation code:

var x = [];
for (let i = 0; i < 1000000; i++){
   x.push({key: `key:${i}`});
}

Tests:

Multiple pipe
x.map(item => item.key) .map(name => `Name: ${name}`) .join(',');
Single pipe
x.map(item => `Name: ${item.key}`) .join(',');

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Multiple pipe
Single pipe

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its components.

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark named "single x multi-pile". The script preparation code generates an array `x` with 1,000,000 elements, where each element is an object with a single property `key`. This setup is used to test various string manipulation operations on the data.

**Options Compared**

Two options are compared:

1. **Single pipe**: The benchmark definition for this option uses `map(item => item.key)` followed by `join(',')`. This approach creates an array of strings where each string is a single property value.
2. **Multiple pipes**: The benchmark definition for this option uses two separate `map` operations: one that transforms each object's key to a string (`item => `Name: ${item.key}``) and another that joins the resulting array of strings with commas.

**Pros and Cons**

*   **Single pipe**:
    *   Pros:
        *   Fewer function calls, which can lead to better performance due to reduced overhead.
        *   Can be more efficient for small arrays since it avoids creating an intermediate array.
    *   Cons:
        *   May require more memory allocations or copies, especially if the array grows large.
        *   The `join()` method can still have some overhead depending on the browser's implementation.
*   **Multiple pipes**:
    *   Pros:
        *   Can be more efficient for larger arrays since it avoids creating an intermediate array and uses a single `join()` call later on.
        *   Allows for better code readability, as each operation has a clear purpose.
    *   Cons:
        *   More function calls can increase overhead due to the added complexity.

**Library Usage**

None of the provided benchmark definitions explicitly use any external libraries. The operations are native JavaScript methods or basic string manipulation functions.

**Special JS Features/Syntax**

The only notable feature used in these benchmark definitions is template literals (`${...}`) for string interpolation, which is a relatively modern JavaScript syntax introduced in ECMAScript 2015 (ES6). This allows for more readable and efficient way to format strings using embedded expressions. However, the performance impact of this feature might vary depending on the specific browser implementation.

**Alternative Approaches**

Other possible approaches to compare include:

*   **Array.prototype.reduce()**: Instead of using `map()` followed by `join()`, you could use `reduce()` to accumulate a string from individual elements. This method can be more memory-efficient for large arrays but might have different performance characteristics depending on the browser's implementation.
*   **String concatenation with `+`**: You could concatenate strings directly using the `+` operator, like this: `"Name: ${item.key}" + ", "`. This approach is simple and widely supported but can lead to string copying and overhead due to the repeated concatenations.

When choosing an approach for a benchmark, it's essential to consider factors such as code readability, performance characteristics, memory usage, and potential browser implementation variations.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.81 Safari/537.36

Browser/OS: Chrome 72 on Mac OS X 10.14.2

View result in a separate tab

Test name	Executions per second
Multiple pipe	3.4 Ops/sec
Single pipe	3.4 Ops/sec

Related benchmarks:

single x multi-pile (version: 0)

Comparing performance of: Multiple pipe vs Single pipe

Created: 5 years ago by: Guest

Jump to the latest result

Multiple pipe

Single pipe

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):