<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>
var max2 = 100000;
var data = [];
for (var i = 0; i <= max2; i++) { data.push({ id: i }); }
_.groupBy(data, ({ id }) => id)
data.reduce((acc, item) => {
acc[item.id] = item;
return acc;
}, {})
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
Lodash | |
Native |
Test name | Executions per second |
---|---|
Lodash | 94.0 Ops/sec |
Native | 252.5 Ops/sec |
Overview of the Benchmark
The provided JSON represents a JavaScript microbenchmark, specifically comparing the performance of two approaches for grouping an array: _.groupBy
from the Lodash library and a native implementation using the reduce
method.
What is being tested?
The benchmark is testing the performance difference between these two approaches on a dataset of 100,000 objects with unique IDs. The test cases are designed to measure which approach is faster in terms of executions per second.
Options compared:
({ id }) => id
.reduce
method of JavaScript arrays to achieve similar results. The callback function accumulates objects with the same ID in the accumulator.Pros and Cons of each approach:
reduce
due to optimizations provided by Lodash.Library: Lodash
Lodash is a popular JavaScript utility library that provides a wide range of functions for tasks like array manipulation, object normalization, and functional programming. The groupBy
function is one of its many useful utilities. It takes an array and a predicate function as arguments, groups the elements based on the output of the predicate, and returns an object with each group as a key.
Special JavaScript feature: ES6 arrow functions
The _.groupBy
function uses an arrow function to extract the ID from each element in the dataset. Arrow functions are a concise way to define small, single-purpose functions without creating a new scope. They were introduced in ECMAScript 2015 (ES6) and provide several benefits, including reduced syntax clutter and improved readability.
Benchmark results
The latest benchmark result shows that the native reduce
approach is slightly faster than the Lodash groupBy
approach on this particular test case. However, it's essential to note that performance differences might vary depending on the specific use case and dataset.
Other alternatives
If you're looking for alternative approaches or libraries for grouping arrays, consider the following options:
reduce
approach.groupBy
function similar to Lodash's implementation.groupBy
function with various options for customizing the grouping behavior.Ultimately, the choice of approach depends on your project's requirements, personal preference, and performance considerations.