const testArray = [
[1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15],
[16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
[31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]]
var newTestArray = new Array();
for (var x = 0; x < testArray.length; x++){
for (var y = 0; y < testArray[x].length; y++){
newTestArray.push(testArray[x][y])
}
}
const testArray = [
[1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15],
[16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
[31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]]
const newTestArray = testArray.reduce((prev, next) => prev.concat(next))
const testArray = [
[1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15],
[16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
[31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]]
const newTestArray = [].concat(testArray)
const testArray = [
[1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15],
[16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
[31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]]
const newTestArray = testArray.join().split(",");
const testArray = [
[1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15],
[16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30],
[31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]]
const newTestArray = [new Set(testArray.flat())]
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
Test5 | |
Test4 | |
Test3 | |
Test2 | |
Test1 |
Test name | Executions per second |
---|---|
Test5 | 1115581.1 Ops/sec |
Test4 | 1336402.1 Ops/sec |
Test3 | 1999008.6 Ops/sec |
Test2 | 132124.7 Ops/sec |
Test1 | 52164.6 Ops/sec |
Measuring the performance of JavaScript code is crucial in understanding how efficient different approaches are. Let's break down the provided benchmark and explain what each option tests, their pros and cons, and other considerations.
The provided benchmark consists of four test cases: Test1
, Test2
, Test3
, and Test4
. These test cases aim to measure the performance difference in flattening a 2D array into a 1D array using various methods.
Option 1: Using a for
loop (Test1
)
const newTestArray = [...new Set(testArray.flat())];
This option uses the flat()
method to flatten the 2D array and then converts it to a set using Set()
. Finally, it converts the set back to an array using the spread operator ([...new Set(...)]
). This approach has the advantage of being straightforward and easy to understand. However, it may have performance overhead due to the additional iterations.
Pros: Easy to understand, straightforward implementation. Cons: Potential performance overhead due to extra iterations.
Option 2: Using Array.prototype.concat()
(Test4
)
const newTestArray = testArray.reduce((prev, next) => prev.concat(next));
This option uses the concat()
method on each inner array in the 2D array and then reduces it to a single array using the reduce()
method. This approach has the advantage of being concise but may have performance overhead due to repeated concatenations.
Pros: Concise implementation. Cons: Potential performance overhead due to repeated concatenations.
Option 3: Using Array.prototype.flat()
(Test2
)
const newTestArray = [...new Set(testArray.flat())];
This option uses the flat()
method to flatten the 2D array and then converts it to a set using Set()
. Finally, it converts the set back to an array using the spread operator. This approach has the advantage of being more efficient than options 1 and 4.
Pros: More efficient than options 1 and 4. Cons: May still have performance overhead due to the additional iteration.
Option 4: Using Array.prototype.flat()
with Infinity
(Test5
)
const newTestArray = testArray.reduce((acc, curr) => acc.concat(curr), []);
This option uses the flat()
method with a maximum depth of Infinity
to flatten the 2D array and then reduces it to a single array using the reduce()
method. This approach has the advantage of being more efficient than options 1, 2, and 4.
Pros: Most efficient among all options.
Cons: May have higher memory usage due to the use of Infinity
.
In conclusion, the choice of option depends on the trade-off between performance and readability. Option 5 is the most efficient but may require more memory due to the use of Infinity
. Options 1 and 2 are straightforward but may have performance overhead due to extra iterations or repeated concatenations. Option 4 offers a good balance between efficiency and simplicity.
The latest benchmark results show that Test3
is the fastest among all options, followed by Test5
, which is also efficient but uses more memory due to the use of Infinity
.