Benchmark: reduce vs map and set

Script Preparation code:

var testArray = [];

// Create test data with duplicate tokenIds
for (let i = 0; i < 10000; i++) {
    testArray.push({
        tokenId: Math.floor(Math.random() * 1000)
    });
}

Tests:

reduce
console.time('reduce'); var tokenIdsReduce = testArray.reduce((acc, { tokenId }) => { if (!acc.includes(tokenId)) { acc.push(tokenId); } return acc; }, []); console.timeEnd('reduce'); console.log('Token IDs (reduce):', tokenIdsReduce);
map-set
console.time('map-set'); var tokenIdsMapSet = [...new Set(testArray.map(({ tokenId }) => tokenId))]; console.timeEnd('map-set'); console.log('Token IDs (map-set):', tokenIdsMapSet);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce
map-set

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:109.0) Gecko/20100101 Firefox/110.0

Browser/OS: Firefox 110 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
reduce	347.1 Ops/sec
map-set	3768.3 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

The provided benchmark is designed to compare the performance of two approaches for getting unique values from an array: using the `reduce` method and using the `map` function in conjunction with a `Set` data structure.

**Options Compared**

Two options are compared:

1. **Reduce Method**: This approach uses the `reduce` method, which accumulates a value by applying a function to each element of the array.
2. **Map-Set Approach**: This approach uses the `map` function to transform each element into a unique token ID, and then creates a new set from the resulting array. The `Set` data structure automatically eliminates duplicates.

**Pros and Cons**

### Reduce Method

Pros:

* Simple and concise implementation
* No additional memory allocation required

Cons:

* Can be slower than the map-set approach due to the overhead of the reduce function
* May perform poorly for large arrays or arrays with a high number of duplicates

### Map-Set Approach

Pros:

* Typically faster than the reduce method, especially for large arrays or arrays with a high number of duplicates
* More memory-efficient, as only unique values are stored in the set

Cons:

* Requires more memory allocation and processing power compared to the reduce method
* More complex implementation due to the use of map and set data structures.

**Library Used**

In both test cases, no external libraries are used. However, the `Set` data structure is a built-in JavaScript object that can be used to eliminate duplicates from an array.

**Special JS Feature or Syntax**

No special JavaScript features or syntax are used in this benchmark.

**Other Alternatives**

Alternative approaches for getting unique values from an array include:

1. **Array.prototype.filter**: This method can be used to filter out duplicate elements, but it may not be as efficient as the map-set approach.
2. **Set.fromArray**: This method creates a new set from an array, eliminating duplicates automatically.
3. **Deduplication using a custom implementation**: A custom implementation using a data structure such as a hash table or a trie can also be used to eliminate duplicates.

In summary, the benchmark compares two common approaches for getting unique values from an array: using the `reduce` method and using the `map` function in conjunction with a `Set` data structure. The map-set approach is typically faster and more memory-efficient, but requires more complex implementation.

Related benchmarks:

reduce vs map and set (version: 0)

get unique values

Comparing performance of: reduce vs map-set

Created: one year ago by: Guest

Jump to the latest result

reduce

map-set

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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