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flatMap vs reduce array generation
(version: 0)
flatMap vs reduce
Comparing performance of:
flatMap vs reduce
Created:
4 years ago
by:
Guest
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Tests:
flatMap
const workFromHour = 13; const workToHour = 23; const timeOptionsList = Array.from({ length: workToHour - workFromHour, }).flatMap((_, index) => { const calculatedIntervalHour = +workFromHour + index; return [{label: `${calculatedIntervalHour}:00`, value: `${calculatedIntervalHour}:00`, }, { label: `${calculatedIntervalHour}:30`, value: `${calculatedIntervalHour}:30`, }, ]; }, []); console.log(timeOptionsList);
reduce
const workFromHour = 13; const workToHour = 23; const timeOptionsList = Array.from({ length: workToHour - workFromHour, }).reduce((acc, _, index) => { const calculatedIntervalHour = workFromHour + index; return [ ...acc, { label: `${calculatedIntervalHour}:00`, value: `${calculatedIntervalHour}:00`, }, { label: `${calculatedIntervalHour}:30`, value: `${calculatedIntervalHour}:30`, }, ]; }, []); console.log(timeOptionsList);
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Suite status:
<idle, ready to run>
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Test case name
Result
flatMap
reduce
Fastest:
N/A
Slowest:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided benchmark and explain what is tested, the options compared, their pros and cons, and other considerations. **Benchmark Overview** The benchmark compares two approaches to generate an array of time intervals: `flatMap` vs `reduce`. The test case uses a simple logic to calculate the interval hours, where each hour has 30 minutes (e.g., 13:00, 13:30, 14:00, etc.). **Options Compared** 1. **`flatMap`**: The `flatMap` method is used to flatten an array of arrays into a single array. In this case, it's used to generate the time intervals. The `flatMap` approach creates a new array with each interval, which can be more efficient than creating intermediate arrays. 2. **`reduce`**: The `reduce` method is used to apply a function to each element in an array and reduce it to a single value. In this case, it's used to generate the time intervals by accumulating arrays. **Pros and Cons** * **`flatMap`**: + Pros: Can be more efficient since it avoids creating intermediate arrays. + Cons: May have higher overhead due to function call and array creation. * **`reduce`**: + Pros: Can be more concise and easier to read, especially for complex transformations. + Cons: May create temporary objects or arrays during iteration. **Other Considerations** * **Memory allocation**: Both approaches allocate memory for the resulting array. However, `flatMap` might have better locality due to the predictable access pattern. * **Cache efficiency**: The choice of approach can affect cache performance, as `flatMap` tends to produce more linear data structures. **Library and JavaScript Features** There are no libraries or special JavaScript features used in this benchmark, only standard ES6 syntax for `flatMap` and `reduce`. **Benchmark Preparation Code** The preparation code is empty (`"Script Preparation Code": null`, `"Html Preparation Code": null`), which means that the test case relies solely on the input data to generate the results. **Alternatives** To compare the performance of different approaches, other alternatives could be: * **`forEach`**: Instead of using `flatMap` or `reduce`, you can use `forEach` with a callback function to iterate over the array and create new elements. * **Array constructor**: You can use the Array constructor (`new Array()`) to create an empty array and then fill it with elements using a loop. * **Loop**: A simple loop using a counter variable can be used to generate the time intervals. These alternatives might not provide a meaningful comparison, as they are less efficient than `flatMap` or `reduce`. However, they could help to demonstrate other aspects of JavaScript performance.
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