Applications of C Language in Big Data: Data Processing and Storage

The C language, as an efficient and flexible programming language, is widely used in various system development and algorithm implementation. In the field of big data, due to its outstanding performance and control over hardware, C language is utilized for data processing and storage. This article will introduce how to use C language for large-scale data processing and storage, providing code examples to aid understanding.

Data Processing

In big data processing, common tasks include reading, processing, and outputting large amounts of data information. Due to C language’s good file operation capabilities, we can use it to read text files and perform simple data analysis.

1. Data Reading

Below is a basic example demonstrating how to read floating-point numbers from a text file and calculate the average:

#include <stdio.h>
int main() {
    FILE *file;
    float number;
    float sum = 0.0;
    int count = 0;

    file = fopen("data.txt", "r"); // Open file
    if (file == NULL) {
        printf("Cannot open file\n");
        return 1; // File open failed
    }

    while (fscanf(file, "%f", &number) != EOF) { // Read numbers line by line
        sum += number; // Accumulate sum
        count++; // Increment counter
    }
    fclose(file); // Close file

    if (count > 0) {
        printf("Average: %f\n", sum / count); // Output average
    } else {
        printf("No numbers read\n");
    }
    return 0;
}

Program Explanation

• <span>fopen</span>: Used to open a file at a specified path.
• <span>fscanf</span>: Reads data from an opened file in a specified format (here, floating-point numbers).
• <span>EOF</span>: Represents “end of file”, used here to determine if the end of the input stream has been reached.
• <span>fclose</span>: Used to close an opened file.

Through the above code, we can extract all floating-point numbers from a text file named <span>data.txt</span> and calculate their average.

Data Storage

When we need to save results or temporarily cache large amounts of data, we can utilize C language’s powerful structures and binary writing capabilities to efficiently write complex data structures to disk.

2. Data Storage Example

Below is an example program that saves student grade information to a binary file:

#include <stdio.h>
#include <stdlib.h>
struct Student {
    int id;
    char name[50];
};
int main() {
    FILE *file;
    struct Student student;

    file = fopen("students.dat", "wb"); // Open/create binary file in write mode
    if (file == NULL) {
        perror("Cannot create student record");
        return EXIT_FAILURE; // File operation failed
    }

    for (int i = 0; i < 5; i++) {
        student.id = i + 1;
        snprintf(student.name, sizeof(student.name), "Student%d", student.id);
        fwrite(&student, sizeof(struct Student), 1, file); // Write student record to binary
    }

    fclose(file);
    printf("Successfully written student records.\n");
    return EXIT_SUCCESS;
}

Program Explanation

• Uses a structure to define student information, including <span>id</span> and <span>name</span> fields.
• Uses the <span>fopen</span> function in “wb” mode (write binary) to create or open a new document named <span>students.dat</span>.
• In the loop, sets ID and names for 5 students, and uses <span>fwrite</span> to write each student’s information to disk.

Through this method, complex objects can be efficiently persisted, and subsequent processing can be performed as needed, such as including more fields or dynamically adding records.

Conclusion

In this article, we explored the basic applications of C language in the big data environment, including how to relatively simply implement data reading and storage. Although C is a low-level programming language, its high performance is a necessary condition for large-scale data operations. Therefore, learning to utilize C to implement these functions will lay a foundation for a deeper understanding of the importance of embedded systems and performance optimization.