feat: Add read support for Parquet bloom filters

pyiceberg/table/bloom_filter.py

@@ -0,0 +1,79 @@
+# 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.
+"""Bloom filter support for reading from Parquet files."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Any
+
+if TYPE_CHECKING:
+    import pyarrow.parquet as pq
+
+
+def get_parquet_bloom_filter_for_column(parquet_file: pq.ParquetFile, column_name: str, row_group_index: int) -> Any | None:
+    """Extract bloom filter for a specific column from a Parquet row group.
+
+    Args:
+        parquet_file: PyArrow ParquetFile object.
+        column_name: Name of the column to get bloom filter for.
+        row_group_index: Index of the row group.
+
+    Returns:
+        Bloom filter object if available, None otherwise.
+    """
+    try:
+        # PyArrow provides access to bloom filters through the row group metadata
+        row_group = parquet_file.metadata.row_group(row_group_index)
+
+        # Find the column by name
+        for i in range(row_group.num_columns):
+            column = row_group.column(i)
+            if column.path_in_schema == column_name:
+                # Check if bloom filter is available
+                if hasattr(column, "bloom_filter"):
+                    return column.bloom_filter
+                break
+
+        return None
+    except Exception:
+        # If bloom filter reading fails, return None
+        return None
+
+
+def bloom_filter_might_contain(bloom_filter: Any, value: Any) -> bool:
+    """Check if a Parquet bloom filter might contain a value.
+
+    Args:
+        bloom_filter: PyArrow bloom filter object.
+        value: Value to check.
+
+    Returns:
+        True if value might be in the filter, False if definitely not.
+    """
+    if bloom_filter is None or value is None:
+        return True  # Conservative: assume it might contain
+
+    try:
+        # PyArrow bloom filters have a check method
+        if hasattr(bloom_filter, "check"):
+            return bloom_filter.check(value)
+        elif hasattr(bloom_filter, "__contains__"):
+            return value in bloom_filter
+        else:
+            return True  # Conservative: assume it might contain
+    except Exception:
+        return True  # On error, be conservative

tests/table/test_bloom_filter.py

@@ -0,0 +1,78 @@
+# 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.
+"""Tests for bloom filter utility functions."""
+
+from unittest.mock import MagicMock
+
+from pyiceberg.table.bloom_filter import bloom_filter_might_contain, get_parquet_bloom_filter_for_column
+
+
+class TestBloomFilterUtilities:
+    """Test cases for Parquet bloom filter reading utilities."""
+
+    def test_get_parquet_bloom_filter_returns_none_when_not_available(self) -> None:
+        """Test that getting a bloom filter returns None when not available."""
+        # Mock a ParquetFile without bloom filters
+        mock_parquet_file = MagicMock()
+        mock_row_group = MagicMock()
+        mock_column = MagicMock()
+        mock_column.path_in_schema = "test_column"
+        del mock_column.bloom_filter  # Ensure bloom_filter attribute doesn't exist
+
+        mock_row_group.num_columns = 1
+        mock_row_group.column.return_value = mock_column
+        mock_parquet_file.metadata.row_group.return_value = mock_row_group
+
+        result = get_parquet_bloom_filter_for_column(mock_parquet_file, "test_column", 0)
+        assert result is None
+
+    def test_bloom_filter_might_contain_returns_true_when_filter_is_none(self) -> None:
+        """Test that might_contain returns True conservatively when filter is None."""
+        result = bloom_filter_might_contain(None, "test_value")
+        assert result is True
+
+    def test_bloom_filter_might_contain_returns_true_when_value_is_none(self) -> None:
+        """Test that might_contain returns True conservatively when value is None."""
+        mock_filter = MagicMock()
+        result = bloom_filter_might_contain(mock_filter, None)
+        assert result is True
+
+    def test_bloom_filter_might_contain_uses_check_method(self) -> None:
+        """Test that might_contain uses the check method if available."""
+        mock_filter = MagicMock()
+        mock_filter.check.return_value = True
+
+        result = bloom_filter_might_contain(mock_filter, "test_value")
+        assert result is True
+        mock_filter.check.assert_called_once_with("test_value")
+
+    def test_bloom_filter_might_contain_uses_contains_method(self) -> None:
+        """Test that might_contain uses __contains__ if check is not available."""
+        mock_filter = MagicMock()
+        del mock_filter.check  # Remove check method
+        mock_filter.__contains__.return_value = True
+
+        result = bloom_filter_might_contain(mock_filter, "test_value")
+        assert result is True
+
+    def test_bloom_filter_might_contain_returns_true_on_exception(self) -> None:
+        """Test that might_contain returns True conservatively on exception."""
+        mock_filter = MagicMock()
+        mock_filter.check.side_effect = Exception("Test error")
+
+        result = bloom_filter_might_contain(mock_filter, "test_value")
+        assert result is True