Benchmark: Testing findMode

Script Preparation code:

// Purposely global
numbers = Array.from({length: 1e6}, () => Math.floor(Math.random() * 1e20))

function findMode(numbers) {
    let counted = numbers.reduce((acc, curr) => { 
        if (curr in acc) {
            acc[curr]++;
        } else {
            acc[curr] = 1;
        }

        return acc;
    }, {});

    let mode = Object.keys(counted).reduce((a, b) => counted[a] > counted[b] ? a : b);

    return mode;
}

function mostCommonNumber(numbers) {
    let map = new Map()
    for (let num of numbers) {
        map.set(num, (map.get(num) || 0) + 1)
    }

    let mostCommonNumber = NaN
    let maxCount = -1
    for (let [num, count] of map.entries()) {
        if (count > maxCount) {
            maxCount = count
            mostCommonNumber = num
        }
    }

    return mostCommonNumber
}

​x
 
// Purposely globalnumbers = Array.from({length: 1e6}, () => Math.floor(Math.random() * 1e20))​function findMode(numbers) {    let counted = numbers.reduce((acc, curr) => {         if (curr in acc) {            acc[curr]++;        } else {            acc[curr] = 1;        }​        return acc;    }, {});​    let mode = Object.keys(counted).reduce((a, b) => counted[a] > counted[b] ? a : b);​    return mode;}​function mostCommonNumber(numbers) {    let map = new Map()    for (let num of numbers) {        map.set(num, (map.get(num) || 0) + 1)    }​    let mostCommonNumber = NaN    let maxCount = -1    for (let [num, count] of map.entries()) {        if (count > maxCount) {            maxCount = count            mostCommonNumber = num        }    }​    return mostCommonNumber}​​

Tests:

findMode
findMode(numbers)
findMode(numbers)
mostCommonNumber
mostCommonNumber(numbers)
mostCommonNumber(numbers)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
findMode
mostCommonNumber

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/61.0.3163.100 Safari/537.36

Browser/OS: Chrome 61 on Windows

View result in a separate tab

Test name	Executions per second
findMode	0.4 Ops/sec
mostCommonNumber	1.4 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 7 months ago):

Let's break down the provided benchmark and explain what's being tested, compared options, pros and cons, and other considerations.

Benchmark Overview

The benchmark consists of two test cases: findMode and mostCommonNumber. Both functions are designed to find the mode (the most frequently occurring value) in an array of numbers. The tests compare the performance of these two implementations.

Implementation Comparison

The two implementations differ in their approach:

findMode: This implementation uses a hash map (Object.keys and reduce) to count the occurrences of each number. It then finds the key with the highest value.
mostCommonNumber: This implementation uses an array-based approach, creating a frequency map using a Map object. It iterates through the numbers, incrementing the count for each unique number.

Pros and Cons

findMode:
- Pros: Simple and easy to understand. Uses built-in JavaScript features.
- Cons: May have performance issues due to the use of Object.keys, which has a higher overhead than using an array-based approach.
mostCommonNumber:
- Pros: Efficient for large datasets, as it only iterates through the numbers once.
- Cons: Requires additional memory allocation and iteration.

Other Considerations

Browser Support: The benchmark uses Chrome 61, which may not be supported by older browsers or versions of JavaScript.
Device Platform: The benchmark runs on a Windows device, which may affect performance due to factors like disk I/O and network bandwidth.
Randomized Input: The input data is randomly generated using Array.from and Math.random, which ensures that the results are not deterministic.

Special JS Features

In this benchmark, we don't see any special JavaScript features being used. However, some other benchmarks might use features like:

ES6 classes
async/await
Promises
Web Workers

These features can introduce additional overhead or complexities, making it harder to compare performance results.

Alternative Implementations

If you're interested in exploring alternative implementations, here are a few examples:

Sorting-based approach: Instead of using a hash map or array-based approach, you could sort the numbers and find the most common value. This approach would have higher overhead due to sorting.
Distributed computing: You could divide the input data among multiple processes or workers and use a consensus algorithm to find the mode. This approach would require additional complexity and synchronization mechanisms.

Keep in mind that these alternative implementations might not be as efficient or scalable as the original findMode and mostCommonNumber implementations.

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, compared options, pros and cons, and other considerations.

**Benchmark Overview**

The benchmark consists of two test cases: `findMode` and `mostCommonNumber`. Both functions are designed to find the mode (the most frequently occurring value) in an array of numbers. The tests compare the performance of these two implementations.

**Implementation Comparison**

The two implementations differ in their approach:

1. **findMode**: This implementation uses a hash map (`Object.keys` and `reduce`) to count the occurrences of each number. It then finds the key with the highest value.
2. **mostCommonNumber**: This implementation uses an array-based approach, creating a frequency map using a `Map` object. It iterates through the numbers, incrementing the count for each unique number.

**Pros and Cons**

* **findMode**:
	+ Pros: Simple and easy to understand. Uses built-in JavaScript features.
	+ Cons: May have performance issues due to the use of `Object.keys`, which has a higher overhead than using an array-based approach.
* **mostCommonNumber**:
	+ Pros: Efficient for large datasets, as it only iterates through the numbers once.
	+ Cons: Requires additional memory allocation and iteration.

**Other Considerations**

* **Browser Support**: The benchmark uses Chrome 61, which may not be supported by older browsers or versions of JavaScript.
* **Device Platform**: The benchmark runs on a Windows device, which may affect performance due to factors like disk I/O and network bandwidth.
* **Randomized Input**: The input data is randomly generated using `Array.from` and `Math.random`, which ensures that the results are not deterministic.

**Special JS Features**

In this benchmark, we don't see any special JavaScript features being used. However, some other benchmarks might use features like:

* ES6 classes
* async/await
* Promises
* Web Workers

These features can introduce additional overhead or complexities, making it harder to compare performance results.

**Alternative Implementations**

If you're interested in exploring alternative implementations, here are a few examples:

1. **Sorting-based approach**: Instead of using a hash map or array-based approach, you could sort the numbers and find the most common value. This approach would have higher overhead due to sorting.
2. **Distributed computing**: You could divide the input data among multiple processes or workers and use a consensus algorithm to find the mode. This approach would require additional complexity and synchronization mechanisms.

Keep in mind that these alternative implementations might not be as efficient or scalable as the original `findMode` and `mostCommonNumber` implementations.

Related benchmarks:

Testing findMode (version: 3)

Comparing performance of: findMode vs mostCommonNumber

Created: 7 years ago by: Registered User

Jump to the latest result

findMode

mostCommonNumber

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 7 months ago):