How to deal with data compression and decompression issues in C++ big data development?

How to deal with data compression and decompression issues in C big data development?

Introduction:
In modern big data applications, data compression and decompression are a A very important technology. Data compression can reduce the space occupied by data during storage and transmission, thereby speeding up data transmission and reducing storage costs. This article will introduce how to deal with data compression and decompression issues in C big data development, and provide relevant code examples.

1. Data Compression
Data compression is the process of converting original data into a more compact format. In C, we can use various compression algorithms to compress data, such as Gzip, Deflate, etc. The following is a code example that uses the Gzip algorithm for data compression:

#include <iostream>
#include <fstream>
#include <sstream>
#include <string>
#include <cassert>
#include <zlib.h>

std::string compressData(const std::string& input)
{
    z_stream zs;                        // z_stream is zlib's control structure
    memset(&zs, 0, sizeof(zs));

    if (deflateInit(&zs, Z_DEFAULT_COMPRESSION) != Z_OK)
        throw(std::runtime_error("deflateInit failed while compressing."));

    zs.next_in = (Bytef*)input.data();
    zs.avail_in = input.size();           // set the z_stream's input

    int ret;
    char outbuffer[32768];
    std::string outstring;

    // retrieve the compressed bytes blockwise
    do {
        zs.next_out = reinterpret_cast<Bytef*>(outbuffer);
        zs.avail_out = sizeof(outbuffer);

        ret = deflate(&zs, Z_FINISH);

        if (outstring.size() < zs.total_out) {
            // append the block to the output string
            outstring.append(outbuffer, zs.total_out - outstring.size());
        }
    } while (ret == Z_OK);

    deflateEnd(&zs);

    if (ret != Z_STREAM_END) {          // an error occurred that was not EOF
        std::ostringstream oss;
        oss << "Exception during zlib compression: (" << ret << ") " << zs.msg;
        throw(std::runtime_error(oss.str()));
    }

    return outstring;
}

int main()
{
    std::string input = "This is a sample string to be compressed.";
    std::string compressed = compressData(input);

    std::cout << "Original size: " << input.size() << std::endl;
    std::cout << "Compressed size: " << compressed.size() << std::endl;

    return 0;
}

2. Data decompression
Data decompression is the process of restoring compressed data to original data. In C, we can use the decompression function corresponding to the compression algorithm to decompress data. For example, the decompression function corresponding to Gzip is gunzip. The following is a code example using the Gzip algorithm for data decompression:

#include <iostream>
#include <fstream>
#include <sstream>
#include <string>
#include <cassert>
#include <zlib.h>

std::string decompressData(const std::string& input)
{
    z_stream zs;                        // z_stream is zlib's control structure
    memset(&zs, 0, sizeof(zs));

    if (inflateInit(&zs) != Z_OK)
        throw(std::runtime_error("inflateInit failed while decompressing."));

    zs.next_in = (Bytef*)input.data();
    zs.avail_in = input.size();

    int ret;
    char outbuffer[32768];
    std::string outstring;

    // get the decompressed bytes blockwise using repeated calls to inflate
    do {
        zs.next_out = reinterpret_cast<Bytef*>(outbuffer);
        zs.avail_out = sizeof(outbuffer);

        ret = inflate(&zs, 0);

        if (outstring.size() < zs.total_out) {
            outstring.append(outbuffer, zs.total_out - outstring.size());
        }

    } while (ret == Z_OK);

    inflateEnd(&zs);

    if (ret != Z_STREAM_END) {          // an error occurred that was not EOF
        std::ostringstream oss;
        oss << "Exception during zlib decompression: (" << ret << ") "
            << zs.msg;
        throw(std::runtime_error(oss.str()));
    }

    return outstring;
}

int main()
{

    std::string decompressed = decompressData(compressed);

    std::cout << "Compressed size: " << compressed.size() << std::endl;
    std::cout << "Decompressed size: " << decompressed.size() << std::endl;

    return 0;
}

Conclusion:
This article introduces the method of handling data compression and decompression problems in C big data development, and provides relevant code Example. Through reasonable selection of compression algorithms and decompression functions, we can effectively reduce data storage and transmission overhead and improve program performance and efficiency during big data processing. It is hoped that readers can flexibly use this knowledge in practical applications to optimize their own big data applications.

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