laskoviymishka commented on code in PR #2398: URL: https://github.com/apache/iceberg-rust/pull/2398#discussion_r3989303461
########## crates/iceberg/src/expr/visitors/bloom_filter_evaluator.rs: ########## @@ -0,0 +1,1559 @@ +// 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. + +//! Evaluates predicates against Parquet bloom filters to determine whether +//! a row group can be skipped. + +use std::collections::{HashMap, HashSet}; + +use fnv::FnvHashSet; +use parquet::basic::Type as PhysicalType; +use parquet::bloom_filter::Sbbf; +use parquet::data_type::ByteArray; + +use crate::Result; +use crate::expr::visitors::bound_predicate_visitor::{BoundPredicateVisitor, visit}; +use crate::expr::{BoundPredicate, BoundReference}; +use crate::spec::decimal_utils::decimal_to_fixed_length_bytes_exact; +use crate::spec::{Datum, PrimitiveLiteral, PrimitiveType, Type}; + +const ROW_GROUP_MIGHT_MATCH: Result<bool> = Ok(true); +const ROW_GROUP_CANT_MATCH: Result<bool> = Ok(false); + +/// A column's bloom filter for one row group, together with the file's physical +/// encoding of that column. A probe must be encoded the way the writer encoded +/// the values it inserted, so the encoding travels with the filter. +pub(crate) struct ColumnBloomFilter { + sbbf: Sbbf, + physical_type: PhysicalType, + /// `type_length` from the file's column descriptor. Only meaningful for + /// `FIXED_LEN_BYTE_ARRAY`. + type_length: i32, +} + +impl ColumnBloomFilter { + pub(crate) fn new(sbbf: Sbbf, physical_type: PhysicalType, type_length: i32) -> Self { + Self { + sbbf, + physical_type, + type_length, + } + } +} + +pub(crate) struct BloomFilterEvaluator<'a> { + /// Maps Iceberg field_id -> bloom filter for this row group + bloom_filters: &'a HashMap<i32, ColumnBloomFilter>, +} + +impl BloomFilterEvaluator<'_> { + /// Evaluate the predicate against the provided bloom filters. + /// Returns `false` if the row group definitely does not match, + /// `true` if it might match. + pub(crate) fn eval( + filter: &BoundPredicate, + bloom_filters: &HashMap<i32, ColumnBloomFilter>, + ) -> Result<bool> { + if bloom_filters.is_empty() { + return ROW_GROUP_MIGHT_MATCH; + } + + let mut evaluator = BloomFilterEvaluator { bloom_filters }; + visit(&mut evaluator, filter) + } + + fn check_datum(&self, reference: &BoundReference, datum: &Datum) -> bool { + let field_id = reference.field().id; + let Some(column) = self.bloom_filters.get(&field_id) else { + // No bloom filter for this column — conservatively might match + return true; + }; + + check_in_bloom_filter(column, datum) + } +} + +/// Collects field IDs that appear in `eq` or `in` predicates — the only +/// predicate types that benefit from bloom filter checks. +/// +/// Each node returns the field IDs its subtree contributes, mirroring +/// [`BloomFilterEvaluator`]'s structure so that a field is collected only where +/// the evaluator can act on it. In particular `not` discards its subtree: the +/// evaluator's `not` returns might-match regardless, so a filter fetched for a +/// field under a `NOT` could never prune and would be pure wasted I/O. +/// +/// Boolean fields are skipped for the same reason: with only two possible values, +/// a column chunk's min/max statistics already determine membership exactly, so a +/// bloom filter cannot prune anything statistics did not, and reading one costs a +/// round trip to learn nothing. +pub(crate) fn collect_bloom_filter_field_ids(predicate: &BoundPredicate) -> Result<HashSet<i32>> { + visit(&mut BloomFilterFieldIdCollector, predicate) +} + +struct BloomFilterFieldIdCollector; + +/// Field IDs worth fetching a bloom filter for: none if probing the column could +/// never prune. +fn probeable_field_id(reference: &BoundReference) -> HashSet<i32> { + if matches!