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flatMap and forEach with push
(version: 0)
Comparing performance of:
flatMap vs forEach with push
Created:
2 years ago
by:
Guest
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Script Preparation code:
var arr = Array(10_000).fill(0)
Tests:
flatMap
var out = arr.flatMap(x => [x, x]);
forEach with push
var out = []; arr.forEach(x => { out.push(x); out.push(x); });
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
flatMap
forEach with push
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
2 years ago
)
User agent:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36
Browser/OS:
Chrome 119 on Mac OS X 10.15.7
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Test name
Executions per second
flatMap
1265.5 Ops/sec
forEach with push
17055.1 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided benchmark and its test cases. **Benchmark Overview** The provided JSON represents a JavaScript microbenchmark called "MeasureThat.net". The benchmark measures the performance of two different approaches: `flatMap` and `forEach with push`. **Script Preparation Code** The script preparation code is used to set up the environment for the benchmark. In this case, it creates an array `arr` with 10,000 elements filled with zeros: ```javascript var arr = Array(10_000).fill(0); ``` This code is executed before running each test case. **Html Preparation Code** The HTML preparation code is not provided in the benchmark definition, but it's likely used to set up the UI for the benchmark. Since it's empty, we can assume that it doesn't affect the performance of the tests. **Test Cases** There are two individual test cases: 1. **flatMap**: This test case uses the `flatMap` method to transform the array `arr`. The benchmark definition is: ```javascript var out = arr.flatMap(x => [x, x]); ``` The purpose of this method is to apply a transformation function to each element in the array and return a new array with the results. Pros: * Efficient memory usage: `flatMap` avoids creating intermediate arrays and uses the `push` method directly on the result array. * Fast iteration: `flatMap` iterates over the elements using a single loop, making it faster than `forEach`. Cons: * Limited control: The transformation function is applied only once to each element, which might limit its usefulness in certain scenarios. 2. **forEach with push**: This test case uses the `forEach` method to iterate over the array `arr` and pushes each element twice to a new array: ```javascript var out = []; arr.forEach(x => { out.push(x); out.push(x); }); ``` The purpose of this approach is to demonstrate the overhead of using `forEach` with multiple push operations. Pros: * Wide compatibility: `forEach` is widely supported by modern browsers and Node.js. * Easy to understand: This code is straightforward and easy to comprehend. Cons: * Performance overhead: Using `forEach` with multiple push operations can lead to slower performance due to the repeated function calls and memory allocations. **Library** None of the provided test cases uses any external libraries. The `flatMap` method is a built-in JavaScript method, while `forEach` is also a built-in method for iterating over arrays. **Special JS Features or Syntax** There are no special JS features or syntax used in these benchmark tests. Both approaches use standard JavaScript methods and operators. **Other Alternatives** If you're looking to optimize your code or explore alternative approaches, here are some considerations: * **Array.prototype.map()**: Instead of using `flatMap`, you could use the `map()` method with a transformation function that returns an array. However, this approach would create intermediate arrays and might be slower. * **Reduce()**: If you need to perform aggregate operations on the array elements, consider using the `reduce()` method instead of `flatMap` or `forEach`. * **Web workers**: For CPU-intensive tasks like array processing, you could offload the work to web workers for improved performance. Keep in mind that the best approach depends on your specific use case and requirements. Experiment with different methods and libraries to find the most efficient solution for your needs.
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