Feature: Add metadata-only replace API to Table for REPLACE snapshot operations
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Evaluación
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Aptitud para principiantes
- 28/100
Línea de trabajo
Comienza con pyiceberg/table/update/snapshot.py y las APIs de snapshots existentes de Table y Transaction, y luego compara el comportamiento propuesto con la interfaz RewriteFiles de Java. Revisa tests/table/test_snapshots.py, especialmente test_invalid_operation(), y añade cobertura específica para intercambios de archivos, números de secuencia y operation=REPLACE. Se considera terminado cuando el reemplazo basado únicamente en metadatos funciona atómicamente con entradas Iterable[DataFile] y evita la serialización Parquet.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Feature Request / Improvement
Description
This issue proposes implementing a metadata-only replace API in PyIceberg, enabling orchestrators to submit a set of DataFiles to delete and a set of DataFiles to append in a single atomic transaction.
This functionality is critical for maintenance operations such as data compaction (the "small files" problem), ensuring the logical state of the table remains unaltered while physical data layout is optimized.
Background
In a current PR (#3124, part of #1092), PyIceberg's replace semantics are tightly coupled with PyArrow dataframes (def replace(self, df: pa.Table)). This approach introduces several architectural flaws:
- Coupling Physical Serialization with Metadata: It forces a
.parquetwrite serialization hook directly into the snapshot commit transaction, increasing the risk of schema degradation and blocking network topologies. - Missing
Operation.REPLACE: The current system uses primitives that log asAPPENDorOVERWRITE, muddying the table history and complicating snapshot expiry/maintenance. - Java Inconsistency: This severely drifts from Java Iceberg's native
org.apache.iceberg.RewriteFilesspecification, which strictly isolates the builder into accepting purelyDataFilepointers.
Proposed Solution
To fix this and achieve logical equivalence, we must implement an exact port of Java's RewriteFiles builder API into PyIceberg's native _SnapshotProducer engine.
-
Introduce
_RewriteFilesSnapshot Producer:
Add a new_RewriteFilesclass that specifically targets replacing existing files. This class will implement:_deleted_entries(): To find the existing target files and re-emit them asDELETEDentries, defensively keeping their ancestralsequence_numbers completely intact for time travel compatibility._existing_manifests(): To scavenge unchanged manifests natively, skipping deep rewrites and only mutating manifests impacted by the deleted files.
-
Builder Hook Implementation:
ImplementUpdateSnapshot().replace()which configures the transaction withOperation.REPLACE. -
Expose Shorthands on Table & Transaction:
AddreplaceAPIs on bothTableandTransactiontakingIterable[DataFile]arguments to elegantly wrap the snapshot mutation:def replace( self, files_to_delete: Iterable[DataFile], files_to_add: Iterable[DataFile], snapshot_properties: dict[str, str] = EMPTY_DICT, branch: str | None = MAIN_BRANCH, ) -> None: ...
Notable canges
replace()API implemented on bothTableandTransactionusingIterable[DataFile].- PyArrow
.parquetwrite logic decoupled from the metadata transaction. _RewriteFilescorrectly copies ancestralsequence_numberpointers forDELETEDandEXISTINGmanifest entries.- Snapshots committed via the
replace()hook possess a Summary containingoperation=Operation.REPLACE. - Unit tests pass simulating data file swaps and summary verifications.
Related Java API
Inspired heavily by Java's builder interface: https://github.com/apache/iceberg/blob/main/api/src/main/java/org/apache/iceberg/RewriteFiles.java
AI Disclosure
AI was used to help understand the code base and draft code changes. All code changes have been thoroughly reviewed, ensuring that the code changes are in line with a broader understanding of the codebase.
- Worth deeper review after AI-assistance:
- The
test_invalid_operation()intests/table/test_snapshots.pypreviously usedOperation.REPLACEas a value to test invalid operations, but with this changeOperation.REPLACEbecomes valid. In place I just put a dummy Operation. - The
_RewriteFilesinpyiceberg/table/update/snapshot.pyoverrides the_deleted_entriesand_existing_manifestsfunctions. I sought to test this thoroughly that it was done correctly. I am thinking it's possible to improve the test suite to make this more rigorous. I am open to suggestions on how that could be done.
- Lenguaje dominante
- Python
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- PR fusionados (30 d)
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