Benchmark: Map and Filter vs forEach

Script Preparation code:

var jobIds = [1, 2, 3, 4, 5]
var jobs = {
  1: { status: 2 },
  2: { status: 1 },
  3: { status: 3 },
  4: { status: 2 },
  5: { status: 3 }
}

Tests:

map and filter
var activeJobs = jobIds.map(id => jobs[id]).filter(job => job.status !== 3)
forEach
var activeJobs = [] jobIds.forEach(id => { var job = jobs[id] if (job.status !== 3) activeJobs.push(job) })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map and filter
forEach

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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I'll break down the benchmark and explain what's being tested, compared options, pros and cons, library usage, special JS features or syntax, and alternative approaches.

**Benchmark Purpose**

The test measures the performance difference between two approaches for filtering an array of job IDs: `map` and `filter`, versus using a traditional loop with `forEach`. The benchmark aims to identify which approach is faster and more efficient.

**Options Compared**

There are two options being compared:

1. **Map and Filter**: This approach uses the built-in `map` method to create a new array of job objects based on the filtered conditions, followed by the `filter` method to remove jobs with status 3.
2. **forEach Loop**: This approach uses a traditional loop with `forEach` to iterate through each job ID, creating a new object for each job and pushing it into an array if its status is not 3.

**Pros and Cons**

* **Map and Filter**:
	+ Pros: More concise and readable code, less chance of off-by-one errors.
	+ Cons: Can be slower due to the creation of a new array.
* **forEach Loop**:
	+ Pros: Faster execution time, as it avoids creating a new array.
	+ Cons: More verbose code, more prone to off-by-one errors.

**Library Usage**

The `map` and `filter` methods are built-in JavaScript Array.prototype methods. They are part of the ECMAScript standard and do not require any additional libraries or dependencies.

**Special JS Feature or Syntax**

There is no special JavaScript feature or syntax being used in this benchmark. It's a basic demonstration of two common array manipulation techniques in JavaScript.

**Alternative Approaches**

Other approaches that could be considered for filtering an array include:

* Using `reduce` to create a new array.
* Using a function with `every` method to filter the array.
* Using a library like Lodash, which provides a `filter` function as part of its utility belt.
* Using a different programming language or framework that might have built-in filtering capabilities.

**Benchmark Preparation Code**

The preparation code is used to set up the test environment. In this case:

* The `jobIds` array is defined with some sample data.
* A `jobs` object is created with corresponding job objects for each ID in `jobIds`.
* The two benchmark definitions are provided as strings, which will be executed by the test runner.

**Individual Test Cases**

Each test case defines a specific benchmarking scenario. In this case:

* The first test case (`map and filter`) uses the `map` and `filter` methods to create a new array of active jobs.
* The second test case (`forEach`) uses a traditional loop with `forEach` to iterate through each job ID, creating a new object for each job and pushing it into an array if its status is not 3.

**Latest Benchmark Result**

The latest benchmark result provides the execution time for each test case on a specific device (Chrome 90 on Windows). The results are displayed in the format of `ExecutionsPerSecond`, which represents the number of times the code was executed per second.

Related benchmarks:

Map and Filter vs forEach (version: 1)

Comparing performance of: map and filter vs forEach

Created: 8 years ago by: Registered User

Jump to the latest result

map and filter

forEach

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):