Benchmark: Test Set versus Array-like object perfomance to get value

Script Preparation code:

var iSet = new Set();
var arr = [];
arr.byNum = {};

for (var i = 0;i++;i<500) {
    if (!arr.byNum[i]) {
      arr.push(i);
      arr.byNum[i] = i;
    }
  	iSet.add(i);
}

Tests:

Array Object
for (var i = 0;i++;i<500) { let a = arr.byNum[i] }
Set
for (var i = 0;i++;i<500) { let a = iSet.get(i) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array Object
Set

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark and explain what is being tested, compared, and the pros and cons of different approaches.

**Benchmark Overview**

The test compares two methods: accessing an element from an array-like object (`arr`) using its index (`byNum` property) and accessing a value from a Set data structure (`iSet`). The goal is to measure the performance difference between these two approaches for retrieving values from large arrays.

**Test Case 1: Array Object**

In this test case, we have:

* `arr.byNum[i]`: an array-like object where each index `i` corresponds to a value in the original array.
* `let a = arr.byNum[i]`: accessing the value at index `i` from the array-like object.

**Test Case 2: Set**

In this test case, we have:

* `iSet.get(i)`: accessing a value from the Set data structure using its key (`i`).
* `let a = iSet.get(i)`: assigning the retrieved value to variable `a`.

**Comparison and Pros/Cons**

The two approaches differ in how they store and retrieve values.

**Array-like Object (Test Case 1)**

Pros:

1. Efficient memory usage: The array-like object only stores the original values, reducing memory overhead.
2. Fast lookups: Accessing an element by index is a constant-time operation for arrays.

Cons:

1. Increased complexity: Creating and maintaining the `byNum` property adds complexity to the data structure.
2. Cache misses: If the value at index `i` is not in cache, accessing it may incur additional overhead (e.g., disk I/O).

**Set (Test Case 2)**

Pros:

1. Simple and intuitive: Sets are a natural data structure for fast lookups.
2. No additional memory overhead: Sets store only the keys (in this case, integers), which reduces memory usage.

Cons:

1. Slower lookup times: Set operations like `get(i)` typically have an average time complexity of O(1) + O(log n), where n is the number of elements in the set.
2. More complex data structure: Sets require additional processing to maintain their integrity (e.g., handling duplicates).

**Library and Purpose**

The JavaScript `Set` object is a built-in data structure that stores unique values, allowing for efficient membership testing and fast lookups.

**Special JS Feature/Syntax**

None mentioned in the provided benchmark code. However, note that some newer JavaScript features like `Map`, `WeakSet`, or `Promise.all()` might be used to optimize or compare performance in different scenarios.

**Alternatives**

Other data structures and approaches could be explored for this benchmark:

1. **Hash Table**: Similar to Sets but can store arbitrary key-value pairs.
2. **Object with indexing**: Implementing an object with indexed properties (e.g., using `Object.create()` and assigning properties) could be another approach.
3. **Custom data structure**: Designing a custom data structure optimized for fast lookups, like a trie or a balanced binary search tree.

These alternatives might offer different performance characteristics, trade-offs in complexity, or even novel solutions to the benchmarking challenge.

Related benchmarks:

Test Set versus Array-like object perfomance to get value (version: 0)

Comparing performance of: Array Object vs Set

Created: 7 years ago by: Guest

Jump to the latest result

Array Object

Set

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):