Fokko commented on code in PR #7831: URL: https://github.com/apache/iceberg/pull/7831#discussion_r1257807284
########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) Review Comment: Can we initialize the structs just once? Similar to the Avro reading: https://github.com/apache/iceberg/blob/e389e4d139624a49729379acd330dd9c96187b04/python/pyiceberg/avro/__init__.py#L19-L20 ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 Review Comment: In Spark this is configurable, but I'm fine with leaving this as is right now. ########## python/tests/utils/test_file_stats.py: ########## @@ -0,0 +1,361 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + + +import math +import struct +from tempfile import TemporaryDirectory +from typing import Any, List + +import pyarrow as pa +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile +from pyiceberg.schema import Schema +from pyiceberg.utils.file_stats import BOUND_TRUNCATED_LENGHT, fill_parquet_file_metadata, parquet_schema_to_ids + + +def construct_test_table() -> pa.Buffer: + schema = pa.schema( + [pa.field("strings", pa.string()), pa.field("floats", pa.float64()), pa.field("list", pa.list_(pa.int64()))] Review Comment: Can we also add a map here? ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) + + +def int32_to_avro(value: int) -> bytes: + return struct.pack("<i", value) + + +def int64_to_avro(value: int) -> bytes: + return struct.pack("<q", value) + + +def float_to_avro(value: float) -> bytes: + return struct.pack("<f", value) + + +def double_to_avro(value: float) -> bytes: + return struct.pack("<d", value) + + +def bytes_to_avro(value: Union[bytes, str]) -> bytes: + if type(value) == str: + return value.encode() + else: + assert isinstance(value, bytes) # appeases mypy + return value + + +class StatsAggregator: + def __init__(self, type_string: str): + self.current_min: Any = None + self.current_max: Any = None + self.serialize: Any = None + + if type_string == "BOOLEAN": + self.serialize = bool_to_avro + elif type_string == "INT32": + self.serialize = int32_to_avro + elif type_string == "INT64": + self.serialize = int64_to_avro + elif type_string == "INT96": + raise NotImplementedError("Statistics not implemented for INT96 physical type") + elif type_string == "FLOAT": + self.serialize = float_to_avro + elif type_string == "DOUBLE": + self.serialize = double_to_avro + elif type_string == "BYTE_ARRAY": + self.serialize = bytes_to_avro + elif type_string == "FIXED_LEN_BYTE_ARRAY": + self.serialize = bytes_to_avro + else: + raise AssertionError(f"Unknown physical type {type_string}") + + def add_min(self, val: bytes) -> None: + if not self.current_min: + self.current_min = val + elif val < self.current_min: + self.current_min = val + + def add_max(self, val: bytes) -> None: + if not self.current_max: + self.current_max = val + elif self.current_max < val: + self.current_max = val + + def get_min(self) -> bytes: + return self.serialize(self.current_min)[:BOUND_TRUNCATED_LENGHT] + + def get_max(self) -> bytes: + return self.serialize(self.current_max)[:BOUND_TRUNCATED_LENGHT] + + +def fill_parquet_file_metadata( + df: DataFile, metadata: pq.FileMetaData, col_path_2_iceberg_id: Dict[str, int], file_size: int Review Comment: Should we move this one to `pyarrow.py`? This uses PyArrow classes that might not be installed. ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) + + +def int32_to_avro(value: int) -> bytes: + return struct.pack("<i", value) + + +def int64_to_avro(value: int) -> bytes: + return struct.pack("<q", value) + + +def float_to_avro(value: float) -> bytes: + return struct.pack("<f", value) + + +def double_to_avro(value: float) -> bytes: + return struct.pack("<d", value) + + +def bytes_to_avro(value: Union[bytes, str]) -> bytes: + if type(value) == str: + return value.encode() + else: + assert isinstance(value, bytes) # appeases mypy + return value + + +class StatsAggregator: + def __init__(self, type_string: str): + self.current_min: Any = None + self.current_max: Any = None + self.serialize: Any = None + + if type_string == "BOOLEAN": + self.serialize = bool_to_avro + elif type_string == "INT32": + self.serialize = int32_to_avro + elif type_string == "INT64": + self.serialize = int64_to_avro + elif type_string == "INT96": + raise NotImplementedError("Statistics not implemented for INT96 physical type") + elif type_string == "FLOAT": + self.serialize = float_to_avro + elif type_string == "DOUBLE": + self.serialize = double_to_avro + elif type_string == "BYTE_ARRAY": + self.serialize = bytes_to_avro + elif type_string == "FIXED_LEN_BYTE_ARRAY": + self.serialize = bytes_to_avro + else: + raise AssertionError(f"Unknown physical type {type_string}") + + def add_min(self, val: bytes) -> None: + if not self.current_min: + self.current_min = val + elif val < self.current_min: + self.current_min = val + + def add_max(self, val: bytes) -> None: + if not self.current_max: Review Comment: ```suggestion if self.current_max is not None: ``` ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) + + +def int32_to_avro(value: int) -> bytes: + return struct.pack("<i", value) + + +def int64_to_avro(value: int) -> bytes: + return struct.pack("<q", value) + + +def float_to_avro(value: float) -> bytes: + return struct.pack("<f", value) + + +def double_to_avro(value: float) -> bytes: + return struct.pack("<d", value) + + +def bytes_to_avro(value: Union[bytes, str]) -> bytes: + if type(value) == str: + return value.encode() + else: + assert isinstance(value, bytes) # appeases mypy + return value + + +class StatsAggregator: + def __init__(self, type_string: str): + self.current_min: Any = None + self.current_max: Any = None + self.serialize: Any = None + + if type_string == "BOOLEAN": + self.serialize = bool_to_avro + elif type_string == "INT32": + self.serialize = int32_to_avro + elif type_string == "INT64": + self.serialize = int64_to_avro + elif type_string == "INT96": + raise NotImplementedError("Statistics not implemented for INT96 physical type") + elif type_string == "FLOAT": + self.serialize = float_to_avro + elif type_string == "DOUBLE": + self.serialize = double_to_avro + elif type_string == "BYTE_ARRAY": + self.serialize = bytes_to_avro + elif type_string == "FIXED_LEN_BYTE_ARRAY": + self.serialize = bytes_to_avro + else: + raise AssertionError(f"Unknown physical type {type_string}") + + def add_min(self, val: bytes) -> None: + if not self.current_min: + self.current_min = val + elif val < self.current_min: + self.current_min = val + + def add_max(self, val: bytes) -> None: + if not self.current_max: + self.current_max = val + elif self.current_max < val: + self.current_max = val + + def get_min(self) -> bytes: + return self.serialize(self.current_min)[:BOUND_TRUNCATED_LENGHT] + + def get_max(self) -> bytes: + return self.serialize(self.current_max)[:BOUND_TRUNCATED_LENGHT] + + +def fill_parquet_file_metadata( + df: DataFile, metadata: pq.FileMetaData, col_path_2_iceberg_id: Dict[str, int], file_size: int +) -> None: + """ + Computes and fills the following fields of the DataFile object. + + - file_format + - record_count + - file_size_in_bytes + - column_sizes + - value_counts + - null_value_counts + - nan_value_counts + - lower_bounds + - upper_bounds + - split_offsets + + Args: + df (DataFile): A DataFile object representing the Parquet file for which metadata is to be filled. + metadata (pyarrow.parquet.FileMetaData): A pyarrow metadata object. + col_path_2_iceberg_id: A mapping of column paths as in the `path_in_schema` attribute of the colum + metadata to iceberg schema IDs. For scalar columns this will be the column name. For complex types + it could be something like `my_map.key_value.value` + file_size (int): The total compressed file size cannot be retrieved from the metadata and hence has to + be passed here. Depending on the kind of file system and