Benchmark: map vs obj test3

Script Preparation code:

var map = new Map();
var obj = {};

var value = {
    toto: 'name',
    toto: {
        toto: 'name',
        toto: {
            toto: 'name',
        },
    },
    toto: {
        toto: 'name',
        toto: {
            toto: 'name',
        },
    },
    toto: {
        toto: 'name',
        toto: {
            toto: 'name',
        },
    },
}

for (i = 0; i < 10000; i++) {
    map.set(i, value);
    obj[i] = value
}

Tests:

map
map.get(991) map.delete(980)
obj
obj[991]

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
obj

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:109.0) Gecko/20100101 Firefox/117.0

Browser/OS: Firefox 117 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
map	80720880.0 Ops/sec
obj	742066624.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the benchmark and explain what's being tested, compared options, pros and cons, library usage, special JS features, and alternatives.

**Benchmark Overview**

The provided benchmark measures the performance of JavaScript objects (specifically, arrays) versus Maps in accessing and deleting elements. The benchmark consists of two test cases:

1. `map` test case: It accesses and deletes an element from a Map using the `.get()` and `.delete()` methods.
2. `obj` test case: It accesses an element from an array (an object with numeric keys) using square bracket notation (`[]`) and deleting an element.

**Options Compared**

Two options are compared:

1. **Map**: A built-in JavaScript data structure that stores key-value pairs. Maps provide fast lookup, insertion, and deletion operations.
2. **Object/Array**: An object with numeric keys used as a proxy for an array. This approach is often referred to as "object-based indexing."

**Pros and Cons**

**Map:**

Pros:

* Fast lookup, insertion, and deletion operations (average O(1) time complexity)
* Efficient use of memory for large datasets

Cons:

* May require more memory overhead due to the added data structure
* Can be slower for very small datasets or specific use cases

**Object/Array:**

Pros:

* Simple implementation with minimal overhead
* Fast access and iteration (average O(1) time complexity)

Cons:

* May have slower lookup, insertion, and deletion operations compared to Maps
* Not suitable for large datasets or complex data structures

**Library Usage**

None of the provided benchmark code explicitly uses any external libraries. However, it's worth noting that some JavaScript implementations might use internal libraries or data structures under the hood.

**Special JS Features**

No special JavaScript features or syntax are used in this benchmark. The focus is on comparing the performance of two fundamental data structures: Maps and objects with numeric keys.

**Alternatives**

Other alternatives for accessing and deleting elements include:

1. **Set**: A built-in JavaScript data structure that stores unique values. Sets provide fast lookup, insertion, and deletion operations (average O(1) time complexity).
2. **Array-based implementation with binary search**: An alternative approach to object-based indexing, using binary search to locate elements in the array.
3. **Custom implementations**: Developers can create custom data structures or algorithms tailored to specific use cases or performance requirements.

These alternatives might offer better performance or efficiency for certain scenarios but may come with additional complexity, memory overhead, or trade-offs in terms of simplicity and readability.

Related benchmarks:

map vs obj test3 (version: 0)

Comparing performance of: map vs obj

Created: one year ago by: Guest

Jump to the latest result

map

obj

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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