jorisvandenbossche commented on code in PR #6775:
URL: https://github.com/apache/iceberg/pull/6775#discussion_r1192188646
##########
python/pyiceberg/io/pyarrow.py:
##########
@@ -498,6 +504,49 @@ def expression_to_pyarrow(expr: BooleanExpression) ->
pc.Expression:
return boolean_expression_visit(expr, _ConvertToArrowExpression())
+@lru_cache
+def _get_file_format(file_format: FileFormat, **kwargs: Dict[str, Any]) ->
ds.FileFormat:
+ if file_format == FileFormat.PARQUET:
+ return ds.ParquetFileFormat(**kwargs)
+ else:
+ raise ValueError(f"Unsupported file format: {file_format}")
+
+
+def _construct_fragment(fs: FileSystem, data_file: DataFile,
file_format_kwargs: Dict[str, Any] = EMPTY_DICT) -> ds.Fragment:
+ _, path = PyArrowFileIO.parse_location(data_file.file_path)
+ return _get_file_format(data_file.file_format,
**file_format_kwargs).make_fragment(path, fs)
+
+
+def _read_deletes(fs: FileSystem, data_file: DataFile) -> Dict[str,
pa.ChunkedArray]:
+ delete_fragment = _construct_fragment(
+ fs, data_file, file_format_kwargs={"dictionary_columns":
("file_path",), "pre_buffer": True, "buffer_size": ONE_MEGABYTE}
+ )
+ table = ds.Scanner.from_fragment(fragment=delete_fragment).to_table()
+ table.unify_dictionaries()
+ return {
+ file.as_py(): table.filter(pc.field("file_path") == file).column("pos")
+ for file in table.column("file_path").chunks[0].dictionary
+ }
+
+
+def _create_positional_deletes_indices(positional_deletes:
List[pa.ChunkedArray], fn_rows: Callable[[], int]) -> pa.Array:
+ sorted_deleted = merge(*positional_deletes)
+
+ def generator() -> Generator[int, None, None]:
+ deleted_pos = next(sorted_deleted).as_py() # type: ignore
+ for pos in range(fn_rows()):
+ if deleted_pos == pos:
+ try:
+ deleted_pos = next(sorted_deleted).as_py() # type: ignore
+ except StopIteration:
+ deleted_pos = -1
+ else:
+ yield pos
+
+ # Filter on the positions
+ return pa.array(generator(), type=pa.int64())
Review Comment:
Would something like this work?
```
In [20]: positional_deletes = [pa.chunked_array([[1, 3], [5, 7]]),
pa.chunked_array([[8], [10, 14]])]
In [21]: merged = pa.chunked_array([arr for carr in positional_deletes for
arr in carr.chunks])
In [22]: np.setdiff1d(np.arange(20), merged)
Out[22]: array([ 0, 2, 4, 6, 9, 11, 12, 13, 15, 16, 17, 18, 19])
```
(assuming that `fn_rows()` returns 20)
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