Benchmark: forEach vs reduce vs map vs filter vs for v2292U9I2JIR2J0IEJ02JE0IJ20EJ

Script Preparation code:

var arr = [];
for (var i = 0; i < 12345; i++) {
  arr[i] = i;
}

function someFn(i) {
  return (i * 3 * 8 / 1200 * 0.002 / 40 * 0.2);
}

var sumForEach = 0,
  sumReduce = 0,
  sumMap = 0,
  sumFilter = 0,
  sumFor = 0;

Tests:

forEach
arr.forEach(item => sumForEach += someFn(item));
reduce
sumReduce = arr.reduce((lastValue, item) => { return lastValue += someFn(item); }, 0);
map
arr.map(item => (sumMap += someFn(item)));
filter
arr.filter(item => (sumFilter += someFn(item)));
for
for (var j = 0; j < arr.length; j++) { sumFor += arr[j]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
forEach
reduce
map
filter
for

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

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Measuring the performance of different JavaScript iteration methods is a crucial task, especially when it comes to optimizing code for large datasets or high-performance applications.

**What are we testing?**

We're comparing the performance of five different iteration methods:

1. `forEach`
2. `reduce`
3. `map`
4. `filter`
5. `for` (a traditional loop)

These methods will be applied to an array with a large number of elements (12345) and will perform a calculation on each element.

**Options compared:**

Each iteration method has its own strengths and weaknesses:

* `forEach`: Iterates over the array, performing the calculation on each element. It's easy to use, but can be slower than other methods.
* `reduce`: Accumulates a value by applying the callback function to each element in the array. It's efficient for reducing arrays to single values, but may not be suitable for all use cases.
* `map`: Creates a new array with transformed elements from the original array. It's great for creating new data structures, but can consume more memory and resources than other methods.
* `filter`: Creates a new array with filtered elements from the original array. Like map, it consumes more memory and resources, but is useful when working with conditional logic.
* `for`: A traditional loop that iterates over the array using an index variable.

**Pros and Cons:**

* **forEach**: Pros: Easy to use, concise code. Cons: May be slower than other methods due to function call overhead.
* **reduce**: Pros: Efficient for accumulating values, suitable for reducing arrays to single values. Cons: Can be confusing to use for some tasks.
* **map**: Pros: Great for creating new data structures, efficient with array comprehensions. Cons: Consumes more memory and resources than other methods.
* **filter**: Pros: Useful for conditional logic, consumes less memory and resources than map. Cons: May not be suitable for all use cases due to performance overhead.
* **for**: Pros: Suitable for complex loops, easy to control iteration flow. Cons: Can be error-prone due to index management.

**Library usage:**

The provided benchmark code doesn't explicitly mention any libraries, but it does use the `someFn` function, which is likely a custom function designed for testing purposes.

**Special JS features:**

The benchmark doesn't utilize any special JavaScript features beyond what's standard in ECMAScript 2015 (ES6).

**Other alternatives:**

If you need to optimize iteration performance further, consider using:

* `Array.prototype.every()`: Similar to `filter`, but returns a boolean value instead of creating a new array.
* `Array.prototype.some()`: Similar to `forEach`, but returns a boolean value indicating whether at least one element meets the condition.
* `Set` data structures: Suitable for fast lookup and insertion operations, but may not be as efficient for iteration-intensive tasks.

In conclusion, measuring the performance of different JavaScript iteration methods helps developers understand the trade-offs between conciseness, readability, and execution speed. By choosing the right method for their specific use case, developers can optimize code for better performance and scalability.

Related benchmarks:

forEach vs reduce vs map vs filter vs for v2292U9I2JIR2J0IEJ02JE0IJ20EJ (version: 0)

Comparing performance of: forEach vs reduce vs map vs filter vs for

Created: 5 years ago by: Guest

Jump to the latest result

forEach

reduce

map

filter

for

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):