Controlled input
Sequential reads and bounded channels limit memory pressure.
Compression and archiving engine
Go engine for processing large files in parallel while keeping memory controlled and integrity verifiable.
Technical vision
GGCompress processes large files with sequential reads, parallel processing, ordered writing, and a verifiable .ggc format.
versioned format with deterministic manifest and chunk table
Sequential reads and bounded channels limit memory pressure.
Worker pools process chunks in parallel with buffer reuse.
Extraction uses temporary staging and publishes the result only after full validation.
Execution flow
GGCompress processes large files with sequential reads, parallel processing, ordered writing, and a verifiable .ggc format.
LARGE FILE -> BOUNDED CHUNKS -> WORKERS -> ORDERED OUTPUT -> CHECKSUM
Files, directories, and symbolic links enter the deterministic manifest of the .ggc format.
Workers process chunks with bounded channels and ordered writing.
Per-chunk checksums and global SHA-256 validate the result before final publication.
Engineering decisions
The format stores a deterministic manifest, chunk table, files, directories, and symbolic links.
Worker pools, bounded channels, and buffer reuse control memory during parallel processing.
The result is published only after full validation in temporary staging.
Risk controls
Per-chunk checksums and global SHA-256 verify integrity.
Temporary staging avoids publishing a result before full validation.
Stack
Outcome
The project includes measurements for workers, chunk size, throughput, compression ratio, speedup, and peak heap without exposing values not provided.