const array = [Array.from(100000)];
array.filter(i => i % 2 === 0).map(i => i++);
const array = [Array.from(100000)];
array.reduce((acc, t) => {
return t % 2 === 0? acc.push[t++] : acc;
},[]);
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
pipe | |
reduce with conditions |
Test name | Executions per second |
---|---|
pipe | 785427.8 Ops/sec |
reduce with conditions | 706123.6 Ops/sec |
Let's break down the provided JSON benchmark data and explain what's being tested.
Benchmark Definition The benchmark definition outlines the scenario being tested: pipe chaining vs reduce with if statements (with a new array) compared to creating a new array for iteration.
In this case, the goal is to compare the performance of three different approaches:
reduce()
method with a callback function that checks conditions for each element in the array and either pushes it to a new accumulator array or returns the current value.push()
method.Pros and Cons of Each Approach
Library Used
In this benchmark, Array.from()
is used to create an array from a specified length (in this case, 100,000). filter()
and map()
are also used for filtering and transformation operations, respectively.
Special JavaScript Feature or Syntax There's no explicit mention of special features like ES6 syntax (e.g., arrow functions) in the benchmark definition. However, it's worth noting that modern JavaScript environments often support ES6+ features by default.
Other Alternatives
For similar benchmarks, you might want to consider alternative approaches, such as:
for
loops or forEach()
instead of array methods.Keep in mind that the choice of approach will depend on the specific requirements and performance characteristics of your use case.
In this benchmark, pipe chaining
seems to be the fastest approach, followed by reduce with conditions
. The new array
approach is the slowest.