( + reference.field().field_type.as_ref(), + Type::Primitive(PrimitiveType::Boolean) + ) { + return HashSet::new(); + } + HashSet::from([reference.field().id]) +} + +impl BoundPredicateVisitor for BloomFilterFieldIdCollector { + type T = HashSet<i32>; + + fn always_true(&mut self) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn always_false(&mut self) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn and(&mut self, mut lhs: Self::T, rhs: Self::T) -> Result<Self::T> { + lhs.extend(rhs); + Ok(lhs) + } + + fn or(&mut self, mut lhs: Self::T, rhs: Self::T) -> Result<Self::T> { + lhs.extend(rhs); + Ok(lhs) + } + + fn not(&mut self, _inner: Self::T) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn is_null(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_null(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn is_nan(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_nan(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn less_than( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn less_than_or_eq( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn greater_than( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn greater_than_or_eq( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn eq(&mut self, r: &BoundReference, _l: &Datum, _p: &BoundPredicate) -> Result<Self::T> { + Ok(probeable_field_id(r)) + } + + fn not_eq(&mut self, _r: &BoundReference, _l: &Datum, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn starts_with( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_starts_with( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn r#in( + &mut self, + r: &BoundReference, + _literals: &FnvHashSet<Datum>, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(probeable_field_id(r)) + } + + fn not_in( + &mut self, + _r: &BoundReference, + _literals: &FnvHashSet<Datum>, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } +} + +/// Check whether a datum value might be present in the bloom filter. +/// +/// The value must be checked using the same physical encoding the Parquet +/// writer used when inserting into the bloom filter. We use the actual +/// physical type from the column metadata to ensure correctness regardless +/// of which writer produced the file. +fn check_in_bloom_filter(column: &ColumnBloomFilter, datum: &Datum) -> bool { + let ColumnBloomFilter { + sbbf, + physical_type, + type_length, + } = column; + let physical_type = *physical_type; + + match datum.literal() { + // Parquet does not define bloom filter semantics for BOOLEAN — parquet-java + // only hashes int/long/float/double/binary. arrow-rs does write them, but min/max + // statistics already decide membership for a two-valued domain, so there is nothing to gain. + PrimitiveLiteral::Boolean(_) => true, + // A promoted column (int -> long, float -> double) keeps its original + // physical width in files written before the promotion, and the writer + // hashed that width, so probe at the file's width rather than the + // predicate's. + PrimitiveLiteral::Int(v) => match physical_type { + PhysicalType::INT32 => sbbf.check(v), + PhysicalType::INT64 => sbbf.check(&i64::from(*v)), + _ => true, + }, + PrimitiveLiteral::Long(v) => match physical_type { + PhysicalType::INT64 => sbbf.check(v), + PhysicalType::INT32 => match i32::try_from(*v) { + Ok(narrowed) => sbbf.check(&narrowed), + // Too wide for an INT32 column to hold, so there is nothing + // meaningful to probe — keep the row group. Review Comment: The comment has it backwards — a value too wide for INT32 provably can't be in an INT32 column, so the filter *can* give a definitive answer here; we're just choosing not to act on it. "Nothing meaningful to probe" reads like the filter is helpless, when we're really returning a conservative might-match rather than pruning. If we ever wanted the extra pruning, returning `false` here would actually beat the Java reference (which truncates and can't prune) — but the tests deliberately assert the conservative path, so that's a genuine follow-up, not something to change now. Just the comment wording, wdyt? ########## crates/iceberg/src/expr/visitors/bloom_filter_evaluator.rs: ########## @@ -0,0 +1,1559 @@ +// 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. + +//! Evaluates predicates against Parquet bloom filters to determine whether +//! a row group can be skipped. + +use std::collections::{HashMap, HashSet}; + +use fnv::FnvHashSet; +use parquet::basic::Type as PhysicalType; +use parquet::bloom_filter::Sbbf; +use