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Map + filter + flat vs Reduce
(version: 0)
Given an array input object
Comparing performance of:
Map + filter + flat vs Reduce
Created:
2 years ago
by:
Guest
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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>
Run tests (2)
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Test case name
Result
Map + filter + flat
Reduce
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
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.
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