Binary Data Handling

Binary Data Handling

Overview

FLEXON CLI provides robust support for handling binary data efficiently. This guide covers best practices and common patterns for working with binary data.

Features

1. Binary Data Types

• Raw bytes
• Streams
• Blobs
• Memory-mapped files

2. Optimization Techniques

• Zero-copy operations
• Streaming support
• Memory pooling
• Buffer management

Implementation

Basic Usage

// Example of handling binary data
var binaryData = new byte[] { ... };
var options = new FlexonBinaryOptions
{
    Compression = CompressionType.GZIP,
    ChunkSize = 8192
};

flexon.SerializeBinary(binaryData, "output.flexon", options);

Streaming

// Example of streaming binary data
using var stream = new FlexonBinaryStream("large.flexon");
await stream.WriteAsync(binaryChunk);

Best Practices

1. Memory Management

• Use buffer pools
• Implement proper disposal
• Handle large files efficiently
• Monitor memory usage

2. Performance

• Choose appropriate chunk sizes
• Use async operations
• Implement caching
• Optimize for your use case

3. Error Handling

• Handle corrupted data
• Implement checksums
• Validate binary content
• Provide recovery options

Common Scenarios

1. Large File Handling

// Example of handling large files
using var reader = new FlexonBinaryReader("large.flexon");
await foreach (var chunk in reader.ReadChunksAsync())
{
    // Process chunk
}

2. Image Processing

// Example of image handling
var imageData = await flexon.ReadBinaryAsync<ImageData>("image.flexon");
imageData.Process();
await flexon.WriteBinaryAsync("processed.flexon", imageData);

Performance Tips

1. Buffering

• Use appropriate buffer sizes
• Implement double buffering
• Pool frequently used buffers
• Monitor buffer usage

2. Compression

• Choose compression level
• Consider data type
• Balance size vs speed
• Use hardware acceleration

Troubleshooting

Common Issues

1. Out of memory errors
2. Performance bottlenecks
3. Data corruption
4. Concurrency problems

Solutions

1. Implement streaming
2. Optimize buffer sizes
3. Add data validation
4. Use proper synchronization

Related Topics

• Performance Optimization
• Error Handling
• Schema Validation
• Type System