data = [Array(1000)].map((_, id) => ({ id, data: Math.random() }))
map = new Map(data.map(v => [v.id, v]))
const res = map.get(50)
const res = data.find(({ id }) => id === 50)
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
Map.get | |
Array.find |
Test name | Executions per second |
---|---|
Map.get | 4531271.5 Ops/sec |
Array.find | 3236547.5 Ops/sec |
Let's break down the benchmark and its components.
Benchmark Definition
The benchmark is defined in JSON format, which describes two individual test cases: Map.get
and Array.find
. The benchmark is designed to measure the performance difference between these two approaches when searching for a specific element in an array.
Script Preparation Code
The script preparation code generates an array of 1000 elements using the Array.from()
method and maps over it to create an object with an ID and some random data. A new Map object is created from this data, where each key-value pair consists of the ID as the key and the corresponding object as the value.
Options Compared The two options being compared are:
Map.get()
: This method retrieves the value associated with a given key in a Map object.Array.find()
: This method finds the first element in an array that satisfies a provided testing function.Pros and Cons
Map.get()
: Pros:Array.find()
:Map.get()
, with an average time complexity of O(n) for large datasets.Library and Purpose
No libraries are explicitly mentioned in the benchmark definition. However, JavaScript's built-in Map
object is used to store data, and Array.find()
is a standard array method provided by modern JavaScript engines.
Special JS Features or Syntax None are mentioned specifically in this benchmark.
Other Considerations
ExecutionsPerSecond
) but not memory usage or other performance metrics.Alternatives
For Array.find()
, alternative approaches could include:
filter()
followed by indexing the resulting array: data.filter(({ id }) => id === 50)[50]
.For Map.get()
, alternative approaches could include:
Array.prototype.indexOf()
or Set
data structures.Keep in mind that these alternatives might not offer significant performance improvements for this specific benchmark and may introduce additional complexity.