Benchmark: for vs. map - MeasureThat.net

Script Preparation code:

var arr10 = new Array(10).fill();
var arr1k = new Array(1000).fill();
var arr100k = new Array(100000).fill();
var arr1M = new Array(1000000).fill();

Tests:

map10
const map10 = arr10.map((item) => item);
for10
const for10 = []; for (const item of arr10) { for10.push(item); }
map1k
const map1k = arr1k.map((item) => item);
for1k
const for1k = []; for (const item of arr1k) { for1k.push(item); }
map100k
const map100k = arr100k.map((item) => item);
for100k
const for100k = []; for (const item of arr100k) { for100k.push(item); }
map1M
const map1M = arr1M.map((item) => item);
for1M
const for1M = []; for (const item of arr1M) { for1M.push(item); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map10
for10
map1k
for1k
map100k
for100k
map1M
for1M

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.75 Safari/537.36

Browser/OS: Chrome 86 on Windows

View result in a separate tab

Test name	Executions per second
map10	5612796.5 Ops/sec
for10	5393590.5 Ops/sec
map1k	180510.8 Ops/sec
for1k	148983.8 Ops/sec
map100k	407.4 Ops/sec
for100k	723.9 Ops/sec
map1M	38.3 Ops/sec
for1M	44.2 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Explanation**

The provided benchmark measures the performance difference between using `Array.prototype.map()` and traditional `for` loops to iterate over arrays of varying sizes.

**Options Compared**

Two options are compared:

1. **`map()`:** A built-in JavaScript method that creates a new array with the results of applying a provided function on every element in an array.
2. **Traditional `for` loop:** A manual iteration approach using a `for` loop to push elements into a new array.

**Pros and Cons**

* **`map()`:**
	+ Pros:
		- Concise and expressive code
		- Less prone to errors due to implicit type checking
		- Often faster than traditional loops for large datasets
	+ Cons:
		- Creates a new array, which can lead to increased memory usage
		- May not be suitable for very large datasets due to memory constraints
* **Traditional `for` loop:**
	+ Pros:
		- Can be more control-oriented and flexible
		- Does not create a new array, which can reduce memory usage
	+ Cons:
		- More verbose code
		- Prone to errors if not implemented carefully

**Library and Purpose**

In the benchmark code, `Array.prototype.map()` is used. The `map()` method is a built-in JavaScript function that applies a provided function on every element of an array and returns a new array with the results.

**Special JS Feature or Syntax**

There are no special JS features or syntaxes used in this benchmark beyond what's already discussed.

**Other Considerations**

When choosing between `map()` and traditional loops, consider the following:

* For most use cases, `map()` is a suitable choice due to its concise and expressive nature.
* However, for very large datasets or memory-constrained environments, traditional loops might be a better option.
* Always profile your code and measure performance to determine the best approach for your specific use case.

**Alternatives**

Other alternatives for iterating over arrays include:

1. **`forEach()`:** Similar to `map()`, but without returning a new array.
2. **`reduce()`:** A method that applies a function on every element of an array, reducing it to a single value.
3. **Arrow functions or function expressions with explicit loops:** These can provide more control over the iteration process.

Keep in mind that each approach has its own strengths and weaknesses, and choosing the right one depends on your specific use case and performance requirements.

Related benchmarks:

for vs. map (version: 0)

Comparing performance of: map10 vs for10 vs map1k vs for1k vs map100k vs for100k vs map1M vs for1M

Created: 4 years ago by: Guest

Jump to the latest result

map10

for10

map1k

for1k

map100k

for100k

map1M

for1M

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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