Benchmark: merge maps big - MeasureThat.net

Script Preparation code:

const arr = [];
const arr2 = [];
for (let i = 0; i < 10000; i++) {
    arr.push([i, 'Val' + i]);
    arr2.push(['key' + i, 'Val' + i]);
}

var map1 = new Map(arr)
var map2 = new Map(arr2)

const arr3 = [];
for (let i = 0; i < 1000; i++) {
    arr3.push(['key2' + i, 'Val' + i]);
}
var map9 = new Map(arr3)

Tests:

Merge spread
var map3 = new Map([...map1, ...map2]);
merge foreach
var map4 = new Map(map1) map2.forEach((val, key) => {map4.set(key, val)})
merge 2 foreach
var map4 = new Map() map1.forEach((val, key) => {map4.set(key, val)}) map2.forEach((val, key) => {map4.set(key, val)})
update big map
map9.forEach( (val,key) => {map1.set(key,val)})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Merge spread
merge foreach
merge 2 foreach
update big map

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

To understand what is being tested, let's break down the provided benchmark definition and test cases.

**Benchmark Definition**

The benchmark definition provides a set of JavaScript code snippets that are used to create two maps (`map1` and `map2`) with different data structures. The maps are then merged using three different approaches:

1. **Merge spread**: Using the spread operator (`...`) to merge the two maps.
2. **Merge foreach**: Iterating over both maps using `forEach` and updating the resulting map.
3. **Merge 2 foreach**: Similar to the previous approach, but with an additional iteration.

The goal of this benchmark is to compare the performance of these three approaches for merging large datasets.

**Options Compared**

* Three different approaches for merging two maps:
	+ Merge spread: `map3 = new Map([...map1, ...map2])`
	+ Merge foreach: `var map4 = new Map(); map1.forEach((val, key) => {map4.set(key, val)}) map2.forEach((val, key) => {map4.set(key, val)})`
	+ Merge 2 foreach: Similar to the previous approach, but with an additional iteration.

**Pros and Cons**

* **Merge spread**: Pros:
	+ Shorter code
	+ Less overhead due to iteration
Cons:
	+ May not perform well for large datasets
* **Merge foreach**: Pros:
	+ Can handle large datasets efficiently
Cons:
	+ Longer code
	+ More overhead due to iteration
* **Merge 2 foreach**: Similar pros and cons as the previous approach, with an additional iteration.

**Library Used**

None mentioned in this specific benchmark definition.

**Special JS Features/Syntax**

The `Map` data structure is used throughout the benchmark. A `Map` is a built-in JavaScript object that stores key-value pairs, where each key is unique and maps to a specific value.

In this benchmark, the `Map` constructor is used to create new instances of the map, and methods like `forEach`, `set`, and others are used to manipulate the data within the maps.

**Other Considerations**

* The benchmark uses Chrome 103 as the browser for testing.
* The test cases are designed to run on desktop platforms (Windows).
* The raw UAS string is provided for each test case, which may be useful for debugging or analyzing performance metrics.

As an alternative, you could consider other approaches for merging large datasets in JavaScript, such as:

* Using `reduce` method
* Utilizing third-party libraries like Lodash or Ramda
* Implementing a custom merge function
* Using Web Workers or parallel processing to speed up the merging process

Related benchmarks:

merge maps big (version: 0)

Comparing performance of: Merge spread vs merge foreach vs merge 2 foreach vs update big map

Created: 3 years ago by: Guest

Jump to the latest result

Merge spread

merge foreach

merge 2 foreach

update big map

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):