var arr = Array(10_000).fill(0)
arr.reduce((acc, x) => { acc.push(x, x); return acc; }, [])
arr.flatMap(x => [x, x])
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
Reduce Push | |
flatMap |
Test name | Executions per second |
---|---|
Reduce Push | 17713.4 Ops/sec |
flatMap | 2560.7 Ops/sec |
Let's break down the provided benchmark and explain what's being tested.
Benchmark Overview
The benchmark compares two approaches: reduce
with a custom callback that pushes elements to an accumulator array (Reduce Push
), and flatMap
(which is supported by modern JavaScript engines, introduced in ECMAScript 2019). The test case uses an array of 10,000 zeros as the input data.
Options Compared
The benchmark compares two options:
reduce()
method to accumulate elements in an array. In this custom implementation, each element is pushed twice (i.e., x
and x
) into the accumulator array (acc
). The callback returns the updated accumulator array.flatMap()
method to transform the array into a new array with the same length as the original array, but with each element transformed by the provided function (in this case, an arrow function that doubles the value).Pros and Cons of Each Approach
Library and Purpose
The flatMap()
method is part of the modern JavaScript standard, introduced in ECMAScript 2019. Its purpose is to transform an array into a new array by applying a transformation function to each element, which returns an array-like object. This allows for efficient processing of large datasets while maintaining readability.
Special JS Feature or Syntax
There is no special feature or syntax mentioned in the benchmark code. However, it's worth noting that modern JavaScript engines support flatMap()
and other new features introduced in ECMAScript 2019.
Other Alternatives
If you're interested in alternative approaches for reducing arrays, consider:
reduce()
method is similar to the custom implementation used in "Reduce Push".flatMap()
. However, it may have slightly higher performance overhead due to the creation of intermediate arrays.In conclusion, this benchmark compares two approaches for reducing an array: a custom implementation using reduce()
(Reduce Push
), and the modern flatMap()
method. The choice between these approaches depends on your specific use case, performance requirements, and desired level of customization.