Benchmark: Map vs Array vs Object has uint32 key speed

Script Preparation code:

var map = new Map();
var arr = [];
var obj = {};

var randomU32 = function() {
	return Math.random() * (1 << 31) >>> 0;
}

Tests:

Map
map.has(randomU32(), true);
Array
randomU32() in arr
Object
randomU32() in obj

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map
Array
Object

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

**Benchmark Explanation**

The provided JSON represents a JavaScript microbenchmark test case on MeasureThat.net, which compares the performance of three data structures: `Map`, `Array`, and `Object` with a specific type of key (`uint32`). The benchmark aims to measure how fast these data structures can look up keys.

**Options Compared**

*   **Map**: A built-in JavaScript object that stores key-value pairs. In this case, the `Map` is used to store integer values as keys and arbitrary values as values.
*   **Array**: A built-in JavaScript data structure that stores an ordered collection of elements. In this case, the `Array` is used to store a collection of integer values.
*   **Object**: A built-in JavaScript object that stores key-value pairs. Similar to the `Map`, in this case, the `Object` is used to store integer values as keys and arbitrary values as values.

**Pros and Cons**

*   **Map**: Pros:
    *   Fast lookups for integers due to the use of a compact integer representation (uint32).
    *   Good performance for random key lookups.
*   **Array**: Pros:
    *   Simple implementation with minimal overhead.
    *   Easy to understand and maintain.
*   **Object**: Pros:
    *   Familiar data structure with well-understood behavior.

Cons:

*   **Map**:
    *   May require additional memory to store the map's internal state (hash table).
    *   Can be slower for random key lookups compared to `Map`.
*   **Array**:
    *   Slower performance for random key lookups due to linear search.
    *   May not be as efficient as other data structures like `Map` or `Object` for large datasets.

**Library and Purpose**

There is no specific library mentioned in the benchmark definition. However, it's essential to note that using the `>>> 0` operator on an integer value (`Math.random() * (1 << 31)`), which returns a uint32. This optimization helps reduce memory usage and improves performance for integer lookups.

**Special JS Feature or Syntax**

There is no special JavaScript feature or syntax used in this benchmark definition. The code only uses standard JavaScript constructs like `Map`, `Array`, and `Object`, along with basic arithmetic operations.

**Other Alternatives**

If you're interested in exploring alternative data structures, consider the following:

*   **Set**: A built-in JavaScript object that stores unique values.
*   **WeakMap**: A variant of the `Map` that allows storing weak references to objects.
*   **SortedSet**: An implementation of a sorted set, which can provide faster lookup times for ordered data.

Note that each data structure has its strengths and weaknesses, and choosing the right one depends on your specific use case.

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Linux; Android 9; ONEPLUS A5010) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.116 Mobile Safari/537.36

Browser/OS: Chrome Mobile 79 on Android

View result in a separate tab

Test name	Executions per second
Map	1045960.1 Ops/sec
Array	496363.6 Ops/sec
Object	513230.7 Ops/sec

Related benchmarks:

Map vs Array vs Object has uint32 key speed (version: 0)

Comparing performance of: Map vs Array vs Object

Created: 8 years ago by: Guest

Jump to the latest result

Map

Array

Object

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):