Benchmark: Map vs Object (large list)

Script Preparation code:

var map = new Map();
var obj = {};

map.set('a', 5);
obj['a'] = 5;

var i = 0, count = 100000, a;

Tests:

Map lookup
for (i = 0; i < count; i++) { a = map.get('a'); }
Obj lookup
for (i = 0; i < count; i++) { a = obj['a']; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map lookup
Obj lookup

Fastest: N/A

Slowest: N/A

Latest 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 and explain what's being tested, compared, and analyzed.

**Benchmark Overview**

The benchmark tests two approaches to access an element in a data structure: using a `Map` (a built-in JavaScript object) versus using an `Object`. The test case uses a large list of 100,000 elements, with each element having a unique key-value pair. The benchmark compares the performance of these two approaches.

**Comparison Options**

The benchmark compares two options:

1. **Map Lookup**: This option uses the `Map` data structure to store the key-value pairs. The `get()` method is used to retrieve the value associated with a given key.
2. **Object Lookup**: This option uses an `Object` (a built-in JavaScript object) to store the key-value pairs. The property access syntax (`obj['key']`) is used to retrieve the value associated with a given key.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

* **Map Lookup**:
	+ Pros: Maps are optimized for fast lookups, especially when dealing with large datasets. They also provide additional features like set operations (e.g., `map.set()`) and iterative methods.
	+ Cons: Maps are less intuitive to use than objects, especially for developers without experience with them. Additionally, some older JavaScript engines may not support maps natively.
* **Object Lookup**:
	+ Pros: Objects are widely supported by all JavaScript engines and have a familiar syntax for most developers. They also provide additional features like property access (e.g., `obj['key']`) and inheritance.
	+ Cons: Object lookups can be slower than map lookups, especially when dealing with large datasets.

**Library**

There is no external library used in this benchmark. The `Map` data structure is a built-in part of the JavaScript language.

**Special JS Feature/Syntax**

The benchmark uses ES6 features, specifically:

* **Template literals**: The `var i = 0, count = 100000, a;` line uses template literals to initialize variables.
* **Arrow functions**: The `for (i = 0; i < count; i++) {\r\n  a = map.get('a');\r\n}` and `for (i = 0; i < count; i++) {\r\n  a = obj['a'];\r\n}` lines use arrow functions to define the loop bodies.

**Other Alternatives**

If you're interested in exploring alternative approaches, consider:

* Using `Set` data structure for lookup operations
* Utilizing third-party libraries like Lodash or Ramda for optimized lookup and manipulation operations
* Implementing a custom lookup algorithm using bitwise operations or other techniques

Keep in mind that these alternatives may not be as efficient or straightforward to use as the original Map and Object approaches.

Related benchmarks:

Map vs Object (large list) (version: 0)

Lookup of map vs object for a large list of elements

Comparing performance of: Map lookup vs Obj lookup

Created: 5 years ago by: Guest

Jump to the latest result

Map lookup

Obj 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):