Benchmark: Large Map vs Object 2

Script Preparation code:

var map = new Map();
var obj = {};
for (let i = 0; i < 100000; i++) {
  const key = Math.random().toString(36).slice(2);
  const value = Math.random().toString(36).slice(2);
  map.set(key, value);
  obj[key] = value;
}
const count = 1000;

Tests:

Map lookup
for (let i = 0; i < 1000; i++) { const key = Math.random().toString(36).slice(2); a = map.get(key); }
Object lookup
for (let i = 0; i < 1000; i++) { const key = Math.random().toString(36).slice(2); a = obj[key]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map lookup
Object lookup

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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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 definition and test cases to understand what is being tested.

**What is being tested?**

The benchmark measures the performance of two data structures: `Map` and plain objects, specifically focusing on their lookup operations (`get()` for Maps and property access for objects).

**Options compared**

Two approaches are compared:

1. **Map Lookup**: This approach uses a `Map` object to store key-value pairs. The test case iterates over 1000 iterations, generating random keys and values using `Math.random().toString(36).slice(2)`. For each iteration, it retrieves the value associated with the generated key using `map.get(key)`.
2. **Object Lookup**: This approach uses a plain object (`obj`) to store key-value pairs. Similar to the Map approach, the test case generates random keys and values and iterates over 1000 iterations, accessing the value associated with each key using `obj[key]`.

**Pros and Cons of each approach**

**Map Lookup:**

Pros:

* Efficient use of memory, as Maps only store unique keys.
* Fast lookup times, as Maps use a hash table data structure.

Cons:

* May require more computational resources for iteration and generation of random keys.
* Might have slower initial setup time due to the creation of the Map object.

**Object Lookup:**

Pros:

* Easier to implement and understand for developers familiar with plain objects.
* Faster initial setup time, as objects can be created without additional overhead.

Cons:

* May lead to slower lookup times if the object has a large number of properties (e.g., collisions).
* Requires more memory to store all key-value pairs.

**Library usage**

The benchmark uses the `Map` data structure from JavaScript's built-in `Object` namespace. The purpose of this library is to provide an efficient way to store and retrieve key-value pairs, with fast lookup times and good memory management.

**Special JS feature or syntax**

The benchmark does not explicitly use any special JavaScript features or syntax beyond what's necessary for the test cases. However, it does rely on the `Math.random()` function, which is a built-in JavaScript function that generates random numbers within a specified range.

**Other alternatives**

If the developers were to modify the benchmark, they might consider alternative approaches, such as:

* Using an external data structure library (e.g., Lodash) for map or object lookup operations.
* Employing caching mechanisms to reduce the number of iterations and improve performance.
* Utilizing parallel processing or multithreading techniques to accelerate computation on multi-core processors.

Keep in mind that these alternatives might introduce additional complexity, dependencies, or overhead, which could affect the benchmark's accuracy and reliability.

Related benchmarks:

Large Map vs Object 2 (version: 0)

Comparing performance of: Map lookup vs Object lookup

Created: 5 years ago by: Guest

Jump to the latest result

Map lookup

Object lookup

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):