Benchmark: Map + filter + flat vs Reduce

Script Preparation code:

var inputs = [{
        id: 1,
        type: 'product',
        quantity: 5
    },
    {
        id: 2,
        type: 'product',
        quantity: 2
    },
    {
        id: 3,
        type: 'bundle',
        quantity: 1,
        items: [{
                id: 4,
                type: 'product',
                quantity: 1
            },
            {
                id: 5,
                type: 'product',
                quantity: 1
            },
            {
                id: 6,
                type: 'product',
                quantity: 2
            },
            {
                id: 8,
                type: 'unknown',
                quantity: 2
            }
        ]
    },
    {
        id: 7,
        type: 'product',
        quantity: 1
    },
    {
        id: 8,
        type: 'unknown',
        quantity: 1
    }
]

function extractBundleItems(bundle) {
    return bundle.items.map(item => {
        return {
            item_id: item.id,
            item_type: item.type,
            quantity: item.quantity
        }
    })
}

Tests:

Map + filter + flat
inputs.map((item) => { if (item.type === 'product') { return { item_id: item.id, item_type: item.type, quantity: item.quantity, } } if (item.type === 'bundle') { return extractBundleItems(item) } return null }).filter(Boolean).flat()
Reduce
inputs.reduce((results, item) => { if (item.type === 'product') { results.push({ item_id: item.id, item_type: item.type, quantity: item.quantity, }) } if (item.type === 'bundle') { results.push(...extractBundleItems(item)) } return results }, [],)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map + filter + flat
Reduce

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_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36

Browser/OS: Chrome 116 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Map + filter + flat	1687691.4 Ops/sec
Reduce	9679192.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the provided benchmark definition and explore what's being tested.

**Benchmark Definition**

The benchmark is designed to compare the performance of two approaches: using `map`, `filter`, and `flat` or using `reduce`. The input data consists of an array of objects, each representing a product or bundle. The goal is to extract specific information from these objects (item ID, item type, and quantity) and return it as an array.

**Options being compared**

There are two main approaches:

1. **Map + filter + flat**: This approach uses the `map` method to transform each object into an object with the desired properties, followed by `filter` to remove any null values, and finally `flat` to flatten the resulting array.
2. **Reduce**: This approach uses the `reduce` method to iterate over the input array and accumulate the extracted information in a single array.

**Pros and Cons of each approach**

1. **Map + filter + flat**:
	* Pros: Simple and straightforward, easy to understand for beginners.
	* Cons: May incur additional overhead due to the creation of intermediate arrays, which can lead to slower performance.
2. **Reduce**:
	* Pros: More efficient than `map`, `filter`, and `flat` since it avoids creating intermediate arrays. It also allows for a more concise solution.
	* Cons: May be less intuitive for beginners, as it requires understanding of the accumulator pattern.

**Library usage**

There is no explicit library mentioned in the benchmark definition, but the `extractBundleItems` function is used within the `Map + filter + flat` approach. This function appears to be a custom implementation that extracts bundle items from an object.

However, the `reduce` approach uses the built-in `reduce` method of the Array prototype, which is a standard JavaScript method for reducing arrays to a single value.

**Special JS features or syntax**

There are no special JavaScript features or syntax mentioned in the benchmark definition. The code is written in vanilla JavaScript and relies on standard libraries and methods.

**Other alternatives**

If you're looking for alternative approaches, consider:

* **Using `forEach`**: Instead of `map`, you could use `forEach` to iterate over the array and perform the necessary operations.
* **Using a custom loop**: If you prefer not to use built-in methods like `map`, `filter`, or `reduce`, you can implement a custom loop using traditional JavaScript syntax.

Keep in mind that these alternatives may incur additional overhead or have different performance characteristics compared to the original approach.

Related benchmarks:

Map + filter + flat vs Reduce (version: 0)

Given an array input object

Comparing performance of: Map + filter + flat vs Reduce

Created: one year ago by: Guest

Jump to the latest result

Map + filter + flat

Reduce

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):