Benchmark: Map lookup vs array index lookup

Script Preparation code:


var map = new Map();
var arrLookup = [];
var items = [];

for (var i = 0; i < 100; i++) {
  	items[i] = [];
	for (var j = 0; j < 100; j++) {
      	items[i][j] = [i,j];
		if (Math.random() < 0.1) {
        	map.set(i+","+j, Math.random()>=0.5);
          	if (!arrLookup[i]) arrLookup[i] = [];
          	arrLookup[i][j] = Math.random()>=0.5;
		}
	}
}

Tests:

Map lookup
var results = [], i, j; for (i = 0; i < 100; i++) { for (j = 0; j < 100; j++) { if (map.has(i+","+j)) results.push(map.get(i+","+j)); } } if (results.length === 0) throw Error();
Array lookup
var results = [], i, j; for (i = 0; i < 100; i++) { for (j = 0; j < 100; j++) { if (arrLookup[i] && typeof arrLookup[i][j] !== "undefined") results.push(arrLookup[i][j]); } } if (results.length === 0) throw Error();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map lookup
Array lookup

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and its test cases.

**Benchmark Definition JSON**

The benchmark is designed to compare two approaches: using a `Map` data structure for key-value storage versus accessing an array with indexed lookup.

Here's what's being tested:

* A map (`map`) is created, which stores key-value pairs.
* An array (`arrLookup`) is also created, which will be used as an alternative data structure for key-value storage.
* A large dataset of `items` (arrays) is generated, with each item containing another array of 100 elements.
* For each element in the `items` array, there's a 10% chance that the corresponding value in the map or arrLookup will be set. The value is randomly generated and has a 50% chance of being a random number.

**Test Cases**

There are two individual test cases:

1. **Map lookup**: This test case uses the `map` data structure to access its values.
	* The benchmark definition script initializes an empty array `results` to store the retrieved values.
	* It then iterates through each element in the `items` array and checks if a value exists in the map using the `has()` method. If it does, the corresponding value is pushed onto the `results` array using the `get()` method.
2. **Array lookup**: This test case uses the `arrLookup` array data structure to access its values.
	* The benchmark definition script initializes an empty array `results` to store the retrieved values.
	* It then iterates through each element in the `items` array and checks if the corresponding value exists in arrLookup using a conditional statement (`typeof arrLookup[i][j] !== "undefined"`). If it does, the value is pushed onto the `results` array.

**Options Compared**

The two test cases are comparing the performance of:

1. Using a `Map` data structure for key-value storage (Map lookup)
2. Using an array with indexed lookup for key-value storage (Array lookup)

**Pros and Cons**

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

* **Map lookup**
	+ Pros:
		- Faster lookups due to the hash-based search algorithm used by `Map`.
		- Efficient handling of large datasets.
	+ Cons:
		- Requires more memory overhead compared to arrLookup, as it stores additional metadata (key-value pairs).
* **Array lookup**
	+ Pros:
		- Less memory overhead compared to Map, as only the indexed values are stored.
		- Simpler implementation and less dependency on JavaScript's built-in `Map` data structure.
	+ Cons:
		- Slower lookups due to the linear search algorithm used in array iteration.

**Other Considerations**

* **Library usage**: The benchmark uses the built-in `Map` data structure provided by JavaScript. No additional libraries are required for this benchmark.
* **Special JS feature/syntax**: There is no special JavaScript feature or syntax being tested in this benchmark. It's a straightforward comparison of two simple data structures.

**Alternatives**

If you want to explore alternative approaches, consider the following:

1. **Object-oriented lookup**: Instead of using arrays or maps, you could use objects with named properties for key-value storage.
2. **Hash tables**: Implement a custom hash table algorithm and compare its performance to the built-in `Map` data structure.
3. **Bloom filters**: Use Bloom filters as an alternative to `Map` for fast lookups, but at the cost of higher memory usage.

Keep in mind that these alternatives might require significant modifications to your benchmark code.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.198 Safari/537.36

Browser/OS: Chrome 86 on Linux

View result in a separate tab

Test name	Executions per second
Map lookup	476.2 Ops/sec
Array lookup	585.2 Ops/sec

Related benchmarks:

Map lookup vs array index lookup (version: 0)

Comparing performance of: Map lookup vs Array lookup

Created: 7 years ago by: Guest

Jump to the latest result

Map lookup

Array lookup

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):