Benchmark: Search: Map.get vs Array.find

Script Preparation code:

dataArr = [...Array(100)].map((_, id) => ({ id, data: Math.random() }))
dataMap = new Map(dataArr.map(v => [v.id, v]))

Tests:

Map.get
const res = dataMap.get(50)
Array.find
const res = dataArr.find(({ id }) => id === 50)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map.get
Array.find

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the benchmark definition and test cases to understand what is being tested.

**Benchmark Definition**

The benchmark definition json provides information about the benchmark, including its name, description (which is empty), script preparation code, and HTML preparation code (which is also empty). The script preparation code creates two data structures: an array `dataArr` with 100 random objects, each having a unique `id` and `data` property. A map `dataMap` is then created from the array, where each object's `id` is used as the key.

**Test Cases**

The test cases are individual benchmark tests that compare two different approaches:

1. **Map.get**: This test case uses the `get()` method of the `Map` data structure to retrieve a value by its key (in this case, `50`).
2. **Array.find**: This test case uses the `find()` method of the array to find an element that satisfies a condition (in this case, having an `id` equal to `50`).

**Options Compared**

The two options being compared are:

* Using a `Map` data structure to store and retrieve values
* Using an array with a custom index or map function to retrieve values

**Pros and Cons of Each Approach**

**Map.get**

Pros:

* Efficient for large datasets, as it only searches through the relevant part of the map
* Can be faster than array-based approaches for certain use cases

Cons:

* May have slower startup times due to the creation of the map
* Requires an additional data structure (the map) which may increase memory usage

**Array.find**

Pros:

* Fast and efficient, as it only searches through the relevant part of the array
* Does not require an additional data structure (the map)

Cons:

* May be slower for very large datasets, as it needs to iterate over the entire array
* Requires a custom index or comparison function to find the desired element

**Library: Lodash**

In the provided code, there is no explicit reference to a library. However, the `dataArr` and `dataMap` variables are created using ES6 features (e.g., `map()`, arrow functions). The `Array.find()` method is a built-in JavaScript method, but it's not immediately clear what other libraries might be used in this context.

**Special JS Feature or Syntax**

In the script preparation code, there is an example of a custom index function: `(v => [v.id, v])`. This is an example of a callback function used to create a key-value pair for each element in the array. It's not a special feature or syntax per se, but rather a common way to create a map data structure.

**Other Alternatives**

There are several other alternatives that could be used instead of `Map.get` and `Array.find`, depending on the specific use case:

* For finding an element in an array:
	+ `indexOf()` method
	+ `forEach()` method with an index parameter
	+ A custom loop or iterative approach
* For searching a large dataset (e.g., a database or CSV file):
	+ Using a query language like SQL or MongoDB queries
	+ Utilizing indexing and caching mechanisms

Overall, the choice between `Map.get` and `Array.find` depends on the specific requirements of the use case, such as performance, memory usage, and data size.

Related benchmarks:

Search: Map.get vs Array.find (version: 0)

Comparing performance of: Map.get vs Array.find

Created: 3 years ago by: Guest

Jump to the latest result

Map.get

Array.find

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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