parquet::data_type::ByteArray; + +use crate::Result; +use crate::expr::visitors::bound_predicate_visitor::{BoundPredicateVisitor, visit}; +use crate::expr::{BoundPredicate, BoundReference}; +use crate::spec::decimal_utils::decimal_to_fixed_length_bytes_exact; +use crate::spec::{Datum, PrimitiveLiteral, PrimitiveType, Type}; + +const ROW_GROUP_MIGHT_MATCH: Result<bool> = Ok(true); +const ROW_GROUP_CANT_MATCH: Result<bool> = Ok(false); + +/// A column's bloom filter for one row group, together with the file's physical +/// encoding of that column. A probe must be encoded the way the writer encoded +/// the values it inserted, so the encoding travels with the filter. +pub(crate) struct ColumnBloomFilter { + sbbf: Sbbf, + physical_type: PhysicalType, + /// `type_length` from the file's column descriptor. Only meaningful for + /// `FIXED_LEN_BYTE_ARRAY`. + type_length: i32, +} + +impl ColumnBloomFilter { + pub(crate) fn new(sbbf: Sbbf, physical_type: PhysicalType, type_length: i32) -> Self { + Self { + sbbf, + physical_type, + type_length, + } + } +} + +pub(crate) struct BloomFilterEvaluator<'a> { + /// Maps Iceberg field_id -> bloom filter for this row group + bloom_filters: &'a HashMap<i32, ColumnBloomFilter>, +} + +impl BloomFilterEvaluator<'_> { + /// Evaluate the predicate against the provided bloom filters. + /// Returns `false` if the row group definitely does not match, + /// `true` if it might match. + pub(crate) fn eval( + filter: &BoundPredicate, + bloom_filters: &HashMap<i32, ColumnBloomFilter>, + ) -> Result<bool> { + if bloom_filters.is_empty() { + return ROW_GROUP_MIGHT_MATCH; + } + + let mut evaluator = BloomFilterEvaluator { bloom_filters }; + visit(&mut evaluator, filter) + } + + fn check_datum(&self, reference: &BoundReference, datum: &Datum) -> bool { + let field_id = reference.field().id; + let Some(column) = self.bloom_filters.get(&field_id) else { + // No bloom filter for this column — conservatively might match + return true; + }; + + check_in_bloom_filter(column, datum) + } +} + +/// Collects field IDs that appear in `eq` or `in` predicates — the only +/// predicate types that benefit from bloom filter checks. +/// +/// Each node returns the field IDs its subtree contributes, mirroring +/// [`BloomFilterEvaluator`]'s structure so that a field is collected only where +/// the evaluator can act on it. In particular `not` discards its subtree: the +/// evaluator's `not` returns might-match regardless, so a filter fetched for a +/// field under a `NOT` could never prune and would be pure wasted I/O. +/// +/// Boolean fields are skipped for the same reason: with only two possible values, +/// a column chunk's min/max statistics already determine membership exactly, so a +/// bloom filter cannot prune anything statistics did not, and reading one costs a +/// round trip to learn nothing. +pub(crate) fn collect_bloom_filter_field_ids(predicate: &BoundPredicate) -> Result<HashSet<i32>> { + visit(&mut BloomFilterFieldIdCollector, predicate) +} + +struct BloomFilterFieldIdCollector; + +/// Field IDs worth fetching a bloom filter for: none if probing the column could +/// never prune. +fn probeable_field_id(reference: &BoundReference) -> HashSet<i32> { + if matches!( + reference.field().field_type.as_ref(), + Type::Primitive(PrimitiveType::Boolean) + ) { + return HashSet::new(); + } + HashSet::from([reference.field().id]) +} + +impl BoundPredicateVisitor for BloomFilterFieldIdCollector { + type T = HashSet<i32>; + + fn always_true(&mut self) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn always_false(&mut self) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn and(&mut self, mut lhs: Self::T, rhs: Self::T) -> Result<Self::T> { + lhs.extend(rhs); + Ok(lhs) + } + + fn or(&mut self, mut lhs: Self::T, rhs: Self::T) -> Result<Self::T> { + lhs.extend(rhs); + Ok(lhs) + } + + fn not(&mut self, _inner: Self::T) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn is_null(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_null(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn