lawofcycles commented on code in PR #3320:
URL: https://github.com/apache/iceberg-python/pull/3320#discussion_r3605688324
##########
pyiceberg/table/update/snapshot.py:
##########
@@ -132,8 +172,11 @@ def __init__(
self._parent_snapshot_id = (
snapshot.snapshot_id if (snapshot :=
self._transaction.table_metadata.snapshot_by_name(self._target_branch)) else
None
)
+ self._starting_snapshot_id = self._parent_snapshot_id
self._predicate = AlwaysFalse()
self._case_sensitive = True
+ self._commit_window = None
+ self._isolation_level_property: str =
TableProperties.WRITE_DELETE_ISOLATION_LEVEL
Review Comment:
Added `TableMetadata.isolation_level(operation)` and dropped the
`_isolation_level_property` field. The producer just carries the operation now,
and `_validate_concurrency` resolves the level from the metadata, so the lookup
lives in one place and still picks up refreshed properties on retry.
I based it on the logical operation (delete vs update) rather than the
snapshot operation, to match Java.
[`SparkRowLevelOperationBuilder.isolationLevel(properties,
command)`](https://github.com/apache/iceberg/blob/4b4eb38cf6dda7b43faeb40eb00aa5db424d2ecb/spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/source/SparkRowLevelOperationBuilder.java#L95-L113)
picks the property from the SQL command and applies it to the whole operation,
including copy on write, so a copy on write delete stays on
write.delete.isolation-level. Going by the snapshot operation would push the
rewrite part of a delete onto write.update, which diverges.
The tradeoff is that a small operation marker still travels with the
producer.
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