Benchmark: List vs Dict - MeasureThat.net

Script Preparation code:

var apiList = [];
var apiDict = {};

function genApiItem(numValue) {
  return {id: numValue, a: numValue + 1};
}

for (var i = 1; i <= 1000; i++) {
  var apiItem = genApiItem(i);
  apiList.push(apiItem);
  apiDict[i] = apiItem;
}

Tests:

Fetch one in list
console.log(apiList.find(a => a.id === 1));
Fetch list
console.log(apiList);
Fetch one in dict
console.log(apiDict[1]);
Fetch dict
console.log(Object.values(apiDict));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Fetch one in list
Fetch list
Fetch one in dict
Fetch dict

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.

The provided JSON represents a JavaScript microbenchmark test case for comparing the performance of fetching an item from an array versus an ID-indexed dictionary.

**Benchmark Definition**

The benchmark is designed to compare the execution time of three different approaches:

1. **Fetch one in list**: This approach uses the `find()` method to retrieve a single item from the `apiList` array.
2. **Fetch list**: This approach simply logs the entire `apiList` array.
3. **Fetch one in dict**: This approach uses the bracket notation (`apiDict[1]`) to retrieve a single item from the `apiDict` dictionary.
4. **Fetch dict**: This approach uses the `Object.values()` method to retrieve an array of values from the `apiDict` dictionary.

**Options being compared**

The benchmark is comparing the performance of these four approaches:

* Array-based approach (Fetch one in list and Fetch list)
* Dictionary-based approach (Fetch one in dict and Fetch dict)

**Pros and cons of each approach**

1. **Array-based approach (Fetch one in list and Fetch list)**
	* Pros:
		+ Fast access to individual elements using indexing.
		+ No need to iterate over the entire array.
	* Cons:
		+ May not be suitable for large datasets, as it requires accessing individual elements sequentially.
		+ Can be slower than dictionary-based approaches for small datasets due to the overhead of array iteration.
2. **Dictionary-based approach (Fetch one in dict and Fetch dict)**
	* Pros:
		+ Fast access to individual elements using bracket notation.
		+ No need to iterate over the entire dataset.
	* Cons:
		+ May not be suitable for large datasets, as it requires accessing individual keys sequentially.
		+ Can be slower than array-based approaches for small datasets due to the overhead of dictionary lookup.

**Library used**

The `Object.values()` method is a built-in JavaScript method that returns an array of values from an object. This library is not explicitly mentioned in the benchmark definition, but it's essential for understanding the Fetch dict approach.

**Special JS feature or syntax**

None are explicitly mentioned in this benchmark definition.

**Other considerations**

* The benchmark uses Safari 13 as the browser and Desktop as the device platform.
* The executions per second value indicates the average number of iterations performed by the browser during each test run.

**Alternatives**

For comparison purposes, other approaches could include:

* Using `for...in` loop to iterate over the array or dictionary
* Using a custom implementation for searching individual elements in the array or dictionary
* Using parallel processing or multithreading to speed up the searches

However, these alternatives may not be directly applicable to this specific benchmark definition.

Related benchmarks:

List vs Dict (version: 0)

Comparing fetching one item in an array to the same in an ID-indexed dictionary.

Comparing performance of: Fetch one in list vs Fetch list vs Fetch one in dict vs Fetch dict

Created: 5 years ago by: Registered User

Jump to the latest result

Fetch one in list

Fetch list

Fetch one in dict

Fetch dict

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):