Benchmark: map x reduce - MeasureThat.net

Script Preparation code:

const qts = [{sy: 1}, {sy: 2}];

function mapIt(payload) {
return (
                payload.map(cr => (
                    (qts || []).find((it) => it.sy === cr)
                )).filter(Boolean)
    )
}

function reduceIt(payload) {
return (
                payload.reduce((ns, cr) => {
                    const foo = (qts || []).find((it) => it.sy === cr)
                    if (foo) {
                      return [...ns, foo]
                    }
                  return ns
                }, [])
    )
}

Tests:

map
mapIt([1,2,3,4,5,1,2,3])
reduce
reduceIt([1,2,3,4,5,1,2,3])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
reduce

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's dive into the provided JSON benchmark data.

**Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided JSON represents two individual test cases: `map` and `reduce`. We'll explore what's being tested, the different approaches, their pros and cons, and other considerations.

**Benchmark Definitions**

The benchmark definitions are stored in the `"Benchmark Definition"` field of each test case:

1. `mapIt`: This function takes an array as input and returns a new array with elements that match a specific condition.
	* The `payload.map(cr => ...)`: This is using the `map()` method, which applies a specified function to each element of an array and returns a new array with the results.
	* The inner function `(qts || []).find((it) => it.sy === cr)`:
		+ `(qts || [])` accesses an external array `qts`, which contains objects with a `sy` property. If `qts` is undefined (e.g., due to a browser cache issue), this returns an empty array.
		+ `.find((it) => it.sy === cr)` searches the resulting array for an object with a `sy` property matching the current element `cr`.
2. `reduceIt`: This function takes an array as input and returns a new array with elements that match a specific condition.
	* The `payload.reduce((ns, cr) => ...)`: This is using the `reduce()` method, which applies a specified function to each element of an array and reduces it to a single value.
	* The inner function `(qts || []).find((it) => it.sy === cr)`:
		+ Same as in `mapIt`.

**Approaches**

The two approaches being compared are:

1. **`map()`**: This method creates a new array by applying a specified function to each element of the original array.
2. **`reduce()`**: This method reduces an array to a single value by applying a specified function to each element of the array.

**Pros and Cons**

* **`map()`**:
	+ Pros: Easy to understand, efficient for creating new arrays with transformed data.
	+ Cons: May lead to performance issues if the original array is very large, as it creates a new array with duplicate elements.
* **`reduce()`**:
	+ Pros: More memory-efficient than `map()`, can be used for both aggregation and transformation.
	+ Cons: Requires more effort to understand, may not be suitable for all use cases.

**Other Considerations**

* The benchmark uses an external array `qts` which is accessed using the `||` operator. This might lead to performance issues if `qts` is undefined or very large.
* The `find()` method is used in both approaches, which can also impact performance if the resulting arrays are very large.

**Library Usage**

The benchmark uses an external array `qts`, but it does not explicitly mention any libraries. However, based on the syntax and structure of the code, it appears to be using a JavaScript standard library or a custom implementation.

**Special JS Features/Syntax**

None mentioned in this explanation. If there were any specific JavaScript features or syntax used (e.g., `async/await`, `let` or `const` declarations), they would need to be explicitly stated for clarity.

**Alternatives**

Other alternatives for creating new arrays with transformed data could include:

* Using a loop and appending elements to an array
* Utilizing a library like Lodash or Ramda, which provide various utility functions for array manipulation.
* Leveraging modern JavaScript features like `Array.prototype.forEach()` or `map()`, along with custom implementation of the transformation logic.

Related benchmarks:

map x reduce (version: 0)

Comparing performance of: map vs reduce

Created: 4 years ago by: Guest

Jump to the latest result

map

reduce

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):