Benchmark: filter.map - MeasureThat.net

Script Preparation code:

var arr = [];
for (var i = 0; i < 12345; i++) {
  arr[i] = i;
}

function reduceFilterMap(filterSelector, valueSelector) {
    return [
        (previousValue, currentValue, currentIndex) => {
            const shouldBeAdded = filterSelector(currentValue, currentIndex);
            if (shouldBeAdded) {
                previousValue.push(valueSelector(currentValue, currentIndex));
            }

            return previousValue;
        },
        [],
    ];
}

Tests:

filter.map
arr.filter(v => v % 2).map(v => v * 2);
reduce
arr.reduce(...reduceFilterMap(v => v % 2, v => v * 2))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter.map
reduce

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Let's dive into the explanation of the benchmark.

**Benchmark Definition JSON**

The benchmark definition is a JavaScript code that represents a microbenchmark. In this case, there are two benchmark definitions:

1. `arr.filter(v => v % 2).map(v => v * 2);`
2. `arr.reduce(...reduceFilterMap(v => v % 2, v => v * 2))`

These benchmarks test the performance of filtering and mapping operations on an array.

**Options Compared**

The two benchmark definitions compare different approaches to perform filtering and mapping:

1. **Filtering and Mapping**: The first benchmark definition uses `Array.prototype.filter()` followed by `Array.prototype.map()`. This approach is straightforward but might be slower due to the overhead of function calls.
2. **Reduce with Filter**: The second benchmark definition uses `Array.prototype.reduce()`, which is a more efficient approach that combines filtering and mapping into a single operation.

**Pros and Cons**

**Filtering and Mapping**

Pros:

* Simple and easy to understand
* Well-supported by most JavaScript engines

Cons:

* Might be slower due to function call overhead
* Requires two separate operations, which can lead to additional overhead

**Reduce with Filter**

Pros:

* More efficient approach that reduces the number of operations
* Can lead to better performance

Cons:

* Less straightforward and might require more complex code
* Not as well-supported by older JavaScript engines (before ES6)

**Library and Syntax**

In this benchmark, we're using standard JavaScript libraries and syntax. There are no specific libraries or frameworks mentioned in the benchmark definition.

However, if we look at the `reduceFilterMap` function in the script preparation code, it's not a part of the standard JavaScript library. This function is likely a custom implementation for testing purposes.

**Special JS Feature or Syntax**

There are no special JS features or syntax used in this benchmark. The code follows standard JavaScript syntax and conventions.

**Other Alternatives**

If you're interested in alternative approaches to filtering and mapping, here are some options:

* Using `Array.prototype.filter()` followed by a `forEach()` loop
* Using `Array.prototype.map()` with an iterator (e.g., `for...of` loop)
* Using a third-party library like Lodash for filtering and mapping operations
* Using WebAssembly or other just-in-time compilation techniques for optimized performance

Keep in mind that the best approach depends on your specific use case, JavaScript engine, and target audience.

Related benchmarks:

filter.map (version: 0)

Comparing performance of: filter.map vs reduce

Created: 3 years ago by: Guest

Jump to the latest result

filter.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):