Toggle navigation
MeasureThat.net
Create a benchmark
Tools
Feedback
FAQ
Register
Log In
flatMap vs reduce 99984545878432
(version: 0)
Comparing performance of:
flatMap vs reduce
Created:
3 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
var values = [] for(i=0; i<100000; i++){ values.push(i) }
Tests:
flatMap
values.flatMap(i => [i, i * 2, i *3])
reduce
values.reduce((acc, x) => { acc.push(x, x* 2, x * 3) return acc; }, [])
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
Fork
Test case name
Result
flatMap
reduce
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 what's being tested in the provided JSON. The website MeasureThat.net is comparing two approaches to transform an array of numbers: `flatMap` and `reduce`. These are both methods available on the Array prototype in JavaScript. **What is being compared?** * `flatMap`: This method returns a new array with the results of applying a provided function on every element of this array. The function is called for each element, and it must return an array. The resulting arrays are then flattened (i.e., concatenated) into one array. * `reduce`: This method applies a user-supplied function to an accumulator and each element in the array (from left to right) to reduce it to a single value. **Options compared** * `flatMap` vs `reduce` **Pros and Cons of each approach:** * **flatMap**: * Pros: + More concise and expressive when dealing with simple transformations. + Less memory-intensive since it returns an array, which can be useful for large datasets. * Cons: + May be slower due to the function being called on every element, potentially leading to more overhead. * **reduce**: + Pros: + Can handle complex transformations and accumulations more elegantly. + More suitable for certain use cases where a single value needs to be computed from multiple elements. * Cons: + May be slower due to the function being called on every element, potentially leading to more overhead. + Requires more memory since it returns an accumulator array. **Other considerations:** * The `flatMap` method was introduced in ECMAScript 2019 (ES10), so older browsers might not support it. This could affect performance and compatibility across different devices and browsers. * If the input array is very large, both methods may use significant amounts of memory, as they return new arrays with transformed elements. **Library or syntax used:** Neither `flatMap` nor `reduce` relies on any external libraries in this context; these are built-in methods available on the Array prototype. **Special JS feature or syntax:** None mentioned in the provided JSON. However, note that both methods use a functional programming style, which is supported by JavaScript and other languages. This approach encourages concise code, reusability, and easier maintenance. **Other alternatives:** * Other approaches to transform an array could involve: * Using `map` with subsequent operations (e.g., concatenation or filtering). * Utilizing a for loop with manual indexing. * Leveraging libraries like Lodash or Ramda for more complex transformations.
Related benchmarks:
flatMap vs reduce test
flatMap vs reduce test 2
Reduce Push vs. flatMap with subarrays
flatMap vs Reduce with push - test
flatMap vs reduce (push)
Comments
Confirm delete:
Do you really want to delete benchmark?