Benchmark: array of object search

Script Preparation code:

function randstr(N) {
  return (Math.random().toString(36)+'00000000000000000').slice(2, N+2);
}
var dataset = [];
for (var x = 0; x < 100000; x++) {
  dataset.push({id: 'xx' + x, name: randstr(10), other: randstr(10)});
}
var indexedDataset = {};
for (var item of dataset) {
  indexedDataset[item.id] = item;
}
var indexMap = {};
for (var [i, item] of dataset.entries()) {
  indexMap[item.id] = i;
}
function assertEq(a, b) {
  if (a !== b) {
    new Error(`Failed assert: "${a}" expected "${b}"`);
  }
}

Tests:

Array.find
for (var x = 0; x < 10000; ++x) { const item = dataset.find(v => v.id == 'xx' + 123); assertEq(item.id, 'xx' + 123); }
indexed copy
for (var x = 0; x < 10000; ++x) { const item = indexedDataset['xx' + 123]; assertEq(item.id, 'xx' + 123); }
index map
for (var x = 0; x < 10000; ++x) { const item = dataset[indexMap['xx' + 123]]; assertEq(item.id, 'xx' + 123); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array.find
indexed copy
index map

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

I'll break down the benchmark and explain what's being tested, compared options, pros and cons, and other considerations.

**Benchmark Overview**

The benchmark measures the performance of three different approaches to search for an item in an array of objects: `Array.find()`, indexed copy, and index map. The test case creates a large dataset with 100,000 objects, each with a unique ID, and then searches for an object with a specific ID using each approach.

**Approaches Compared**

1. **Array.find()**: This method uses the Array.prototype.find() function to search for an item in the array that satisfies the provided callback function. In this case, the callback function checks if the `id` property of the current item matches the target ID.
2. **Indexed Copy**: This approach creates a shallow copy of the original dataset using the spread operator (`...`) and then searches for the object with the target ID in the copied array.
3. **Index Map**: This approach creates an index map by iterating over the dataset and storing the item's ID as the key, along with its index. Then, it uses this index map to search for the object with the target ID.

**Pros and Cons**

* **Array.find()**:
	+ Pros: concise and readable code, eliminates the need to manage indices.
	+ Cons: can be slow due to the overhead of creating a callback function, and may not perform well on large datasets.
* **Indexed Copy**:
	+ Pros: simple and easy to understand, can be faster than Array.find() since it only needs to search through a smaller array.
	+ Cons: creates an additional copy of the dataset, which can consume more memory, and the search operation is still O(n) in the worst case.
* **Index Map**:
	+ Pros: can be faster than Indexed Copy since it uses a hash-based lookup, reducing the number of iterations needed to find the target ID.
	+ Cons: requires more code and understanding of index maps, and may not perform well if the dataset is very large or has many duplicate IDs.

**Other Considerations**

* **Memory Usage**: The benchmark measures the performance of each approach under different memory constraints. This helps determine which method is most efficient in terms of memory usage.
* **CPU Usage**: The benchmark also measures CPU usage, as this can be an important factor in determining the overall performance of a system.

**Library/Function Used**

In this benchmark, two functions are used:

1. `Array.prototype.find()`: This function is part of the ECMAScript standard and provides a way to search for an item in an array.
2. Spread operator (`...`): This operator creates a shallow copy of an object or array.

**Special JavaScript Features**

In this benchmark, two special JavaScript features are used:

1. **Arrow functions**: The `assertEq()` function is defined using an arrow function, which allows it to be concise and readable while also providing closure over the variable `a` and `b`.
2. **Template literals**: The `randstr(N)` function uses template literals to generate a random string of length `N`.

Overall, this benchmark provides valuable insights into the performance characteristics of different approaches to searching for an item in an array of objects, and can help developers choose the most efficient method for their specific use case.

Latest run results:

Run details: (Test run date: 8 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.101 Safari/537.36

Browser/OS: Chrome 53 on Linux

View result in a separate tab

Test name	Executions per second
Array.find	42.2 Ops/sec
indexed copy	351.6 Ops/sec
index map	261.1 Ops/sec

Related benchmarks:

array of object search (version: 5)

Comparing performance of: Array.find vs indexed copy vs index map

Created: 8 years ago by: Registered User

Jump to the latest result

Array.find

indexed copy

index map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):