kevinjqliu commented on code in PR #1354:
URL: https://github.com/apache/iceberg-python/pull/1354#discussion_r1855235419
##########
tests/io/test_pyarrow_stats.py:
##########
@@ -681,6 +685,39 @@ def test_stats_types(table_schema_nested: Schema) -> None:
]
+def test_read_missing_statistics() -> None:
+ # write statistics for only for "strings" column
+ metadata, table_metadata =
construct_test_table(write_statistics=["strings"])
+
+ # expect only "strings" column to have statistics in metadata
+ assert metadata.row_group(0).column(0).is_stats_set is True
+ assert metadata.row_group(0).column(0).statistics is not None
+
+ # expect all other columns to have no statistics
+ for r in range(metadata.num_row_groups):
+ for pos in range(1, metadata.num_columns):
+ assert metadata.row_group(r).column(pos).is_stats_set is False
+ assert metadata.row_group(r).column(pos).statistics is None
+
+ schema = get_current_schema(table_metadata)
+ statistics = data_file_statistics_from_parquet_metadata(
+ parquet_metadata=metadata,
+ stats_columns=compute_statistics_plan(schema,
table_metadata.properties),
+ parquet_column_mapping=parquet_path_to_id_mapping(schema),
+ )
+
+ datafile = DataFile(**statistics.to_serialized_dict())
+
+ # expect only "strings" column values to be reflected in the
+ # upper_bound, lower_bound and null_value_counts props of datafile
+ assert len(datafile.lower_bounds) == 1
+ assert datafile.lower_bounds[1].decode() == "aaaaaaaaaaaaaaaa"
Review Comment:
ah i see, for readability, wdyt about something like
```
string_col_idx = 1
datafile.lower_bounds[string_col_idx]
```
##########
tests/io/test_pyarrow_stats.py:
##########
@@ -681,6 +685,39 @@ def test_stats_types(table_schema_nested: Schema) -> None:
]
+def test_read_missing_statistics() -> None:
+ # write statistics for only for "strings" column
+ metadata, table_metadata =
construct_test_table(write_statistics=["strings"])
+
+ # expect only "strings" column to have statistics in metadata
+ assert metadata.row_group(0).column(0).is_stats_set is True
+ assert metadata.row_group(0).column(0).statistics is not None
+
+ # expect all other columns to have no statistics
+ for r in range(metadata.num_row_groups):
+ for pos in range(1, metadata.num_columns):
+ assert metadata.row_group(r).column(pos).is_stats_set is False
+ assert metadata.row_group(r).column(pos).statistics is None
+
+ schema = get_current_schema(table_metadata)
+ statistics = data_file_statistics_from_parquet_metadata(
+ parquet_metadata=metadata,
+ stats_columns=compute_statistics_plan(schema,
table_metadata.properties),
+ parquet_column_mapping=parquet_path_to_id_mapping(schema),
+ )
+
+ datafile = DataFile(**statistics.to_serialized_dict())
+
+ # expect only "strings" column values to be reflected in the
+ # upper_bound, lower_bound and null_value_counts props of datafile
+ assert len(datafile.lower_bounds) == 1
+ assert datafile.lower_bounds[1].decode() == "aaaaaaaaaaaaaaaa"
+ assert len(datafile.upper_bounds) == 1
+ assert datafile.upper_bounds[1].decode() == "zzzzzzzzzzzzzzz{"
+ assert len(datafile.null_value_counts) == 1
+ assert datafile.null_value_counts[1] == 1
Review Comment:
ah
https://github.com/apache/iceberg-python/blob/939d325693e5a484bed0377310d49f04eb1fef31/pyiceberg/io/pyarrow.py#L2305-L2306
its calculated in `to_serialized_dict`. `column_aggregates` is converted to
`lower_bounds` and `upper_bounds`
##########
tests/io/test_pyarrow_stats.py:
##########
@@ -681,6 +685,39 @@ def test_stats_types(table_schema_nested: Schema) -> None:
]
+def test_read_missing_statistics() -> None:
+ # write statistics for only for "strings" column
+ metadata, table_metadata =
construct_test_table(write_statistics=["strings"])
+
+ # expect only "strings" column to have statistics in metadata
+ assert metadata.row_group(0).column(0).is_stats_set is True
+ assert metadata.row_group(0).column(0).statistics is not None
+
+ # expect all other columns to have no statistics
+ for r in range(metadata.num_row_groups):
+ for pos in range(1, metadata.num_columns):
+ assert metadata.row_group(r).column(pos).is_stats_set is False
+ assert metadata.row_group(r).column(pos).statistics is None
+
+ schema = get_current_schema(table_metadata)
+ statistics = data_file_statistics_from_parquet_metadata(
+ parquet_metadata=metadata,
+ stats_columns=compute_statistics_plan(schema,
table_metadata.properties),
+ parquet_column_mapping=parquet_path_to_id_mapping(schema),
+ )
+
+ datafile = DataFile(**statistics.to_serialized_dict())
+
+ # expect only "strings" column values to be reflected in the
+ # upper_bound, lower_bound and null_value_counts props of datafile
+ assert len(datafile.lower_bounds) == 1
+ assert datafile.lower_bounds[1].decode() == "aaaaaaaaaaaaaaaa"
+ assert len(datafile.upper_bounds) == 1
+ assert datafile.upper_bounds[1].decode() == "zzzzzzzzzzzzzzz{"
+ assert len(datafile.null_value_counts) == 1
+ assert datafile.null_value_counts[1] == 1
Review Comment:
we can check the `statistics` variable, but I'm now wondering if we forgot
to propagate `column_aggregates` to DataFile.
