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Array.Sort vs Math.Min-Max
(version: 0)
Comparing performance of:
Math.Min - Math.Max vs Array.Sort
Created:
4 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
// Create an array of 100,000 numbers (0 - 99,999) var arr = Array.from(Array(100000).keys()); // Knuth Shuffle Function function shuffle(array) { var currentIndex = array.length, temporaryValue, randomIndex; while (0 !== currentIndex) { randomIndex = Math.floor(Math.random() * currentIndex); currentIndex -= 1; temporaryValue = array[currentIndex]; array[currentIndex] = array[randomIndex]; array[randomIndex] = temporaryValue; } return array; } // Randomize Order shuffle(arr);
Tests:
Math.Min - Math.Max
var max = Math.max(...arr); var min = Math.max(...arr);
Array.Sort
arr = arr.sort(function(a, b) { return a - b; }); var max = arr[arr.length]; var min = arr[0];
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Math.Min - Math.Max
Array.Sort
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/128.0.0.0 Safari/537.36
Browser/OS:
Chrome 128 on Mac OS X 10.15.7
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Test name
Executions per second
Math.Min - Math.Max
1289.6 Ops/sec
Array.Sort
388.1 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into the world of microbenchmarks! **Benchmark Definition** The benchmark measures the performance difference between two approaches: `Math.Min-Max` and `Array.Sort`. Both methods are used to find the minimum and maximum values in an array. **Options Compared** There are two options being compared: 1. **Math.Min-Max**: This method uses the built-in `Math.max()` function twice to find both the minimum and maximum values in the array. 2. **Array.Sort**: This method sorts the entire array using the `sort()` function with a custom comparator, which returns the difference between two elements (`a - b`). After sorting, it finds the first element (minimum) and the last element (maximum). **Pros and Cons** **Math.Min-Max** Pros: * Simple and straightforward implementation * No overhead of sorting the entire array Cons: * Requires two function calls, which can be expensive in terms of performance * Does not take advantage of any potential parallelization or caching **Array.Sort** Pros: * Takes advantage of sorting algorithms' ability to find both minimum and maximum values in a single pass * Can potentially leverage hardware optimizations (e.g., SIMD instructions) Cons: * Requires sorting the entire array, which can be slower for large datasets * Custom comparator function may introduce additional overhead **Other Considerations** * Both methods assume that the input array contains distinct elements. If there are duplicates, the results may not be accurate. * The `Array.Sort` method is sensitive to the initial order of elements in the array. A different starting point can lead to different results. **Library: Knuth Shuffle Function** The `shuffle()` function used in the benchmark preparation code is a simple randomized shuffle algorithm that rearranges the elements of an array. Its purpose is to randomize the order of the elements, which is often necessary when running benchmarks or tests on arrays. **Special JS Feature/Syntax: None** There are no special JavaScript features or syntaxes being used in this benchmark. **Alternatives** If you wanted to explore alternative approaches, here are a few options: 1. **Use `Array.prototype.reduce()`**: Instead of sorting the array and then finding the minimum and maximum values, you could use `Array.prototype.reduce()` with a custom callback function to find both values in a single pass. 2. **Use `Array.prototype.every()` and `Array.prototype.some()`**: You could use these methods to check if all elements are greater than or equal to the minimum value and some element is less than or equal to the maximum value, respectively. 3. **Use a custom sorting algorithm**: If you're interested in exploring different sorting algorithms, you could try implementing a hybrid sorting algorithm that combines elements of quicksort, mergesort, and heapsort. Keep in mind that each alternative approach may introduce additional complexity, overhead, or assumptions about the input data.
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