pyarrow library call used, different + ways to obtain this value might be appropriate. + """ + col_index_2_id = {} + + col_names = set(metadata.schema.names) + + first_group = metadata.row_group(0) + + for c in range(metadata.num_columns): + column = first_group.column(c) + col_path = column.path_in_schema + + if col_path in col_path_2_iceberg_id: + col_index_2_id[c] = col_path_2_iceberg_id[col_path] + else: + raise AssertionError(f"Column path {col_path} couldn't be mapped to an iceberg ID") + + column_sizes: Dict[int, int] = {} + value_counts: Dict[int, int] = {} + split_offsets: List[int] = [] + + null_value_counts: Dict[int, int] = {} + nan_value_counts: Dict[int, int] = {} + + col_aggs = {} + + for r in range(metadata.num_row_groups): + # References: + # https://github.com/apache/iceberg/blob/fc381a81a1fdb8f51a0637ca27cd30673bd7aad3/parquet/src/main/java/org/apache/iceberg/parquet/ParquetUtil.java#L232 + # https://github.com/apache/parquet-mr/blob/ac29db4611f86a07cc6877b416aa4b183e09b353/parquet-hadoop/src/main/java/org/apache/parquet/hadoop/metadata/ColumnChunkMetaData.java#L184 + + row_group = metadata.row_group(r) + + data_offset = row_group.column(0).data_page_offset + dictionary_offset = row_group.column(0).dictionary_page_offset + + if row_group.column(0).has_dictionary_page and dictionary_offset < data_offset: + split_offsets.append(dictionary_offset) + else: + split_offsets.append(data_offset) + + for c in range(metadata.num_columns): + col_id = col_index_2_id[c] + + column = row_group.column(c) + + column_sizes[col_id] = column_sizes.get(col_id, 0) + column.total_compressed_size + value_counts[col_id] = value_counts.get(col_id, 0) + column.num_values + + if column.is_stats_set: + try: + statistics = column.statistics + + null_value_counts[col_id] = null_value_counts.get(col_id, 0) + statistics.null_count + + if column.path_in_schema in col_names: + # Iceberg seems to only have statistics for scalar columns + + if col_id not in col_aggs: + col_aggs[col_id] = StatsAggregator(statistics.physical_type) + + col_aggs[col_id].add_min(statistics.min) Review Comment: Do we need the intermediate `col_aggs`? I would prefer to directly write it into `{lower,upper}_bounds`. ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) + + +def int32_to_avro(value: int) -> bytes: + return struct.pack("<i", value) + + +def int64_to_avro(value: int) -> bytes: + return struct.pack("<q", value) + + +def float_to_avro(value: float) -> bytes: + return struct.pack("<f", value) + + +def double_to_avro(value: float) -> bytes: + return struct.pack("<d", value) + + +def bytes_to_avro(value: Union[bytes, str]) -> bytes: + if type(value) == str: + return value.encode() + else: + assert isinstance(value, bytes) # appeases mypy + return value + + +class StatsAggregator: + def __init__(self, type_string: str): + self.current_min: Any = None + self.current_max: Any = None + self.serialize: Any = None + + if type_string == "BOOLEAN": + self.serialize = bool_to_avro + elif type_string == "INT32": + self.serialize = int32_to_avro + elif type_string == "INT64": + self.serialize = int64_to_avro + elif type_string == "INT96": + raise NotImplementedError("Statistics not implemented for INT96 physical type") + elif type_string == "FLOAT": + self.serialize = float_to_avro + elif type_string == "DOUBLE": + self.serialize = double_to_avro + elif type_string == "BYTE_ARRAY": + self.serialize = bytes_to_avro + elif type_string == "FIXED_LEN_BYTE_ARRAY": + self.serialize = bytes_to_avro + else: + raise AssertionError(f"Unknown physical type {type_string}") + + def add_min(self, val: bytes) -> None: + if not self.current_min: + self.current_min = val + elif val < self.current_min: + self.current_min = val + + def add_max(self, val: bytes) -> None: + if not self.current_max: + self.current_max = val + elif self.current_max < val: + self.current_max = val + + def get_min(self) -> bytes: + return