is_nan(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_nan(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn less_than( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn less_than_or_eq( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn greater_than( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn greater_than_or_eq( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn eq(&mut self, r: &BoundReference, _l: &Datum, _p: &BoundPredicate) -> Result<Self::T> { + Ok(probeable_field_id(r)) + } + + fn not_eq(&mut self, _r: &BoundReference, _l: &Datum, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn starts_with( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_starts_with( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn r#in( + &mut self, + r: &BoundReference, + _literals: &FnvHashSet<Datum>, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(probeable_field_id(r)) + } + + fn not_in( + &mut self, + _r: &BoundReference, + _literals: &FnvHashSet<Datum>, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } +} + +/// Check whether a datum value might be present in the bloom filter. +/// +/// The value must be checked using the same physical encoding the Parquet +/// writer used when inserting into the bloom filter. We use the actual +/// physical type from the column metadata to ensure correctness regardless +/// of which writer produced the file. +fn check_in_bloom_filter(column: &ColumnBloomFilter, datum: &Datum) -> bool { + let ColumnBloomFilter { + sbbf, + physical_type, + type_length, + } = column; + let physical_type = *physical_type; + + match datum.literal() { + // Parquet does not define bloom filter semantics for BOOLEAN — parquet-java + // only hashes int/long/float/double/binary. arrow-rs does write them, but min/max + // statistics already decide membership for a two-valued domain, so there is nothing to gain. + PrimitiveLiteral::Boolean(_) => true, + // A promoted column (int -> long, float -> double) keeps its original + // physical width in files written before the promotion, and the writer + // hashed that width, so probe at the file's width rather than the + // predicate's. + PrimitiveLiteral::Int(v) => match physical_type { + PhysicalType::INT32 => sbbf.check(v), + PhysicalType::INT64 => sbbf.check(&i64::from(*v)), + _ => true, + }, + PrimitiveLiteral::Long(v) => match physical_type { + PhysicalType::INT64 => sbbf.check(v), + PhysicalType::INT32 => match i32::try_from(*v) { + Ok(narrowed) => sbbf.check(&narrowed), + // Too wide for an INT32 column to hold, so there is nothing + // meaningful to probe — keep the row group. + Err(_) => true, + }, + _ => true, + }, + PrimitiveLiteral::Float(v) => match physical_type { + PhysicalType::FLOAT => sbbf.check(&v.0), Review Comment: I'd want to confirm this arm doesn't diverge from the row filter on signed zero. `sbbf.check(&v.0)` hashes raw IEEE bits, so a file holding only `-0.0` won't match a `= 0.0` probe here — but arrow's `cmp::eq` treats `-0.0 == 0.0` as true, which would mean we prune a row group the row filter would have returned rows from. `test_bloom_pushdown_float_signed_zero` passing hints that arrow normalizes the sign somewhere on the read path, but the test comment says arrow's float eq is bitwise "for the same reason," and I don't think that's right. Could we pin down which it actually is? If it does diverge, probing both zero bit patterns (or returning might-match for any ±0.0 probe) closes it cheaply. ########## crates/iceberg/src/expr/visitors/bloom_filter_evaluator.rs: ########## @@ -0,0 +1,1559 @@ +// 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. + +//! Evaluates predicates against Parquet bloom filters to determine whether +//! a row group can be skipped. + +use std::collections::{HashMap, HashSet}; + +use fnv::FnvHashSet; +use parquet::basic::Type as PhysicalType; +use parquet::bloom_filter::Sbbf; +use parquet::data_type::ByteArray; + +use crate::Result; +use crate::expr::visitors::bound_predicate_visitor::{BoundPredicateVisitor, visit}; +use crate::expr::{BoundPredicate, BoundReference}; +use crate::spec::decimal_utils::decimal_to_fixed_length_bytes_exact; +use