Toggle navigation
MeasureThat.net
Create a benchmark
Tools
Feedback
FAQ
Register
Log In
flatMap vs reduce small array
(version: 0)
Comparing performance of:
reduce with concat vs flatMap
Created:
3 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
var arr = Array(100).fill(0)
Tests:
reduce with concat
arr.reduce((acc, x) => [...acc, x, x], [])
flatMap
arr.flatMap(x => [x, x])
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
Fork
Test case name
Result
reduce with concat
flatMap
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):
I'd be happy to explain the benchmark and its different approaches. **Benchmark Overview** The benchmark is designed to compare the performance of two array processing methods: `reduce` with concatenation (`arr.reduce((acc, x) => [...acc, x, x], [])`) and `flatMap`. The test case uses a small array of 100 zeros. **Library and Purpose** Neither `reduce` nor `flatMap` uses any external libraries. They are built-in JavaScript methods that operate on arrays. **Options Compared** The benchmark compares the performance of two approaches: 1. **Reduce with Concatenation**: This approach uses the `reduce` method to accumulate an array of results, concatenating each new element to the accumulator (`acc`) using the spread operator (`[...acc, x, x]`). 2. **FlatMap**: This approach uses the `flatMap` method to create a new array with the transformed elements. **Pros and Cons** 1. **Reduce with Concatenation**: * Pros: Well-established and widely supported method. * Cons: Can be slower than `flatMap` due to the overhead of concatenating arrays in each iteration. 2. **FlatMap**: * Pros: Often faster and more memory-efficient, as it avoids unnecessary array concatenations. * Cons: Less well-known and less supported compared to `reduce`, which can lead to compatibility issues. **Other Considerations** When choosing between these approaches, consider the following: * If you need to accumulate results in a specific order (e.g., preserving the original order), `reduce` might be a better choice. * If you need to perform multiple transformations on each element and create a new array with the transformed elements, `flatMap` is likely a better option. **Special JS Feature or Syntax** Neither of these approaches uses any special JavaScript features or syntax. They are straightforward, built-in methods that operate on arrays. **Other Alternatives** If you need alternative approaches for this benchmark, here are some options: * Use `map` instead of `reduce` and concatenate the results using `Array.prototype.concat()`. * Use a custom implementation using a loop to iterate over the array and accumulate the results. * Consider using a third-party library like Lodash or Ramda, which provide additional array manipulation functions. Keep in mind that these alternatives may introduce additional complexity, overhead, or compatibility issues, so they should be considered only if `reduce` with concatenation or `flatMap` are not sufficient.
Related benchmarks:
flatMap vs reduce using push
Reduce vs flatMap performance
Reduce Push vs. flatMap with subarrays
flatMap vs reduce flattern array
Comments
Confirm delete:
Do you really want to delete benchmark?