Benchmark: filter vs id lookup

Script Preparation code:

var object = {}
var array = []
for (var i = 0; i < 10000; i++) {
  object[i] = { id: i }
  array[i] = { id : i }
}

Tests:

lookup
console.log(object[5000])
filter
console.log(array.filter(function(item) { return item.id == 5000 })[0])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lookup
filter

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.

I'd be happy to explain what's being tested in this JavaScript microbenchmark.

**Benchmark Definition**

The benchmark is comparing two approaches: `lookup` and `filter`. The test case uses an object and an array, both with 10,000 elements each. Each element has a unique `id` property.

**Options compared**

There are two options being compared:

1. **Lookup**: This approach uses direct indexing to access the desired value in the object. Specifically, it's trying to access `object[5000]`.
2. **Filter**: This approach uses the `filter()` method to create a new array with only the elements that match the condition (`item.id == 5000`). The first element of this new array is then accessed using indexing (`array.filter() ... [0]`).

**Pros and cons**

**Lookup**:

Pros:

* Direct access, potentially faster for small to medium-sized datasets.
* Less overhead compared to function calls.

Cons:

* May be slower for large datasets or when the desired index is near the end of the array.
* Requires knowledge of the object's structure and index.

**Filter**:

Pros:

* Flexible and reusable; can be used with any iterable data structure.
* Can handle edge cases like finding a single matching element.

Cons:

* May be slower due to the overhead of creating a new array and executing the callback function.
* Can be less efficient for small datasets or when exact matches are unlikely.

**Library usage**

In this benchmark, no external libraries are used. However, it's worth noting that `filter()` is a built-in JavaScript method that can be used with any iterable data structure, including objects (in certain cases).

**Special JS features or syntax**

There are no special JavaScript features or syntax being tested in this benchmark.

**Other alternatives**

If you were to reimplement these benchmarks, other approaches could include:

* **Indexing array**: Similar to lookup, but using the `array.indexOf()` method to find the index of the desired element.
* **Binary search**: A more efficient approach for larger datasets, where the algorithm can be optimized to take advantage of binary searching.
* **Hash table-based lookup**: Using a hash table (e.g., JavaScript's built-in `Map`) to store the objects by their IDs, allowing for O(1) lookups.

Keep in mind that these alternatives may have different performance characteristics and trade-offs compared to the original `lookup` and `filter` approaches.

Related benchmarks:

filter vs id lookup (version: 0)

Comparing performance of: lookup vs filter

Created: 9 years ago by: Guest

Jump to the latest result

lookup

filter

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):