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Closest in array
(version: 0)
Comparing performance of:
Reduce vs Map
Created:
9 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
var arr = [1,2,3,4,5,6,7,8,9,10,11,22,33,44,55,66,77,88,99,111,112,114,115,116,400,600,1000];
Tests:
Reduce
var diff = (a, b) => Math.abs(a - b); var closestTo = target => arr => arr.reduce((prev, curr) => diff(prev, target) < diff(curr, target) ? prev : curr ); closestTo(100)(arr);
Map
var closestTo = target => arr => arr .map((num, index) => ({ index, diff: Math.abs(target - num), value: num })) .sort((a, b) => a.diff > b.diff)[0] .value; closestTo(100)(arr);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Reduce
Map
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided JSON and explain what is being tested. **Benchmark Overview** The benchmark tests two approaches for finding the closest number in an array to a target value: using `reduce` and `map`. **Options Compared** Two options are compared: 1. **Reduce Approach**: This approach uses the `reduce` method to iterate over the array and find the closest number to the target. The `reduce` method applies a function to each element of the array, accumulating a result. 2. **Map Approach**: This approach uses the `map` method to transform each element in the array into an object containing the original value, index, and difference from the target. The resulting array is then sorted by the differences, and the first element (which should be the closest) is returned. **Pros and Cons** * **Reduce Approach** + Pros: Often faster for small arrays due to its iterative nature. + Cons: May not be as efficient for large arrays, especially if the array is modified during iteration. * **Map Approach** + Pros: Can be more readable and maintainable, especially for complex transformations. Also, it can handle larger arrays better than `reduce` since it uses a separate array for intermediate results. + Cons: May be slower due to the overhead of creating and sorting an additional array. **Library Used** In both test cases, no specific library is used beyond JavaScript's built-in methods (`Math.abs`, `sort`, etc.). However, some JavaScript features like arrow functions (e.g., `(a, b) => Math.abs(a - b)` in the "Reduce" benchmark definition) are utilized. **Special JS Feature/Syntax** The `map` function and its use with the spread operator (`arr.map(...)`) is a modern JavaScript feature that was introduced in ECMAScript 2015 (ES6). While not strictly necessary for older browsers, it's worth noting that this syntax might be skipped or polyfilled by some implementations to ensure compatibility. **Alternatives** If you were to implement these benchmarks from scratch, you could consider the following alternatives: * Using a different sorting algorithm, like quicksort or mergesort, which might be more efficient for certain use cases. * Employing a caching mechanism to avoid recalculating differences between elements and the target value. * Utilizing parallel processing techniques to take advantage of multi-core processors. Keep in mind that these optimizations would depend on the specific requirements and constraints of your project.
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