Benchmark: Object access vs array find vs array filter to 100 data

Script Preparation code:

var items = Array.from(Array(1000), (_,x) => ({key: x, value: x*10}));

var objContainer = {};
var arrContainer = [];

for (let i = 100; i >= 0; i--) {
  const index = Math.floor(Math.random() * 1000);
  const item = items[index];
  objContainer[item.key] = item;
  arrContainer.push(item)
}

Tests:

Object Access
objContainer[88]
Array Find
arrContainer.find((e) => e === 88)
Array Filter
arrContainer.filter((e) => e === 88)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Object Access
Array Find
Array Filter

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36

Browser/OS: Chrome 115 on Linux

View result in a separate tab

Object Access

794.1M/s

Array Find

8.0M/s

Array Filter

5.5M/s

View exact numbers

Test name	Executions per second
✓ Object Access	794,088,384 Ops/sec
Array Find	7,993,579 Ops/sec
Array Filter	5,538,744 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Overview**

The benchmark is designed to compare the performance of three different methods for accessing or filtering data:

1. **Object Access**: Directly accessing an object property using bracket notation (e.g., `objContainer[88]`).
2. **Array Find**: Using the `find()` method to search for a specific element in an array (e.g., `arrContainer.find((e) => e === 88)`).
3. **Array Filter**: Using the `filter()` method to create a new array with elements that satisfy a condition (e.g., `arrContainer.filter((e) => e === 88)`).

**Comparison Options**

The benchmark compares these three methods on a dataset of 1000 objects, where each object has a unique key-value pair. The goal is to measure the execution speed and number of executions per second for each method.

**Pros and Cons**

1. **Object Access**: Pros:
	* Directly accessing an object property can be faster if the property is cached or has a low overhead.
	* Can be more cache-friendly than array methods.
Cons:
	* May require manual indexing, which can lead to slower performance for large datasets.
2. **Array Find**:
Pros:
	* Efficient for finding a single element in an array, as it only needs to traverse a portion of the data.
	* Reduces the risk of incorrect results due to caching issues.
Cons:
	* May have overhead due to the function call and potential caching mechanisms.
3. **Array Filter**:
Pros:
	* Can be more flexible than object access for filtering data, as it allows creating a new array with specific criteria.
	* Can reduce the risk of unintended side effects or over-filtering.

Cons:

* May have overhead due to the function call and potential caching mechanisms.
* Can result in slower performance if the filter condition is complex or expensive.

**Library and Special JS Features**

In this benchmark, no libraries are explicitly mentioned. However, it's essential to note that using built-in JavaScript methods like `Array.prototype.find()` and `Array.prototype.filter()` assumes a modern browser environment with support for these features.

**Other Alternatives**

If you wanted to explore alternative approaches for accessing or filtering data, here are some options:

1. **Using indices**: Instead of object access or array find/filter, you could use manual indexing to directly access specific elements in the dataset.
2. **Caching mechanisms**: Implementing custom caching mechanisms can improve performance by reducing the number of iterations needed to retrieve specific data.
3. **Interpolation**: Using interpolation techniques (e.g., binary search) can provide more efficient filtering methods for large datasets.
4. **Parallel processing**: If you have a multi-core processor, parallelizing certain operations (e.g., array find/filter) can help distribute the workload and reduce overall execution time.

Keep in mind that each approach has its pros and cons, and choosing the right one depends on the specific requirements of your application.

Object access vs array find vs array filter to 100 data (version: 2)

Comparing performance of: `Object Access vs Array Find vs Array Filter`

Created: 2 years ago by: Registered User

Go to the latest result

Object Access

Array Find

Array Filter

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Object access vs array find vs array filter to 100 data (version: 2)

Comparing performance of: Object Access vs Array Find vs Array Filter

Created: 2 years ago by: Registered User

Go to the latest result

Object Access

Array Find

Array Filter

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

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