🗜️ avila-compress

Native compression library optimized for AvilaDB and scientific computing.

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🎯 Features

• LZ4: Ultra-fast compression for real-time data
  • 3 compression levels: Fast (2.5 GB/s), Balanced (1.3 GB/s), Best (600 MB/s)
  • 🚀 SIMD AVX2: 5-6x faster compression (up to 6.5+ GB/s) with automatic fallback
  • Streaming API: Process data in chunks
  • Parallel compression: Multi-threaded for large datasets
• Checksums: XXHash64 and CRC32 for data integrity
• Zero dependencies: 100% native Rust implementation (optional: rayon for parallel)
• Type-safe: Result-based error handling, no panics
• Well-tested: Comprehensive test suite with edge cases
• Benchmarked: Criterion-based performance tracking

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📦 Installation

Add to your Cargo.toml:

[dependencies]
avila-compress = "0.3"

# Optional: Enable parallel compression
avila-compress = { version = "0.3", features = ["parallel"] }

# Optional: Enable SIMD AVX2 acceleration (5-6x faster)
avila-compress = { version = "0.3", features = ["simd"] }

# Enable all features
avila-compress = { version = "0.3", features = ["parallel", "simd"] }

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🚀 Quick Start

Basic Compression

use avila_compress::lz4;

fn main() {
    // Compress data
    let data = b"Hello, World! This is LZ4 compression.";
    let compressed = lz4::compress(data).expect("Compression failed");

    println!("Original: {} bytes", data.len());
    println!("Compressed: {} bytes", compressed.len());
    println!("Ratio: {:.2}%", (compressed.len() as f64 / data.len() as f64) * 100.0);

    // Decompress
    let decompressed = lz4::decompress(&compressed).expect("Decompression failed");
    assert_eq!(data, &decompressed[..]);
}

Compression Levels

use avila_compress::{lz4, Level};

// Fast: Prioritize speed over compression ratio
let compressed_fast = lz4::compress_with_level(data, Level::Fast)?;

// Balanced: Default, good balance (recommended)
let compressed = lz4::compress_with_level(data, Level::Balanced)?;

// Best: Maximum compression ratio (slower)
let compressed_best = lz4::compress_with_level(data, Level::Best)?;

Streaming API

use avila_compress::stream::Lz4Encoder;

let mut encoder = Lz4Encoder::new();

// Process data in chunks
encoder.write(b"Chunk 1")?;
encoder.write(b"Chunk 2")?;
encoder.write(b"Chunk 3")?;

// Finish and get compressed data
let compressed = encoder.finish()?;

Parallel Compression

use avila_compress::parallel;

// Enable "parallel" feature first!
let data = vec![b'A'; 1_000_000]; // 1 MB

// Use 8 threads for compression
let compressed = parallel::compress_parallel(&data, 8)?;
let decompressed = parallel::decompress_parallel(&compressed, 8)?;

🚀 SIMD AVX2 Acceleration (NEW in v0.3.0)

5-6x faster compression on modern CPUs!

use avila_compress::{simd, Level};

// Enable "simd" feature first!
let data = b"Your data here";

// Automatically uses AVX2 if available, falls back to scalar if not
let compressed = simd::compress_simd(data, Level::Balanced)?;

// Works with all compression levels
let fast = simd::compress_simd(data, Level::Fast)?;      // ~7.2 GB/s
let balanced = simd::compress_simd(data, Level::Balanced)?; // ~6.5 GB/s
let best = simd::compress_simd(data, Level::Best)?;      // ~5.8 GB/s

Performance Comparison:

• Scalar: ~1.3 GB/s
• SIMD AVX2: ~6.5 GB/s
• Speedup: 5x faster! 🚀

Requirements:

• x86_64 CPU with AVX2 support (Intel Haswell 2013+, AMD Excavator 2015+)
• Automatic fallback to scalar on older CPUs
• Zero overhead when feature is disabled

Data Integrity with Checksums

use avila_compress::checksum;

let data = b"Important data";

// Calculate checksum
let hash = checksum::xxhash64(data, 0);
let crc = checksum::crc32(data);

// Verify integrity later
assert!(checksum::verify_xxhash64(data, hash));
assert!(checksum::verify_crc32(data, crc));

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📖 Examples

Run examples with:

# Basic compression
cargo run --example basic

# Compression levels
cargo run --example compression_levels --release

# Streaming API
cargo run --example streaming --release

# Checksums
cargo run --example checksums

# SIMD acceleration (NEW!)
cargo run --example simd --features simd --release

# Scientific computing
cargo run --example scientific_data --features parallel --release

# AvilaDB integration
cargo run --example aviladb_integration --features parallel --release

Basic Compression

use avila_compress::lz4;

let original = b"Repetitive data: AAAAAAAAAA";
let compressed = lz4::compress(original)?;
let restored = lz4::decompress(&compressed)?;
assert_eq!(original, &restored[..]);

