Benchmark: findIndex in map vs. lookup + map

Script Preparation code:

var arr1 = [];
var arr2 = [];
var i = 0;
var j = 0;

while (i <= 1E5) {
  arr1[i] = i++;
  arr2[j] = j++;
}

Tests:

map + findIndex
arr1.map((item1) => (arr2.findIndex(item2 => item2 === item1)));
lookup + map
const lookup = arr2.reduce((lookup, item, index) => {lookup[item] = index; return lookup;}, {}); arr2.map((item) => lookup[item]);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map + findIndex
lookup + map

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.

**Benchmark Explanation**

The provided benchmark measures the performance of two approaches: `map` with `findIndex` and `lookup` with `map`. The goal is to compare the execution speed of these two methods for searching an element in a map.

**Options Compared**

There are two options being compared:

1. **`map` with `findIndex`**: This approach uses the `map()` method to create a new array, and then uses the `findIndex()` method to search for the target element within the created array.
2. **`lookup` with `map`**: This approach uses an object (the second array) as a lookup table. The `reduce()` method is used to populate the lookup object with indices of elements in the second array, and then the `map()` method is used to create a new array by mapping each element from the first array to its corresponding index in the lookup object.

**Pros and Cons**

* **`map` with `findIndex`**:
	+ Pros: Simple and concise implementation.
	+ Cons: Creates an unnecessary intermediate array, which can lead to increased memory usage and slower performance compared to the lookup approach.
* **`lookup` with `map`**:
	+ Pros: More efficient in terms of memory usage and potentially faster execution speed due to the avoidance of creating an intermediate array.
	+ Cons: Requires additional setup and population of the lookup object, which can be more complex and error-prone.

**Library Usage**

In this benchmark, no libraries are explicitly mentioned. However, it's worth noting that JavaScript built-in methods like `map()`, `reduce()`, and `findIndex()` are used.

**Special JS Features/Syntax**

There is no special JavaScript feature or syntax being tested in this benchmark. The code only uses standard JavaScript methods and data structures.

**Alternatives**

Other alternatives to compare the performance of searching an element in a map could include:

1. **Using `forEach()`**: Instead of creating an array and using `findIndex()`, you could use the `forEach()` method to iterate over each element and perform the search.
2. **Using a simple loop**: You could also implement a simple loop to iterate over each element in the array and check if it exists in the lookup object.
3. **Using a more efficient data structure**: Depending on the specific requirements, using a data structure like a hash table or a trie might be more efficient than an array for searching elements.

These alternatives would likely require changes to the benchmark code and setup but could provide additional insights into performance optimizations.

Related benchmarks:

findIndex in map vs. lookup + map (version: 0)

Comparing performance of: map + findIndex vs lookup + map

Created: 2 years ago by: Guest

Jump to the latest result

map + findIndex

lookup + map

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):