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Asked: 2024-09-26T14:15:52+05:30

How to Implement Variable Length Quantity Encoding and Decoding for Integers Up to 1,000,000?

I recently stumbled upon something intriguing about Variable Length Quantity (VLQ) encoding and thought it would be fun to share a little challenge. For those not familiar, VLQ is a way of encoding integers using a variable number of bytes, where the most significant bit (MSB) of each byte indicates if there’s another byte following it. Pretty cool, right?

Now, here’s the challenge: Let’s say you’re given a series of integers that represent some sort of data—like musical note pitches or maybe even just random numbers. Your task is to encode these integers into a VLQ format and then decode them back to their original values. So, you’ll need to implement two main functions: one for encoding and one for decoding.

To make this more interesting, let’s add a twist. Instead of just regular integers, let’s say the integers you’ll be working with can go up to about 1,000,000. That means you’ll have to handle the way these higher values are encoded and ensure that your decoding logic can gracefully convert them back as well.

To give you an example, suppose you start with a set of integers: [128, 256, 1, 64, 1000000]. How do you encode these into their VLQ representations? Can you optimize your coding for speed or efficiency while you’re at it?

On the decoding side, it would be awesome to see how you handle potential edge cases. For instance, if there’s malformed VLQ data (like an extra byte with no preceding number), how will your functions react? And what if you have to handle an empty input list?

I feel like this could really challenge the limits of your coding skills, and it’s a fun way to geek out over some compression techniques. Plus, I’m curious if anyone can come up with an elegant solution. Looking forward to seeing all the creative ways you come up with to tackle this!

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    2 Answers


    1. Variable Length Quantity (VLQ) Encoding and Decoding

      Here’s a simple solution to encode and decode a list of integers using VLQ. It might not be the most optimized code, but it works. Check it out!

      
function encodeVLQ(numbers) {
    const result = [];
    
    numbers.forEach(num => {
        if (num < 0) {
            throw new Error("Negative numbers not supported");
        }
        
        let value = num;
        const encodedBytes = [];

        do {
            let byte = value & 0x7F; // Get last 7 bits
            value >>= 7; // Right shift the number by 7 bits

            if (encodedBytes.length > 0) {
                byte |= 0x80; // Set MSB if we have more bytes
            }

            encodedBytes.push(byte);
        } while (value > 0);

        result.push(...encodedBytes);
    });

    return result;
}

function decodeVLQ(encoded) {
    const result = [];
    let currentValue = 0;

    for (let i = 0; i < encoded.length; i++) {
        const byte = encoded[i];

        currentValue = (currentValue << 7) | (byte & 0x7F); // Append last 7 bits

        if ((byte & 0x80) === 0) { // If MSB is not set, we finished a number
            result.push(currentValue);
            currentValue = 0; // Reset for next number
        }
    }

    if (currentValue !== 0) {
        throw new Error("Malformed input data; extra byte detected.");
    }

    return result;
}

// Example usage
const inputNumbers = [128, 256, 1, 64, 1000000];
const encoded = encodeVLQ(inputNumbers);
const decoded = decodeVLQ(encoded);

console.log("Encoded VLQ:", encoded);
console.log("Decoded Integers:", decoded);

      This code will take a list of integers, encode them into a VLQ format, and then decode them back. Just remember to handle potential edge cases, like malformed input!



    2. To tackle the challenge of encoding and decoding integers using Variable Length Quantity (VLQ) encoding, we start by implementing two key functions. The encode_vlq function converts a list of integers into their VLQ representation. In this encoding scheme, each byte has its most significant bit (MSB) used as a continuation flag, where a value of 1 indicates another byte follows, and a value of 0 signifies the end of the sequence. The function will efficiently handle integers up to 1,000,000, ensuring that higher values are processed correctly, and each integer is represented in a minimal number of bytes. For example, the input integers [128, 256, 1, 64, 1000000] would be transformed into their respective VLQ byte sequences, which can be packed into an array for further processing.

      For decoding, the decode_vlq function reads the VLQ data and reconstructs the original integers. This function will need to manage potential edge cases, such as detecting malformed data, which could arise from an unexpected continuation byte or an empty input list. In such cases, the function should either raise an appropriate error or return an empty list, depending on the specified requirements. The entire solution aims to ensure both speed and efficiency, optimizing the encoding and decoding processes to handle large datasets gracefully.


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