Benchmark: JS Array ref duplication (2)

Script Preparation code:

var baseArray = {}
var refArray = {}

for (let i = 0; i < 5000; i++) {
  baseArray[i] = {
  	x: i,
    y: i%121,
    val: 'test'
  }
}

for (const obj of Object.values(baseArray)) {
  if (refArray[obj.x] === undefined)
    refArray[obj.x] = {}
    
  refArray[obj.x][obj.y] = obj
}

Tests:

Ref access
let x = refArray[4500][120]
Filter access
let x = Object.values(baseArray).filter(e => e.x === 4500 && e.y === 120)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ref access
Filter access

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 provided benchmark definition and test cases to help explain what's being tested.

**Benchmark Definition**

The benchmark measures the performance of JavaScript arrays in accessing data using two different approaches:

1. **Direct reference access**: The first approach, represented by the `Ref access` test case, uses direct reference access to retrieve an object from the `refArray` using its key (`x` and `y`). This involves using array indexing (`refArray[4500][120]`) to access a nested object.
2. **Filtering**: The second approach, represented by the `Filter access` test case, uses filtering to find a specific object in the `baseArray`. It filters objects based on their `x` and `y` properties being equal to 4500 and 120 respectively (`Object.values(baseArray).filter(e => e.x === 4500 && e.y === 120)`).

**Pros and Cons of each approach**

1. **Direct reference access**:
	* Pros: Fast and efficient, as it directly accesses the data without any additional processing.
	* Cons: May not be suitable for large datasets or complex data structures, as it requires precise key matching.
2. **Filtering**:
	* Pros: Suitable for larger datasets or more complex data structures, as it doesn't require direct access to specific keys. It's also more flexible and can handle varying data formats.
	* Cons: Generally slower than direct reference access due to the additional processing required.

**Library usage**

The benchmark uses two libraries:

1. `Object.values()`: This method returns an array of a given object's own enumerable property values. In this case, it's used to get an array of all objects in the `baseArray` for filtering.
2. There is no explicit library usage mentioned in the benchmark definition or test cases.

**Special JS features/syntax**

The benchmark uses some specific JavaScript syntax and techniques:

1. **Template literals**: The `tx` and `\rx` notation in the script preparation code (`\tx` represents a template literal variable) are used to create string templates.
2. **Array initialization**: The benchmark initializes arrays using the `for...of` loop, which is a modern JavaScript feature introduced in ECMAScript 2015 (ES6).

**Other alternatives**

To measure the performance of array access and filtering in JavaScript, alternative approaches could include:

1. Using other data structures like maps or sets for fast lookup and filtering.
2. Implementing custom iteration mechanisms using techniques like `for...in` loops or iterators.
3. Comparing different JavaScript engines or virtual machines (e.g., V8 vs. SpiderMonkey).
4. Creating a microbenchmark that uses multiple threads or concurrent execution to measure performance under load.

In summary, the benchmark measures the performance of direct reference access and filtering in accessing data from JavaScript arrays. The pros and cons of each approach are discussed, along with potential alternatives for further comparison.

Related benchmarks:

JS Array ref duplication (2) (version: 0)

Comparing performance of: Ref access vs Filter access

Created: 6 years ago by: Guest

Jump to the latest result

Ref access

Filter access

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):