Handling Large Files

When dealing with large amounts of data that might not fit into memory, you can read or write the data in chunks instead of processing the entire file at once. This technique, called streaming, allows your application to handle large files efficiently.

Writing Large Files in Chunks

Here’s an example of writing a large amount of data in chunks:

1#include <SDL.h>
2#include <iostream>
3
4namespace File {
5void WriteChunk(const std::string& Path,
6                const char* Data, size_t Size) {
7  SDL_RWops* Handle{
8    SDL_RWFromFile(Path.c_str(), "ab")
9  };
10
11  if (!Handle) {
12    std::cout << "Error opening file: "
13      << SDL_GetError();
14    return;
15  }
16
17  SDL_RWwrite(Handle, Data,
18    sizeof(char), Size); 
19  SDL_RWclose(Handle);
20}
21}

Reading Large Files in Chunks

Similarly, you can read large files in chunks:

1#include <SDL.h>
2#include <iostream>
3
4namespace File {
5void ReadChunk(const std::string& Path,
6               size_t ChunkSize) {
7  SDL_RWops* Handle{
8    SDL_RWFromFile(Path.c_str(), "rb")
9  };
10
11  if (!Handle) {
12    std::cout << "Error opening file: "
13      << SDL_GetError();
14    return;
15  }
16
17  char* Buffer{new char[ChunkSize]};
18
19  size_t BytesRead;
20  while ((BytesRead = SDL_RWread(
21    Handle, Buffer, sizeof(char),
22    ChunkSize)) > 0) {
23    std::cout.write(Buffer, BytesRead);
24  }
25
26  delete[] Buffer;
27  SDL_RWclose(Handle);
28}
29}

Advantages of Streaming

• Memory Efficiency: By processing the file in smaller parts, you avoid using large amounts of memory.
• Scalability: This approach allows your program to handle files of virtually any size, constrained only by available disk space.

Practical Considerations

• Chunk Size: The size of each chunk is a balance between memory usage and performance. Smaller chunks reduce memory usage, but too small chunks can lead to performance overhead.
• Data Consistency: When working with structured data, ensure that chunks are processed in a way that preserves the structure (e.g., avoiding splitting in the middle of a record).

This method is particularly useful when working with log files, media files, or any scenario where you need to process large datasets efficiently.