Benchmark: getEventGroups - MeasureThat.net

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.21/lodash.min.js"></script>

Script Preparation code:

var options = [{
        label: 'kustomer.conversation.create',
        value: 'kustomer.conversation.create',
    },
    {
        label: 'kustomer.conversation.update',
        value: 'kustomer.conversation.update',
    },
    {
        label: 'kustomer.customer.create',
        value: 'kustomer.customer.create',
    },
    {
        label: 'kustomer.customer.update',
        value: 'kustomer.customer.update',
    },
    {
        label: 'kustomer.message.create',
        value: 'kustomer.message.create',
    },
    {
        label: 'kustomer.message.update',
        value: 'kustomer.message.update',
    },
    {
        label: 'kustomer.team.create',
        value: 'kustomer.team.create',
    },
    {
        label: 'kustomer.team.update',
        value: 'kustomer.team.update',
    },
    {
        label: 'kustomer.user.create',
        value: 'kustomer.user.create',
    },
    {
        label: 'kustomer.user.update',
        value: 'kustomer.user.update',
    },
];
var getEventGroups = (eventsList) => {
    const groups = {};
    eventsList.forEach((event) => {
        const group = event.value.split('.', 2)[1];
        if (!groups[group]) groups[group] = {
            label: group,
            options: []
        };
        groups[group].options.push(event);
    });
    return Object.values(groups);
}

var getEventGroupsMemoize = _.memoize(getEventGroups);
var getEventGroupsMemoizeSerialize = _.memoize(getEventGroups, (...args) => JSON.stringify(args));

Tests:

getEventGroups
getEventGroups(options)
getEventGroupsMemoize
getEventGroupsMemoize(options)
getEventGroupsMemoizeSerialize
getEventGroupsMemoizeSerialize(options)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
getEventGroups
getEventGroupsMemoize
getEventGroupsMemoizeSerialize

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.107 Safari/537.36

Browser/OS: Chrome 92 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
getEventGroups	258528.6 Ops/sec
getEventGroupsMemoize	7140223.0 Ops/sec
getEventGroupsMemoizeSerialize	224739.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and explain what is tested, compared, and other considerations.

**Benchmark Definition**

The benchmark definition is a JavaScript function called `getEventGroups` that takes an array of events as input and returns an object with grouped event options. The function uses a simple approach to group events by their value's second part (e.g., `kustomer.conversation.create` becomes `conversation.create`).

**Options Comparison**

The benchmark compares three different approaches:

1. **Original implementation**: This is the original `getEventGroups` function without any optimization or modification.
2. **Memoized version**: This is a memoized version of the original function using Lodash's `memoize` method, which caches the results of expensive function calls and reuses them when the same inputs occur again.
3. **Memoized with serialization**: This is another memoized version of the original function that uses `JSON.stringify` to serialize the input arguments before caching the result.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Original implementation**:
	* Pros: Simple, easy to understand, and doesn't introduce any additional dependencies.
	* Cons: May be slow due to repeated computations for the same inputs.
2. **Memoized version**:
	* Pros: Caches results for expensive function calls, reducing computation time for subsequent executions with the same input.
	* Cons: Requires Lodash library, which may not be present in all environments.
3. **Memoized with serialization**:
	* Pros: Combines caching with stringification, which can help reduce memory usage by serializing complex inputs.
	* Cons: May lead to slower performance due to the additional overhead of serializing and deserializing data.

**Library and its Purpose**

The Lodash library is used for memoization. Memoization is a technique where the results of expensive function calls are cached and reused when the same inputs occur again, reducing computation time by avoiding redundant calculations.

In this benchmark, Lodash's `memoize` method is used to create memoized versions of the original function, which helps reduce computation time by caching results for repeated executions with the same input.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax used in this benchmark. The code primarily relies on standard JavaScript and Lodash functions.

**Alternatives**

If you're interested in exploring alternative approaches, here are a few options:

1. **Caching with V8's built-in caching**: Some JavaScript engines, like V8 (used by Chrome), have built-in caching mechanisms that can be leveraged for memoization.
2. **Using `Map` or `WeakMap` for caching**: Instead of using Lodash's `memoize`, you could use JavaScript's built-in `Map` or `WeakMap` data structures to implement caching.
3. **Using a library like `memorization`**: There are other libraries available, such as `memorization`, that provide memoization functionality for JavaScript functions.

Keep in mind that these alternatives might not be as efficient or convenient as using Lodash's `memoize` method, but they can serve as interesting alternatives to explore.

Related benchmarks:

getEventGroups (version: 0)

Comparing performance of: getEventGroups vs getEventGroupsMemoize vs getEventGroupsMemoizeSerialize

Created: 3 years ago by: Registered User

Jump to the latest result

getEventGroups

getEventGroupsMemoize

getEventGroupsMemoizeSerialize

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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