crate::spec::{Datum, PrimitiveLiteral, PrimitiveType, Type}; + +const ROW_GROUP_MIGHT_MATCH: Result<bool> = Ok(true); +const ROW_GROUP_CANT_MATCH: Result<bool> = Ok(false); + +/// A column's bloom filter for one row group, together with the file's physical +/// encoding of that column. A probe must be encoded the way the writer encoded +/// the values it inserted, so the encoding travels with the filter. +pub(crate) struct ColumnBloomFilter { + sbbf: Sbbf, + physical_type: PhysicalType, + /// `type_length` from the file's column descriptor. Only meaningful for + /// `FIXED_LEN_BYTE_ARRAY`. + type_length: i32, +} + +impl ColumnBloomFilter { + pub(crate) fn new(sbbf: Sbbf, physical_type: PhysicalType, type_length: i32) -> Self { + Self { + sbbf, + physical_type, + type_length, + } + } +} + +pub(crate) struct BloomFilterEvaluator<'a> { + /// Maps Iceberg field_id -> bloom filter for this row group + bloom_filters: &'a HashMap<i32, ColumnBloomFilter>, +} + +impl BloomFilterEvaluator<'_> { + /// Evaluate the predicate against the provided bloom filters. + /// Returns `false` if the row group definitely does not match, + /// `true` if it might match. + pub(crate) fn eval( + filter: &BoundPredicate, + bloom_filters: &HashMap<i32, ColumnBloomFilter>, + ) -> Result<bool> { + if bloom_filters.is_empty() { + return ROW_GROUP_MIGHT_MATCH; + } + + let mut evaluator = BloomFilterEvaluator { bloom_filters }; + visit(&mut evaluator, filter) + } + + fn check_datum(&self, reference: &BoundReference, datum: &Datum) -> bool { + let field_id = reference.field().id; + let Some(column) = self.bloom_filters.get(&field_id) else { + // No bloom filter for this column — conservatively might match + return true; + }; + + check_in_bloom_filter(column, datum) + } +} + +/// Collects field IDs that appear in `eq` or `in` predicates — the only +/// predicate types that benefit from bloom filter checks. +/// +/// Each node returns the field IDs its subtree contributes, mirroring +/// [`BloomFilterEvaluator`]'s structure so that a field is collected only where +/// the evaluator can act on it. In particular `not` discards its subtree: the +/// evaluator's `not` returns might-match regardless, so a filter fetched for a +/// field under a `NOT` could never prune and would be pure wasted I/O. +/// +/// Boolean fields are skipped for the same reason: with only two possible values, +/// a column chunk's min/max statistics already determine membership exactly, so a +/// bloom filter cannot prune anything statistics did not, and reading one costs a +/// round trip to learn nothing. +pub(crate) fn collect_bloom_filter_field_ids(predicate: &BoundPredicate) -> Result<HashSet<i32>> { + visit(&mut BloomFilterFieldIdCollector, predicate) +} + +struct BloomFilterFieldIdCollector; + +/// Field IDs worth fetching a bloom filter for: none if probing the column could +/// never prune. +fn probeable_field_id(reference: &BoundReference) -> HashSet<i32> { + if matches!( + reference.field().field_type.as_ref(), + Type::Primitive(PrimitiveType::Boolean) + ) { + return HashSet::new(); + } + HashSet::from([reference.field().id]) +} + +impl BoundPredicateVisitor for BloomFilterFieldIdCollector { + type T = HashSet<i32>; + + fn always_true(&mut self) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn always_false(&mut self) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn and(&mut self, mut lhs: Self::T, rhs: Self::T) -> Result<Self::T> { + lhs.extend(rhs); + Ok(lhs) + } + + fn or(&mut self, mut lhs: Self::T, rhs: Self::T) -> Result<Self::T> { + lhs.extend(rhs); + Ok(lhs) + } + + fn not(&mut self, _inner: Self::T) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn is_null(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_null(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn is_nan(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_nan(&mut self, _r: &BoundReference, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn less_than( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn less_than_or_eq( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn greater_than( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn