var array = new Array(100);
for (let i = 0; i < array.length; i++) {
array[i];
}
array.forEach(function(i) {
array[i];
});
array.some(function(i) {
array[i];
});
for (const i of array) {
array[i];
}
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
for | |
foreach | |
some | |
for..of |
Test name | Executions per second |
---|---|
for | 221476.1 Ops/sec |
foreach | 8915883.0 Ops/sec |
some | 9187566.0 Ops/sec |
for..of | 364537.2 Ops/sec |
The benchmark defined by the JSON provided compares the performance of different looping constructs in JavaScript: for
, forEach
, some
, and for..of
. Each of these constructs has different performance characteristics and use cases, and the benchmark aims to establish which is the fastest based on their execution speed in a controlled environment.
for
loop:
for (let i = 0; i < array.length; i++) { array[i]; }
forEach
method:
array.forEach(function(i) { array[i]; });
break
or return
, which may limit its usability in certain scenarios.some
method:
array.some(function(i) { array[i]; });
true
), which can be more efficient when searching for a specific condition.forEach
, involving function call overhead.for..of
loop:
for (const i of array) { array[i]; }
From the latest benchmark results, the performance of the different loop constructs was measured in "Executions Per Second":
The some
method emerged as the fastest in this test, followed closely by forEach
. Both of these methods leverage higher-level abstractions but incur additional overhead. The traditional for
loop and for..of
performed more poorly in this specific case, with for..of
being the least efficient.
While this benchmark focuses on these specific looping constructs, there are additional alternatives and patterns available in JavaScript, such as:
map
, filter
, and reduce
are also worth considering if the operation involves transformation or reduction of array data, though they have their own performance quirks due to the function calls involved.Understanding when and why to choose a specific looping construct is crucial for optimizing performance-sensitive applications, especially in scenarios with large datasets or tight performance requirements.