Principle:Apache Paimon Blob Metadata Writing
| Knowledge Sources | |
|---|---|
| Domains | Data_Lake, Blob_Storage |
| Last Updated | 2026-02-07 00:00 GMT |
Overview
Mechanism for writing serialized blob descriptors as table metadata alongside non-blob columns.
Description
Blob metadata writing stores serialized BlobDescriptor bytes in the blob column of a Paimon table along with regular metadata columns (such as IDs, filenames, content types, and other attributes). The writing process involves several coordinated components:
- BlobFormatWriter handles the special serialization of blob columns, writing them with magic numbers and CRC32 checksums for data integrity verification.
- DataBlobWriter coordinates writing both data columns (regular columns) and blob columns (descriptor columns) into the appropriate file formats.
- TableWrite provides the high-level write_arrow() interface that accepts a standard PyArrow table.
After writing, the standard prepare_commit + commit pattern makes the metadata visible to readers. This two-phase commit protocol ensures atomicity -- either all metadata from a write batch becomes visible, or none of it does.
The actual blob data (images, videos, documents) is stored externally in its original storage location; only the lightweight descriptors are written to the Paimon table.
Usage
Use after constructing and serializing BlobDescriptor objects to persist them in the Paimon table. The typical workflow is:
- Build a PyArrow table with regular columns and serialized descriptor bytes in the blob column
- Create a batch write builder from the table
- Write the PyArrow table using write_arrow()
- Call prepare_commit() to prepare commit messages
- Call commit() to finalize the write and make data visible
This is the third step in the blob storage pipeline, following schema definition and descriptor construction.
Theoretical Basis
Separating metadata writes from blob data storage follows the principle of write amplification reduction. Metadata writes are small and fast (typically a few dozen bytes per descriptor), while blob data remains in its original storage location without being copied or moved.
The two-phase commit protocol (prepare_commit + commit) implements atomic visibility. All metadata from a single write batch becomes visible atomically, preventing partial reads where some descriptors are visible but others from the same batch are not.
The BlobFormatWriter's use of magic numbers and CRC32 checksums follows the principle of defensive serialization. Every blob entry can be validated on read, detecting corruption from storage errors, incomplete writes, or other data integrity issues. This is especially important for descriptor data, where a corrupted URI or offset could lead to reading incorrect blob content.
The coordination between DataBlobWriter and BlobFormatWriter follows the strategy pattern -- the writing logic for blob columns is encapsulated in a specialized writer, while the overall write orchestration remains in the data writer.