Benchmark: set.add vs reduce

Tests:

set
const set = new Set() for (let i = 0; i < 1000; i++) { set.add(i) } for (let i = 0; i < 1000; i++) { console.log(set.has(i)) }
reduce
const wordHash = new Array(1000).fill().map((_,i) => i).reduce((hash, char) => { hash[char] = 1; return hash; }, {}); for (let i = 0; i < 1000; i++) { console.log(wordHash[i]) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
set
reduce

Fastest: N/A

Slowest: N/A

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

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Let's break down the provided benchmark and its options.

**Benchmark Overview**

The benchmark, named "set.add vs reduce", tests two approaches for performing operations on large datasets in JavaScript:

1. Using `Set` data structure (specifically, adding elements to a set and checking if an element exists)
2. Using `reduce()` function

**Option 1: Set Data Structure (add)**

* **Purpose**: Create a set containing the numbers 0-999 and then check if each number is present in the set.
* **Library/Functionality**: JavaScript's built-in `Set` object, which provides an efficient way to store unique values.
* **Pros**:
	+ Sets provide fast lookup and insertion operations (average time complexity: O(1)).
	+ This approach avoids unnecessary iterations over large datasets.
* **Cons**:
	+ Creating a set requires initial memory allocation, which might impact performance in some scenarios.
	+ Some older browsers or environments might not support `Set` objects.

**Option 2: Reduce() Function**

* **Purpose**: Create an object where each key is a character from the numbers 0-999 and its value is 1. Then, iterate over the array of numbers to print the corresponding values in the object.
* **Library/Functionality**: JavaScript's built-in `reduce()` function, which applies a reduction function to each element of an array.
* **Pros**:
	+ Reduces memory allocation compared to creating a set.
	+ Can be more flexible if you need to perform different operations on the data.
* **Cons**:
	+ Iterating over the object can be slower than directly accessing elements in the `Set` (average time complexity: O(n)).
	+ This approach requires additional memory for storing the intermediate results.

**Special Considerations**

In this benchmark, there are no special JavaScript features or syntax used beyond what's required to execute these two options. However, it's worth noting that using `reduce()` can be more complex and might lead to unexpected performance issues if not implemented correctly.

**Alternatives**

Other approaches for performing similar operations could include:

* Using a custom data structure, like a hash table or a binary search tree.
* Utilizing parallel processing or multithreading to speed up calculations on large datasets.
* Leveraging browser-specific optimizations or WebAssembly (WASM) for better performance.

Keep in mind that these alternatives might not be directly comparable to the `Set` and `reduce()` approaches, as they introduce additional complexity or require specialized knowledge.

Related benchmarks:

set.add vs reduce (version: 0)

Comparing performance of: set vs reduce

Created: 2 years ago by: Guest

Jump to the latest result

set

reduce

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):