Benchmark: Map + filter + flat vs Reduce2223235ytt

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 })
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:

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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 explain what is being tested, compared options, pros and cons of each approach, and other considerations.

**Benchmark Overview**

The benchmark measures the performance of two approaches to process an array of objects:

1. `Map + filter + flat`: This approach uses the `map()` method to create a new array with transformed elements, then applies `filter()` to remove unwanted items, and finally uses `flat()` to flatten the resulting array.
2. `Reduce`: This approach uses the `reduce()` method to iterate over the array and accumulate the results.

**Test Case 1: Map + filter + flat**

* **Benchmark Definition**: The test case defines a JavaScript function that extracts relevant data from an object using `map()`, filters out unwanted items, and flattens the resulting array using `flat()`. The input data is an array of objects with different types (`product` or `bundle`) and quantities.
* **Pros**:
	+ Easy to understand and implement for developers familiar with the `map()` and `filter()` methods.
	+ Can handle arrays with mixed types and quantities.
* **Cons**:
	+ May have higher overhead due to the additional method calls and iterations.
	+ Can lead to slower performance if the input array is large or complex.

**Test Case 2: Reduce**

* **Benchmark Definition**: The test case defines a JavaScript function that uses `reduce()` to accumulate the results of processing each item in the array. The output will be an array of objects with extracted data.
* **Pros**:
	+ Can lead to better performance, especially for large input arrays or complex data structures, as it avoids multiple method calls and iterations.
	+ Can be more memory-efficient due to reduced overhead.
* **Cons**:
	+ May require a deeper understanding of the `reduce()` method and its callback functions.
	+ Can become difficult to read and maintain for developers unfamiliar with this approach.

**Library: extractBundleItems**

The `extractBundleItems` function is used within the `Map + filter + flat` test case to process `bundle` objects. This function takes an object as input, extracts relevant data from its `items` property using `map()`, and returns a new array of extracted items.

**Special JS Feature/Syntax: None**

There are no special JavaScript features or syntax used in this benchmark.

**Other Alternatives**

Other approaches that could be compared include:

1. Using `forEach()` with callback functions to iterate over the array.
2. Employing a custom iteration mechanism, such as using `for...of` loops or recursive functions.
3. Utilizing libraries like Lodash or Ramda for more complex data processing and manipulation.

These alternatives might provide different performance profiles or characteristics compared to the `Map + filter + flat` and `Reduce` approaches.

Related benchmarks:

Map + filter + flat vs Reduce2223235ytt (version: 0)

Given an array input object

Comparing performance of: Map + filter + flat vs Reduce

Created: 2 years ago by: Guest

Jump to the latest result

Map + filter + flat

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):