self.serialize(self.current_min)[:BOUND_TRUNCATED_LENGHT] + + def get_max(self) -> bytes: + return self.serialize(self.current_max)[:BOUND_TRUNCATED_LENGHT] + + +def fill_parquet_file_metadata( + df: DataFile, metadata: pq.FileMetaData, col_path_2_iceberg_id: Dict[str, int], file_size: int +) -> None: + """ + Computes and fills the following fields of the DataFile object. + + - file_format + - record_count + - file_size_in_bytes + - column_sizes + - value_counts + - null_value_counts + - nan_value_counts + - lower_bounds + - upper_bounds + - split_offsets + + Args: + df (DataFile): A DataFile object representing the Parquet file for which metadata is to be filled. + metadata (pyarrow.parquet.FileMetaData): A pyarrow metadata object. + col_path_2_iceberg_id: A mapping of column paths as in the `path_in_schema` attribute of the colum + metadata to iceberg schema IDs. For scalar columns this will be the column name. For complex types + it could be something like `my_map.key_value.value` + file_size (int): The total compressed file size cannot be retrieved from the metadata and hence has to + be passed here. Depending on the kind of file system and pyarrow library call used, different + ways to obtain this value might be appropriate. + """ + col_index_2_id = {} + + col_names = set(metadata.schema.names) + + first_group = metadata.row_group(0) + + for c in range(metadata.num_columns): + column = first_group.column(c) + col_path = column.path_in_schema + + if col_path in col_path_2_iceberg_id: + col_index_2_id[c] = col_path_2_iceberg_id[col_path] + else: + raise AssertionError(f"Column path {col_path} couldn't be mapped to an iceberg ID") + + column_sizes: Dict[int, int] = {} + value_counts: Dict[int, int] = {} + split_offsets: List[int] = [] + + null_value_counts: Dict[int, int] = {} + nan_value_counts: Dict[int, int] = {} + + col_aggs = {} + + for r in range(metadata.num_row_groups): + # References: + # https://github.com/apache/iceberg/blob/fc381a81a1fdb8f51a0637ca27cd30673bd7aad3/parquet/src/main/java/org/apache/iceberg/parquet/ParquetUtil.java#L232 + # https://github.com/apache/parquet-mr/blob/ac29db4611f86a07cc6877b416aa4b183e09b353/parquet-hadoop/src/main/java/org/apache/parquet/hadoop/metadata/ColumnChunkMetaData.java#L184 + + row_group = metadata.row_group(r) + + data_offset = row_group.column(0).data_page_offset + dictionary_offset = row_group.column(0).dictionary_page_offset + + if row_group.column(0).has_dictionary_page and dictionary_offset < data_offset: + split_offsets.append(dictionary_offset) + else: + split_offsets.append(data_offset) + + for c in range(metadata.num_columns): + col_id = col_index_2_id[c] + + column = row_group.column(c) + + column_sizes[col_id] = column_sizes.get(col_id, 0) + column.total_compressed_size + value_counts[col_id] = value_counts.get(col_id, 0) + column.num_values + + if column.is_stats_set: + try: + statistics = column.statistics + + null_value_counts[col_id] = null_value_counts.get(col_id, 0) + statistics.null_count + + if column.path_in_schema in col_names: + # Iceberg seems to only have statistics for scalar columns + + if col_id not in col_aggs: + col_aggs[col_id] = StatsAggregator(statistics.physical_type) + + col_aggs[col_id].add_min(statistics.min) + col_aggs[col_id].add_max(statistics.max) + + except pyarrow.lib.ArrowNotImplementedError: + pass Review Comment: Should we log a warning here? ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) + + +def int32_to_avro(value: int) -> bytes: + return struct.pack("<i", value) + + +def int64_to_avro(value: int) -> bytes: + return struct.pack("<q", value) + + +def float_to_avro(value: float) -> bytes: + return struct.pack("<f", value) + + +def double_to_avro(value: float) -> bytes: + return struct.pack("<d", value) + + +def bytes_to_avro(value: Union[bytes, str]) -> bytes: + if type(value) == str: + return value.encode() + else: + assert isinstance(value, bytes) # appeases mypy + return value + + +class StatsAggregator: + def __init__(self, type_string: str): + self.current_min: Any = None + self.current_max: Any = None + self.serialize: Any = None + + if type_string == "BOOLEAN": + self.serialize = bool_to_avro + elif type_string == "INT32": + self.serialize = int32_to_avro + elif type_string == "INT64": + self.serialize = int64_to_avro + elif type_string == "INT96": + raise NotImplementedError("Statistics not implemented for INT96 physical type") + elif type_string == "FLOAT": + self.serialize = float_to_avro + elif type_string == "DOUBLE": + self.serialize = double_to_avro + elif type_string == "BYTE_ARRAY": + self.serialize = bytes_to_avro + elif type_string == "FIXED_LEN_BYTE_ARRAY": + self.serialize = bytes_to_avro + else: + raise AssertionError(f"Unknown physical type {type_string}") + + def add_min(self, val: bytes) -> None: + if not self.current_min: + self.current_min = val + elif val < self.current_min: + self.current_min = val + + def add_max(self, val: bytes) -> None: + if not self.current_max: + self.current_max = val + elif self.current_max < val: + self.current_max = val + + def get_min(self) -> bytes: + return self.serialize(self.current_min)[:BOUND_TRUNCATED_LENGHT] + + def get_max(self) -> bytes: + return self.serialize(self.current_max)[:BOUND_TRUNCATED_LENGHT] + + +def fill_parquet_file_metadata( + df: DataFile, metadata: pq.FileMetaData, col_path_2_iceberg_id: Dict[str, int], file_size: int +) -> None: + """ + Computes and fills the following fields of the DataFile object. + + - file_format + - record_count + - file_size_in_bytes + - column_sizes + - value_counts + - null_value_counts + - nan_value_counts + - lower_bounds + - upper_bounds + - split_offsets + + Args: + df (DataFile): A DataFile object representing the Parquet file for which metadata is to be filled. + metadata (pyarrow.parquet.FileMetaData): A pyarrow metadata object. + col_path_2_iceberg_id: A mapping of column paths as in the `path_in_schema` attribute of the colum Review Comment: A suggestion. Since we have the Iceberg write schema, we could also easily construct a `List[int, int]` that will tell the mapping of position to field-id. We have the `PreOrderSchemaVisitor` where we traverse the schema in order to construct this list. I don't like the `key_value` specific to PyArrow, and the list will be faster. WDYT? ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) + + +def int32_to_avro(value: int) -> bytes: + return struct.pack("<i", value) + + +def int64_to_avro(value: int) -> bytes: + return struct.pack("<q", value) + + +def float_to_avro(value: float) -> bytes: + return struct.pack("<f", value) + + +def double_to_avro(value: float) -> bytes: + return struct.pack("<d", value) + + +def bytes_to_avro(value: Union[bytes, str]) -> bytes: + if type(value) == str: + return value.encode() + else: + assert isinstance(value, bytes) # appeases mypy + return value + + +class StatsAggregator: + def __init__(self, type_string: str): Review Comment: Why are we using a `type_string` here? The PyIceberg `PrimitiveType` seems to do the trick for me. We have methods for converting a PyArrow type to an IcebergType. Nit: ```suggestion def __init__(self, type_string: str) -> None: ``` ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) + + +def int32_to_avro(value: int) -> bytes: + return struct.pack("<i", value) + + +def int64_to_avro(value: int) -> bytes: + return struct.pack("<q", value) + + +def float_to_avro(value: float) -> bytes: + return struct.pack("<f", value) + + +def double_to_avro(value: float) -> bytes: + return struct.pack("<d", value) + + +def bytes_to_avro(value: Union[bytes, str]) -> bytes: + if type(value) == str: + return value.encode() + else: + assert isinstance(value, bytes) # appeases mypy + return value + + +class StatsAggregator: + def __init__(self, type_string: str): + self.current_min: Any = None + self.current_max: Any = None + self.serialize: Any = None + + if type_string == "BOOLEAN": + self.serialize = bool_to_avro + elif type_string == "INT32": + self.serialize = int32_to_avro + elif type_string == "INT64": + self.serialize = int64_to_avro + elif type_string == "INT96": + raise NotImplementedError("Statistics not implemented for INT96 physical type") + elif type_string == "FLOAT": + self.serialize = float_to_avro + elif type_string == "DOUBLE": + self.serialize = double_to_avro + elif type_string == "BYTE_ARRAY": + self.serialize = bytes_to_avro + elif type_string == "FIXED_LEN_BYTE_ARRAY": + self.serialize = bytes_to_avro + else: + raise AssertionError(f"Unknown physical type {type_string}") + + def add_min(self, val: bytes) -> None: + if not self.current_min: + self.current_min = val + elif val < self.current_min: Review Comment: Any reason to not use Python's build in `min` function? That one might be passed down to C. ########## python/pyiceberg/utils/file_stats.py: ########## @@ -0,0 +1,333 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import struct +from typing import ( + Any, + Dict, + List, + Union, +) + +import pyarrow.lib +import pyarrow.parquet as pq + +from pyiceberg.manifest import DataFile, FileFormat +from pyiceberg.schema import Schema, SchemaVisitor, visit +from pyiceberg.types import ( + IcebergType, + ListType, + MapType, + NestedField, + PrimitiveType, + StructType, +) + +BOUND_TRUNCATED_LENGHT = 16 + +# Serialization rules: https://iceberg.apache.org/spec/#binary-single-value-serialization +# +# Type Binary serialization +# boolean 0x00 for false, non-zero byte for true +# int Stored as 4-byte little-endian +# long Stored as 8-byte little-endian +# float Stored as 4-byte little-endian +# double Stored as 8-byte little-endian +# date Stores days from the 1970-01-01 in an 4-byte little-endian int +# time Stores microseconds from midnight in an 8-byte little-endian long +# timestamp without zone Stores microseconds from 1970-01-01 00:00:00.000000 in an 8-byte little-endian long +# timestamp with zone Stores microseconds from 1970-01-01 00:00:00.000000 UTC in an 8-byte little-endian long +# string UTF-8 bytes (without length) +# uuid 16-byte big-endian value, see example in Appendix B +# fixed(L) Binary value +# binary Binary value (without length) +# + + +def bool_to_avro(value: bool) -> bytes: + return struct.pack("?", value) + + +def int32_to_avro(value: int) -> bytes: + return struct.pack("<i", value) + + +def int64_to_avro(value: int) -> bytes: + return struct.pack("<q", value) + + +def float_to_avro(value: float) -> bytes: + return struct.pack("<f", value) + + +def double_to_avro(value: float) -> bytes: + return struct.pack("<d", value) + + +def bytes_to_avro(value: Union[bytes, str]) -> bytes: + if type(value) == str: + return value.encode() + else: + assert isinstance(value, bytes) # appeases mypy + return value + + +class StatsAggregator: + def __init__(self, type_string: str): + self.current_min: Any = None + self.current_max: Any = None + self.serialize: Any = None + + if type_string == "BOOLEAN": + self.serialize = bool_to_avro + elif type_string == "INT32": + self.serialize = int32_to_avro + elif type_string == "INT64": + self.serialize = int64_to_avro + elif type_string == "INT96": + raise NotImplementedError("Statistics not implemented for INT96 physical type") + elif type_string == "FLOAT": + self.serialize = float_to_avro + elif type_string == "DOUBLE": + self.serialize = double_to_avro + elif type_string == "BYTE_ARRAY": + self.serialize = bytes_to_avro + elif type_string == "FIXED_LEN_BYTE_ARRAY": + self.serialize = bytes_to_avro + else: + raise AssertionError(f"Unknown physical type {type_string}") + + def add_min(self, val: bytes) -> None: + if not self.current_min: Review Comment: ```suggestion if self.current_min is not None: ``` -- This is an automated message from the Apache Git Service. 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