Why Writing HDF5 Chunks Piece-by-Piece Actually Fails
The Question (March 20, 2023)
The OP wanted to bypass copying and buffering in memory by writing HDF5 chunks in parts—i.e., building them incrementally. They’d heard of using H5Dget_chunk_info plus pwrite() to patch up chunk contents manually, especially in uncompressed scenarios.
My Response (March 24, 2023)
Let me clarify the constraints first: a chunk is an indivisible IO unit in HDF5. It is processed as a single atomic job—particularly vital if filters or compression are applied. That’s baked into the library semantics and reflects how most storage and memory subsystems work.
Here’s how you'd typically handle data in that model:
Chunk-based pipeline (e.g., with block ciphers):
1. pread(fd, data, full_chunk_size, offset)
2. Repeat until the entire chunk is loaded (must be whole)
3. Apply filters/pipelines to the chunk
4. Write or process…
Given this model, partial chunk writes simply don’t make sense—and won’t be accepted by HDF5’s filter chain integrity checks.
What You Should Do Instead
- Read the entire chunk, decode it, process your changes, then write the full chunk back. It’s the only correct way.
- If naive, direct chunk operations hit 90%+ of NVMe bandwidth in benchmarks, you're already in a sweet spot—focus on optimizing higher-level logic.
- H5CPP’s
h5::packet_tableelevates this approach: it abstracts buffer management and chunk alignment, so you can safely accumulate data from multiple sources and efficiently flush complete chunks.
TL;DR
| Chunk Behavior | You Must Do | H5CPP Helps With |
|---|---|---|
| Filter/compression atomicity | Always read and write full chunk | h5::packet_table handles pre-buffering and alignment |
| Fragment writes | Not supported | Use full chunk replacement workflow |
| Performance on NVMe | Good if chunked properly | Fine-tuned by h5::append() internals |
Let me know if you'd like a code breakdown of h5::packet_table or a deep dive on how to handle chunk durability and concurrency in a streaming pipeline.