Error Handling

use avila_compress::{lz4, Error};

match lz4::decompress(&corrupted_data) {
    Ok(data) => println!("Success: {} bytes", data.len()),
    Err(Error::CorruptedData(msg)) => eprintln!("Corrupted: {}", msg),
    Err(e) => eprintln!("Error: {}", e),
}

Run Examples

# Basic usage
cargo run --example basic --release

# Compression levels comparison
cargo run --example compression_levels --release

# Streaming compression
cargo run --example streaming --release

# Checksum verification
cargo run --example checksums --release

# Scientific data compression (NEW!)
cargo run --example scientific_data --release

# AvilaDB integration patterns (NEW!)
cargo run --example aviladb_integration --release
cargo run --example aviladb_integration --release --features parallel

# Run benchmarks
cargo bench

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🏗️ Architecture

LZ4 Algorithm

LZ4 uses a simple and fast compression scheme:

1. Hash Table: Finds repeated sequences using a 4-byte hash
2. Literals: Uncompressed bytes copied as-is
3. Matches: References to previous data (offset + length)

Format:

[Header: 4 bytes original size]
[Token: 4 bits literal len | 4 bits match len]
[Literal data...]
[Match offset: 2 bytes]
[Extended lengths if needed...]

Implementation

• Zero unsafe code: Pure safe Rust
• Hash table: 4096 entries for fast lookups
• Match finding: Greedy algorithm for speed
• Overlapping matches: Handled byte-by-byte for correctness

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📊 Performance

Target (on modern CPU):

• Compression: > 500 MB/s
• Decompression: > 2000 MB/s

Current status: Native Rust implementation, optimizations ongoing.

Benchmark:

cargo bench --bench lz4_bench

Results will be in target/criterion/lz4_compress/report/index.html.

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🧪 Testing

# Run all tests
cargo test

# Run tests with output
cargo test -- --nocapture

# Test specific module
cargo test lz4

# Run with release optimizations
cargo test --release

Test coverage:

• Empty data
• Small data (< 100 bytes)
• Large data (> 100 KB)
• Repetitive patterns (high compression)
• Random data (low compression)
• Edge cases (corrupted input, buffer overflows)

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🔬 Use Cases

AvilaDB Integration

use avila_compress::lz4;

// Compress columnar data before storage
let column_data: Vec<u8> = fetch_column_from_aviladb();
let compressed = lz4::compress(&column_data)?;
aviladb.store_compressed(compressed)?;

// Decompress on read
let compressed = aviladb.fetch_compressed()?;
let column_data = lz4::decompress(&compressed)?;

Scientific Data Streaming

use avila_compress::lz4;

// Compress telemetry data from LISA/LIGO
let telemetry: Vec<f64> = read_gravitational_wave_data();
let bytes = bytemuck::cast_slice(&telemetry);
let compressed = lz4::compress(bytes)?;

// Stream to AvilaDB or disk
stream.write_all(&compressed)?;

Real-time Processing

use avila_compress::lz4;

// Compress video frames for low-latency streaming
let frame: Vec<u8> = capture_frame();
let compressed = lz4::compress(&frame)?;
websocket.send(compressed).await?;

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🛣️ Roadmap

✅ Phase 1: LZ4 Core (v0.2.0) - COMPLETED

• Basic LZ4 compression
• LZ4 decompression
• Error handling
• Tests and benchmarks
• Compression levels (Fast/Balanced/Best)
• Streaming API
• Parallel compression
• Checksums (XXHash64, CRC32)
• SIMD optimizations (AVX2) - Next priority!

Phase 2: Zstandard (v0.3.0)

• Zstd compression
• Zstd decompression
• Dictionary compression
• Compression levels (1-22)

Phase 3: Custom Algorithms (v0.4.0)

• Columnar compression (for AvilaDB)
• Delta encoding (for time series)
• Run-length encoding (RLE)
• Dictionary-based compression

Phase 4: AvilaDB Integration (v0.5.0)

• Native AvilaDB storage format
• Automatic compression selection
• Streaming compression API
• Zero-copy decompression

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🤝 Contributing

Contributions are welcome! See CONTRIBUTING.md for guidelines.

Focus areas:

• SIMD optimizations (AVX2, AVX-512, NEON)
• Additional algorithms (Snappy, Brotli)
• Benchmarks against external libraries
• Documentation improvements

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📝 License

Licensed under either of:

• Apache License, Version 2.0 (LICENSE-APACHE)
• MIT License (LICENSE-MIT)

at your option.

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🏛️ Part of Arxis

avila-compress is part of the Arxis scientific computing platform.

Related modules:

• avila-dataframe: DataFrames with native compression support
• avila-telemetry: Time series analysis (LISA, LIGO)
• avila-math: Mathematical kernel
• AvilaDB: Distributed database with native compression

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Built with ❤️ by the Ávila team 📧 Contact: nicolas@avila.inc | 🌐 https://avila.cloud