Otherwise, why even [update
`column_aggregates`](https://github.com/apache/iceberg-python/blob/939d325693e5a484bed0377310d49f04eb1fef31/pyiceberg/io/pyarrow.py#L2387-L2388)?
##########
tests/io/test_pyarrow_stats.py:
##########
@@ -681,6 +685,39 @@ def test_stats_types(table_schema_nested: Schema) -> None:
]
+def test_read_missing_statistics() -> None:
+ # write statistics for only for "strings" column
+ metadata, table_metadata =
construct_test_table(write_statistics=["strings"])
+
+ # expect only "strings" column to have statistics in metadata
+ assert metadata.row_group(0).column(0).is_stats_set is True
+ assert metadata.row_group(0).column(0).statistics is not None
+
+ # expect all other columns to have no statistics
+ for r in range(metadata.num_row_groups):
+ for pos in range(1, metadata.num_columns):
+ assert metadata.row_group(r).column(pos).is_stats_set is False
+ assert metadata.row_group(r).column(pos).statistics is None
+
+ schema = get_current_schema(table_metadata)
+ statistics = data_file_statistics_from_parquet_metadata(
+ parquet_metadata=metadata,
+ stats_columns=compute_statistics_plan(schema,
table_metadata.properties),
+ parquet_column_mapping=parquet_path_to_id_mapping(schema),
+ )
+
+ datafile = DataFile(**statistics.to_serialized_dict())
+
+ # expect only "strings" column values to be reflected in the
+ # upper_bound, lower_bound and null_value_counts props of datafile
+ assert len(datafile.lower_bounds) == 1
+ assert datafile.lower_bounds[1].decode() == "aaaaaaaaaaaaaaaa"
+ assert len(datafile.upper_bounds) == 1
+ assert datafile.upper_bounds[1].decode() == "zzzzzzzzzzzzzzz{"
+ assert len(datafile.null_value_counts) == 1
+ assert datafile.null_value_counts[1] == 1
Review Comment:
and those are checked in the test already! thanks
##########
tests/io/test_pyarrow_stats.py:
##########
@@ -681,6 +685,39 @@ def test_stats_types(table_schema_nested: Schema) -> None:
]
+def test_read_missing_statistics() -> None:
+ # write statistics for only for "strings" column
+ metadata, table_metadata =
construct_test_table(write_statistics=["strings"])
+
+ # expect only "strings" column to have statistics in metadata
+ assert metadata.row_group(0).column(0).is_stats_set is True
+ assert metadata.row_group(0).column(0).statistics is not None
+
+ # expect all other columns to have no statistics
+ for r in range(metadata.num_row_groups):
+ for pos in range(1, metadata.num_columns):
+ assert metadata.row_group(r).column(pos).is_stats_set is False
+ assert metadata.row_group(r).column(pos).statistics is None
+
+ schema = get_current_schema(table_metadata)
+ statistics = data_file_statistics_from_parquet_metadata(
+ parquet_metadata=metadata,
+ stats_columns=compute_statistics_plan(schema,
table_metadata.properties),
+ parquet_column_mapping=parquet_path_to_id_mapping(schema),
+ )
+
+ datafile = DataFile(**statistics.to_serialized_dict())
+
+ # expect only "strings" column values to be reflected in the
+ # upper_bound, lower_bound and null_value_counts props of datafile
+ assert len(datafile.lower_bounds) == 1
+ assert datafile.lower_bounds[1].decode() == "aaaaaaaaaaaaaaaa"
+ assert len(datafile.upper_bounds) == 1
+ assert datafile.upper_bounds[1].decode() == "zzzzzzzzzzzzzzz{"
+ assert len(datafile.null_value_counts) == 1
+ assert datafile.null_value_counts[1] == 1
Review Comment:
weird, [`DataFileStatistics` sets the
`column_aggregates`](https://github.com/apache/iceberg-python/blob/939d325693e5a484bed0377310d49f04eb1fef31/pyiceberg/io/pyarrow.py#L2409),
which does not exist in
[DataFile](https://github.com/apache/iceberg-python/blob/63169004facb053d3ac3725388411ee7a05c4156/pyiceberg/manifest.py#L311-L330)
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