Benchmark: Large but empty Array versus Small Object (Access wise with string versus sorted number)

Script Preparation code:

var array = [];

for (let i = 0; i < 10; i++)
    array[i] = Math.floor (Math.random () * 10000);

var object = {};

var n0 = 0;
var n1 = 1;
var n2 = 2;
var n3 = 3;
var n4 = 4;
var n5 = 5;
var n6 = 6;
var n7 = 7;
var n8 = 8;
var n9 = 9;

var str0 = "aszfxchJDkdk";
var str1 = "slqmkdjflkjs";
var str2 = "jslkdfJXkfkd";
var str3 = "xnskjdfmjsdj";
var str4 = "xjlkJCLu8_7D";
var str5 = "X?lkdkdxsxsd";
var str6 = "nxJKDFxnJDKF";
var str7 = "LKJClkldjfsv";
var str8 = "LKXJLKDdkfjd";
var str9 = "slkfKLXJdefj";

object[str0] = array[0];
object[str1] = array[1];
object[str2] = array[2];
object[str3] = array[3];
object[str4] = array[4];
object[str5] = array[5];
object[str6] = array[6];
object[str7] = array[7];
object[str8] = array[8];
object[str9] = array[9];

Tests:

Array
let sum = 0; sum += array[n0]; sum += array[n1]; sum += array[n2]; sum += array[n3]; sum += array[n4]; sum += array[n5]; sum += array[n6]; sum += array[n7]; sum += array[n8]; sum += array[n9];
Object
let sum = 0; sum += object[str0]; sum += object[str1]; sum += object[str2]; sum += object[str3]; sum += object[str4]; sum += object[str5]; sum += object[str6]; sum += object[str7]; sum += object[str8]; sum += object[str9];

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array
Object

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/123.0.0.0 Safari/537.36

Browser/OS: Chrome 123 on Windows

View result in a separate tab

Test name	Executions per second
Array	1435230.0 Ops/sec
Object	1441789.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, the options compared, pros and cons of each approach, and other considerations.

**Benchmark Definition**

The benchmark is testing two different ways to access elements in an array or object:

1. **Array**: Accessing elements by index (e.g., `array[n0]`) using a variable (`n0`) that increments from 0 to 9.
2. **Object**: Accessing elements by key (e.g., `object[str0]`) using a string (`str0`) that corresponds to an array element.

**Options Compared**

The benchmark is comparing two approaches:

1. **Array access**: Accessing elements in the array using an incrementing index variable (`n0`).
2. **Object access**: Accessing elements in the object using a corresponding string key (`str0`).

**Pros and Cons of Each Approach**

**Array Access**

Pros:

* Typically faster for random access, as it involves a simple array lookup.
* Can be more cache-friendly, as it tends to access adjacent elements.

Cons:

* May require additional memory allocation or copying if the index variable is not optimized.

**Object Access**

Pros:

* Often slower due to the overhead of dynamic key lookups and potential string internment.
* May involve additional memory allocations or copies if the object is not properly optimized.

Cons:

* Can be more cache-unfriendly, as it often accesses elements at different memory locations.

**Other Considerations**

* The benchmark uses a random array generation algorithm, which can affect performance. A deterministic approach might provide more consistent results.
* The use of `str0` to `str9` keys for object access may introduce additional overhead due to string internment or caching issues.
* The choice of data types (e.g., integers vs. strings) and their lengths can impact performance.

**Library Usage**

In the benchmark, the `Math.random()` function is used to generate random values for the array elements. This is a built-in JavaScript function that generates a random number between 0 (inclusive) and the specified value (exclusive).

There are no explicitly mentioned libraries in this benchmark, but it's essential to note that some modern browsers have performance-optimized implementations of certain functions, such as `Array.prototype.slice()` or `Object.keys()`. However, these optimizations are typically not included in microbenchmarking suites like MeasureThat.net.

**Special JS Features/Syntax**

There are no explicitly mentioned special JavaScript features or syntax in this benchmark. The code uses standard JavaScript syntax and does not rely on any advanced features like async/await, Promises, or arrow functions.

Now that we've broken down the benchmark, let's talk about other alternatives:

* **Benchmarking frameworks**: There are several popular benchmarking frameworks for JavaScript, such as Jest, Mocha, or Benchmark.js. These frameworks often provide more comprehensive features than MeasureThat.net, including support for asynchronous benchmarks and detailed reporting.
* **Online benchmarks**: Other online benchmarking platforms, like JSPerf or Microbenchmarking.io, offer a range of benchmarks and tools for comparing performance across different browsers and environments.
* **Local benchmarking tools**: For those who prefer to run benchmarks locally, there are various command-line tools available, such as `node-benchmark` or ` benchmark.js`. These tools can be used to create custom benchmarks and compare performance across different Node.js versions or environments.

Related benchmarks:

Large but empty Array versus Small Object (Access wise with string versus sorted number) (version: 0)

Comparing performance of: Array vs Object

Created: 2 years ago by: Guest

Jump to the latest result

Array

Object

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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