Toggle navigation
MeasureThat.net
Create a benchmark
Tools
Feedback
FAQ
Register
Log In
red test
(version: 0)
Comparing performance of:
flatmap vs concat
Created:
5 years ago
by:
Registered User
Jump to the latest result
Script Preparation code:
var arr = [1, 2, 3, 4];
Tests:
flatmap
arr.flatMap(x => [x, x * 2]);
concat
arr.reduce((acc, x) => acc.concat([x, x * 2]), []);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
Fork
Test case name
Result
flatmap
concat
Fastest:
N/A
Slowest:
N/A
Latest run results:
No previous run results
This benchmark does not have any results yet. Be the first one
to run it!
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided benchmark definition and individual test cases. **Benchmark Definition JSON** The `Script Preparation Code` is used to prepare the JavaScript environment for the benchmark. In this case, it creates an array `arr` with four elements: `[1, 2, 3, 4]`. This code is executed once before each benchmark to ensure a consistent starting point. **Individual Test Cases** The two test cases are: 1. **flatmap**: The benchmark definition uses the `flatMap()` method on the `arr` array, which returns a new array with the results of calling the provided callback function for each element in the original array. In this case, the callback function takes an element `x` and returns `[x, x * 2]`. This creates two elements: `[1, 2]` and `[3, 6]`. Pros: * Easy to understand and use * Fast execution Cons: * May have performance issues due to overhead of creating new arrays * Not suitable for large datasets or complex transformations 2. **concat**: The benchmark definition uses the `reduce()` method on the `arr` array with an initial value of an empty array `[]`. The callback function takes two arguments: `acc` (the accumulator) and `x` (the current element). It concatenates `[x, x * 2]` to the accumulator. This creates a single-element array for each iteration. Pros: * Suitable for large datasets or complex transformations * Can be more efficient than flatMap due to fewer overheads Cons: * More verbose and harder to read compared to flatMap * May have performance issues due to concatenating arrays **Library Usage** There is no library used in the provided benchmark definition. The `flatMap()` and `reduce()` methods are built-in JavaScript methods. **Special JS Feature or Syntax** The benchmark definition uses arrow functions, which are a concise way to define small anonymous functions. They are also more memory-efficient than traditional function declarations. Other alternatives for the `flatMap` method could be: * `map()`: Creates a new array with the results of calling the provided callback function for each element in the original array. However, this would require more iterations and overhead compared to flatMap. * Loops: A simple loop can achieve the same result as flatMap, but it's more verbose and harder to read. For the `concat` method: * Other methods like `push()` or `splice()` could be used instead of reducing concatenating arrays. However, these methods may not provide the same level of performance and readability as reduce(). **Other Alternatives** If you wanted to write similar benchmarks for other JavaScript features or libraries, here are some alternatives: * Instead of `flatMap()`, consider using `map()` with a loop that accumulates the results. * Instead of `reduce()`, consider using a loop or the spread operator (`...`) to concatenate arrays. * For libraries like Lodash, you could use their equivalent functions (e.g., `lodash.flatMap()` instead of `arr.flatMap(x => [x, x * 2])`). * Consider benchmarking other JavaScript features, such as closures, promises, or async/await. Keep in mind that the best approach will depend on the specific requirements and constraints of your project.
Related benchmarks:
Array clone
arr test
array push
arr delete: length=0 vs []
Clone Array - 08/02/2024
Comments
Confirm delete:
Do you really want to delete benchmark?