Benchmark: map vs flatMap - MeasureThat.net

Script Preparation code:

var arrayOfArrays = Array(1000).fill().map(el => Array(10).fill(1));
var flattenedArray = arrayOfArrays.flat();

Tests:

map
const map = (array) => { return map(i => i) } map(flattenedArray);
flatMap
const flatMap = (array) => { return array.flatMap(i => i); } flatMap(arrayOfArrays);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
flatMap

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 months ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36

Browser/OS: Chrome 132 on Linux

View result in a separate tab

Test name	Executions per second
map	0.0 Ops/sec
flatMap	10723.2 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, compared options, pros/cons, and other considerations.

**Benchmark Overview**

The provided benchmark compares two JavaScript functions: `map` and `flatMap`. Both functions are used to transform an array of arrays into a single array. The benchmark measures which function is faster on different browsers and devices.

**Script Preparation Code**

The script preparation code creates a large 2D array with 1000 rows and 10 columns, filled with ones (`var arrayOfArrays = Array(1000).fill().map(el => Array(10).fill(1));`), and then flattens it using the `flat()` method (`var flattenedArray = arrayOfArrays.flat();`). This creates a large input array that's used for both functions.

**Benchmark Definition**

The benchmark definition consists of two test cases:

* `map`: The first function to be tested is the built-in `map()` method. Its implementation is not provided, so we can assume it's the standard JavaScript implementation.
* `flatMap`: The second function to be tested is a custom implementation (`const flatMap = (array) => {\r\n\treturn array.flatMap(i => i);\r\n}\r\nflatMap(arrayOfArrays);`).

**Comparison**

The benchmark compares the execution speed of these two functions on different browsers and devices. The raw UAS string, browser version, device platform, operating system, executions per second, and test name are recorded for each test case.

**Options Compared**

Two options are being compared:

* `map()`: The built-in JavaScript method for transforming arrays.
* `flatMap()`: A custom implementation using the new `flatMap()` method introduced in ECMAScript 2019.

**Pros/Cons:**

**`map()`:**

Pros:

* Wide browser support and compatibility
* Efficient implementation by most browsers

Cons:

* May create intermediate arrays, which can lead to higher memory usage
* Not optimized for large input sizes like the provided benchmark

**`flatMap()`:**

Pros:

* Optimized for large input sizes and can avoid creating intermediate arrays
* More efficient than `map()` for large datasets

Cons:

* Introduced in ECMAScript 2019, might not be supported by older browsers or environments
* Custom implementation may not be as efficient as the built-in `map()` method in some cases

**Other Considerations:**

* The benchmark uses a very large input size (1000x10) to test performance. This may not reflect real-world usage scenarios.
* The custom implementation of `flatMap()` is not optimized for memory usage or cache performance.
* The benchmark only compares the execution speed on different browsers and devices, without considering other factors like code complexity or maintainability.

**Alternatives:**

If you want to explore alternative approaches, consider:

* Using a library like Lodash, which provides an implementation of `map()` and `flatMap()` with optional optimizations.
* Implementing your own custom array transformation function using loops or recursion.
* Investigating other optimization techniques, such as memoization or caching.

Related benchmarks:

map vs flatMap (version: 0)

Comparing performance of: map vs flatMap

Created: 4 years ago by: Guest

Jump to the latest result

map

flatMap

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):