Benchmark: filter vs flatMap v2

Script Preparation code:

var objArray = [{id: 1}, {id: 2}, {id: 3}, {id: 4}, {id: 5}, {id: 6}, {id: 7}, {id: 8}, {id: 9}, {id: 10}, {id: 11}, {id: 12}, {id: 13}, {id: 14}, {id: 15}, {id: 16}, {id: 17}, {id: 18}, {id: 19}, {id: 20}];
var idArray = [1];

Tests:

filter
var filteredObjArray = objArray.filter(obj => idArray.includes(obj.id));
flatMap
var filteredObjArray = idArray.flatMap(id => objArray.find(obj => obj.id === id) || []);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter
flatMap

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, compared, and their pros and cons.

**Benchmark Definition**

The benchmark is designed to compare the performance of two approaches: filtering an array using `Array.prototype.filter()` and flattening an array using `Array.prototype.flatMap()`. The test case uses a JavaScript object array `objArray` containing 20 objects with an "id" property, as well as an array `idArray` containing a single value.

**Script Preparation Code**

The script preparation code defines the `objArray` and `idArray` variables, which are used in the benchmark. The `var idArray = [1];` line creates an array containing only one element, which is used to filter or map the objects in `objArray`.

**Html Preparation Code**

There is no HTML preparation code provided, so we can assume that this step is not relevant for this particular benchmark.

**Individual Test Cases**

The test cases are defined as separate benchmarks:

1. **filter**: This test case uses the `Array.prototype.filter()` method to create a new array containing only the objects in `objArray` whose "id" property matches one of the values in `idArray`. The condition used is `obj => idArray.includes(obj.id)`.
2. **flatMap**: This test case uses the `Array.prototype.flatMap()` method to create a new array containing the results of applying the function `(id => objArray.find(obj => obj.id === id) || [])` to each value in `idArray`. The purpose of this function is unclear, as it returns an empty array if no matching object is found.

**Pros and Cons**

Here's a brief analysis of the two approaches:

**Filter (Array.prototype.filter())**

Pros:

* Simple and well-known algorithm
* Works for most use cases

Cons:

* May create intermediate arrays or objects that need to be garbage collected
* Can be slower than flatMap if the input array is large

**FlatMap (Array.prototype.flatMap())**

Pros:

* Avoids creating intermediate arrays or objects, reducing memory allocation and garbage collection overhead
* Returns a new array, avoiding side effects on the original data

Cons:

* Less well-known algorithm compared to filter()
* May require additional checks for null/undefined values in the input array
* Can be slower than filter() if the input array is small

**Library Usage**

In both test cases, no external libraries are used. However, it's worth noting that flatMap() was introduced in ECMAScript 2019 (ES10) as a part of the standard library.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax mentioned in the benchmark definition. Both `filter()` and `flatMap()` are built-in methods on arrays, and their usage is straightforward.

**Other Alternatives**

If you need to filter an array, other alternatives besides `Array.prototype.filter()` include:

* Using a simple loop with conditional statements
* Utilizing a library like Lodash's `filter` function

If you need to flatten an array, other alternatives besides `Array.prototype.flatMap()` include:

* Using a simple loop with nested iterations
* Utilizing a library like Ramda's `map` and `flatten` functions

Keep in mind that these alternatives may have different performance characteristics or require additional setup.

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36

Browser/OS: Chrome 116 on Windows

View result in a separate tab

Test name	Executions per second
filter	1464960.1 Ops/sec
flatMap	5023242.0 Ops/sec

Related benchmarks:

filter vs flatMap v2 (version: 0)

Comparing performance of: filter vs flatMap

Created: one year ago by: Guest

Jump to the latest result

filter

flatMap

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):