corleyma commented on code in PR #1427:
URL: https://github.com/apache/iceberg-python/pull/1427#discussion_r1890655836
##########
pyiceberg/table/__init__.py:
##########
@@ -1423,6 +1451,66 @@ def plan_files(self) -> Iterable[FileScanTask]:
for data_entry in data_entries
]
+ def _target_split_size(self) -> int:
+ table_value = property_as_int(
+ self.table_metadata.properties, TableProperties.READ_SPLIT_SIZE,
TableProperties.READ_SPLIT_SIZE_DEFAULT
+ )
+ return property_as_int(self.options, TableProperties.READ_SPLIT_SIZE,
table_value) # type: ignore
+
+ def _loop_back(self) -> int:
+ table_value = property_as_int(
+ self.table_metadata.properties,
TableProperties.READ_SPLIT_LOOKBACK, TableProperties.READ_SPLIT_LOOKBACK_DEFAULT
+ )
+ return property_as_int(self.options,
TableProperties.READ_SPLIT_LOOKBACK, table_value) # type: ignore
+
+ def _split_open_file_cost(self) -> int:
+ table_value = property_as_int(
+ self.table_metadata.properties,
+ TableProperties.READ_SPLIT_OPEN_FILE_COST,
+ TableProperties.READ_SPLIT_OPEN_FILE_COST_DEFAULT,
+ )
+ return property_as_int(self.options,
TableProperties.READ_SPLIT_OPEN_FILE_COST, table_value) # type: ignore
+
+ def plan_task(self) -> Iterable[CombinedFileScanTask]:
Review Comment:
Re what @ConeyLiu was mentioning about the issues he encountered with Ray, I
think it would be reasonable for pyiceberg to have this more nuanced
distributed planning logic in a private API and (if we wanted to), to expose a
RayDatasets implementation that uses the private API... but I'd vote against
committing to this planning logic in a public API for the reasons outlined
above (engines want to bring their own logic, and pyiceberg may well want to
significantly change this logic for itself in the future to the extent that we
do continue to embed more query engine functionality for convenience).
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