Benchmark: lodash test - MeasureThat.net

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/2.4.1/lodash.min.js"></script>

Script Preparation code:

function shuffle(a) {
    var j, x, i;
    for (i = a.length; i; i--) {
        j = Math.floor(Math.random() * i);
        x = a[i - 1];
        a[i - 1] = a[j];
        a[j] = x;
    }
}
var all = [];
var ids = [];
var allLength = 1000;
var idsLength = 5;

for(var i = 0; i < allLength; i++) {
  all[i] = {id: i, value: 'value' + i };
}

for(var i = 0; i < allLength; i++) {
  ids[i] = i;
}
ids = ids.splice(allLength - idsLength)
shuffle(all);
shuffle(ids);

Tests:

map + find iterate on ids
var output = _.map(ids, function(id) { return _.find(all, { id: id }); }); console.log(output);
reduce + includes iterate on all
var output = _.reduce(all, function(acc, element) { if(_.includes(ids, element.id)) { acc.push(element); } return acc; }, []); console.log(output);
filter + includes + map iterate on all
var output = _.filter(all, function(element) { return _.includes(ids, element.id); }); console.log(output);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map + find iterate on ids
reduce + includes iterate on all
filter + includes + map iterate on all

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 7 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36

Browser/OS: Chrome 58 on Windows

View result in a separate tab

Test name	Executions per second
map + find iterate on ids	1986.9 Ops/sec
reduce + includes iterate on all	796.6 Ops/sec
filter + includes + map iterate on all	795.5 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the benchmark and its test cases for you.

**Benchmark Definition**

The benchmark uses JavaScript to measure performance of three different operations: `map`, `reduce`, and `filter`. The operations are applied to two arrays: `all` and `ids`.

*   `all` contains 1000 objects with a unique identifier (`id`) and a value (`value`).
*   `ids` is an array of integers representing the indices of the `id`s in the `all` array.
*   The operations are applied to these arrays, and the results are logged to the console.

**Benchmark Preparation Code**

The script preparation code sets up the benchmark by:

1.  Generating a random shuffle for both `all` and `ids` arrays using the `shuffle()` function.
2.  Defining two constants: `allLength` (1000) and `idsLength` (5).
3.  Creating the `all` and `ids` arrays with their respective values.

**Html Preparation Code**

The HTML preparation code includes a script tag that loads the Lodash library, version 2.4.1.

**Test Cases**

There are three test cases:

*   **map + find iterate on ids**: This test case applies `map()` and `find()` functions to get the values of all objects in `all` array whose `id` matches with any element in `ids`.
*   **reduce + includes iterate on all**: This test case applies `reduce()` function along with `includes()` function to filter elements from `all` array based on their presence in `ids`.
*   **filter + includes + map iterate on all**: This test case combines the above two operations, first filtering elements of `all` using `filter()`, then mapping over that filtered set and applying `map()` on it.

**Options Compared**

The benchmark compares the performance of three different approaches for each operation:

1.  **Map + Find Iterate on IDs**: Uses `map()` followed by `find()` to find the desired elements.
2.  **Reduce + Includes Iterate on All**: Utilizes `reduce()` function with `includes()` helper function to achieve similar results.
3.  **Filter + Includes + Map Iterate on All**: Applies both `filter()` and `map()` operations sequentially.

**Pros and Cons**

Each approach has its advantages:

*   **Map + Find Iterate on IDs**: Provides a straightforward implementation but may require more iterations (e.g., finding the index of an id in ids).
*   **Reduce + Includes Iterate on All**: More efficient because it avoids unnecessary lookups by directly including elements from all array into a result. However, requires extra iteration.
*   **Filter + Includes + Map Iterate on All**: Offers the best balance between readability and performance since it leverages both filtering (to eliminate unwanted results) followed by mapping.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a comprehensive set of functions for functional programming, including `map()`, `reduce()`, `filter()`, `includes()` etc. It helps simplify the code and reduces its readability.

**Special JS Feature/Syntax**

This benchmark does not explicitly use any special JavaScript features or syntax other than using ES6 imports with CommonJS, but it relies heavily on functional programming (map/reduce/filter) to perform operations.

Related benchmarks:

lodash test (version: 0)

Comparing performance of: map + find iterate on ids vs reduce + includes iterate on all vs filter + includes + map iterate on all

Created: 7 years ago by: Guest

Jump to the latest result

map + find iterate on ids

reduce + includes iterate on all

filter + includes + map iterate on all

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):