Benchmark: test123-pschild - MeasureThat.net

HTML Preparation code:

<script src='https://unpkg.com/rxjs@6.5.5/bundles/rxjs.umd.min.js'></script>

Script Preparation code:

function onlyEven(value) {return value % 2 == 0;}
function timesTwo(value) {return value * 2;}
function sum(a, b) {return a + b;}

Tests:

js
Array.from(Array(1000000).keys()) .filter(onlyEven) .map(timesTwo) .reduce(sum, 0);
rxjs
let { from } = rxjs; let { filter, map, reduce } = rxjs.operators; from(Array.from(Array(1000000).keys())).pipe( filter(onlyEven), map(timesTwo), reduce(sum, 0) );

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
js
rxjs

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

I'll break down the benchmark and its options for you.

**Benchmark Description**

The test case is designed to measure the performance of two different approaches: using native JavaScript (denoted as "js") versus using the RxJS library (denoted as "rxjs").

**Options Compared**

In this benchmark, we have two main options:

1. **Native JavaScript**: This approach uses only built-in JavaScript functions and methods.
2. **RxJS Library**: This approach utilizes the Reactive Extensions for JavaScript (RxJS) library to perform the computation.

**Pros and Cons of Each Approach**

### Native JavaScript

Pros:

* Typically faster since it doesn't involve additional overhead from a library
* More straightforward to implement and understand, as it relies on standard JavaScript functionality

Cons:

* May not be as efficient or scalable for complex computations due to its inherent limitations in handling parallelism and concurrency
* Requires more manual memory management and error handling

### RxJS Library

Pros:

* Can take advantage of parallel processing and concurrency, potentially leading to significant performance improvements for certain workloads
* Provides a higher-level abstraction, making it easier to manage complexity and write composable code

Cons:

* Introduces additional overhead due to the library itself, which may negate some performance gains
* Requires understanding and familiarity with RxJS-specific syntax and operators

**Library Used**

In this benchmark, the RxJS library is used in its `rxjs.operators` module. Specifically, the following operators are employed:

* `filter`: Selects only elements that meet a condition
* `map`: Transforms each element of an observable sequence by applying a given function
* `reduce`: Combines all items of an array into a single value

**Special JS Features/Syntax**

There is no mention of any special JavaScript features or syntax in this benchmark. Both test cases use standard JavaScript functions and methods, as well as RxJS operators.

**Other Alternatives**

If you wanted to explore alternative approaches, here are some options:

1. **Closure-based parallelization**: This method would utilize closures (anonymous functions) to create multiple iterations of the computation, potentially leveraging parallel processing capabilities.
2. **Web Workers**: Web workers allow for concurrent execution of JavaScript code in separate threads, which could be used to parallelize computations.
3. **Other libraries or frameworks**: Depending on the specific use case and requirements, other libraries like Lodash, underscore.js, or specialized libraries like NumJS (for numerical computations) might be considered as alternatives.

Keep in mind that each alternative would require significant changes to the benchmark setup and testing approach.

I hope this explanation helps you understand the benchmark's design and options!

Related benchmarks:

test123-pschild (version: 0)

test123

Comparing performance of: js vs rxjs

Created: 4 years ago by: Guest

Jump to the latest result

js

rxjs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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