greater_than_or_eq( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn eq(&mut self, r: &BoundReference, _l: &Datum, _p: &BoundPredicate) -> Result<Self::T> { + Ok(probeable_field_id(r)) + } + + fn not_eq(&mut self, _r: &BoundReference, _l: &Datum, _p: &BoundPredicate) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn starts_with( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn not_starts_with( + &mut self, + _r: &BoundReference, + _l: &Datum, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } + + fn r#in( + &mut self, + r: &BoundReference, + _literals: &FnvHashSet<Datum>, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(probeable_field_id(r)) + } + + fn not_in( + &mut self, + _r: &BoundReference, + _literals: &FnvHashSet<Datum>, + _p: &BoundPredicate, + ) -> Result<Self::T> { + Ok(HashSet::new()) + } +} + +/// Check whether a datum value might be present in the bloom filter. +/// +/// The value must be checked using the same physical encoding the Parquet +/// writer used when inserting into the bloom filter. We use the actual +/// physical type from the column metadata to ensure correctness regardless +/// of which writer produced the file. +fn check_in_bloom_filter(column: &ColumnBloomFilter, datum: &Datum) -> bool { + let ColumnBloomFilter { + sbbf, + physical_type, + type_length, + } = column; + let physical_type = *physical_type; + + match datum.literal() { + // Parquet does not define bloom filter semantics for BOOLEAN — parquet-java + // only hashes int/long/float/double/binary. arrow-rs does write them, but min/max + // statistics already decide membership for a two-valued domain, so there is nothing to gain. + PrimitiveLiteral::Boolean(_) => true, + // A promoted column (int -> long, float -> double) keeps its original + // physical width in files written before the promotion, and the writer + // hashed that width, so probe at the file's width rather than the + // predicate's. + PrimitiveLiteral::Int(v) => match physical_type { + PhysicalType::INT32 => sbbf.check(v), + PhysicalType::INT64 => sbbf.check(&i64::from(*v)), + _ => true, + }, + PrimitiveLiteral::Long(v) => match physical_type { + PhysicalType::INT64 => sbbf.check(v), + PhysicalType::INT32 => match i32::try_from(*v) { + Ok(narrowed) => sbbf.check(&narrowed), + // Too wide for an INT32 column to hold, so there is nothing + // meaningful to probe — keep the row group. + Err(_) => true, + }, + _ => true, + }, + PrimitiveLiteral::Float(v) => match physical_type { + PhysicalType::FLOAT => sbbf.check(&v.0), + PhysicalType::DOUBLE => sbbf.check(&f64::from(v.0)), + _ => true, + }, + PrimitiveLiteral::Double(v) => match physical_type { + PhysicalType::DOUBLE => sbbf.check(&v.0), + PhysicalType::FLOAT => { + let narrowed = v.0 as f32; + // Only an exactly representable value can equal a widened f32. + if f64::from(narrowed) == v.0 { + sbbf.check(&narrowed) + } else { + true + } + } + _ => true, + }, + PrimitiveLiteral::String(v) => sbbf.check(v.as_str()), + PrimitiveLiteral::Binary(v) => sbbf.check(v.as_slice()), + PrimitiveLiteral::Int128(v) => { + // Decimal: dispatch based on the actual Parquet physical type + // from the file, not inferred from precision. + match physical_type { + // Narrow only when the mantissa round-trips; a truncated copy would + // hash to an unrelated slot. + PhysicalType::INT32 => match i32::try_from(*v) { + Ok(narrowed) => sbbf.check(&narrowed), + Err(_) => true, + }, + PhysicalType::INT64 => match i64::try_from(*v) { + Ok(narrowed) => sbbf.check(&narrowed), + Err(_) => true, + }, + PhysicalType::FIXED_LEN_BYTE_ARRAY => { + // Encode to the file's declared length, not one derived from + // the Iceberg precision: a widened precision would change the + // length and miss every entry the writer inserted. + match usize::try_from(*type_length) + .ok() + .and_then(|len| decimal_to_fixed_length_bytes_exact(*v, len)) + { + Some(bytes) => sbbf.check(&ByteArray::from(bytes)), + // Unusable length, or a value too large for the column to + // hold — conservatively might match. + None => true, + } + } + // Known gap: BYTE_ARRAY decimals are valid in Parquet (though not in + // Iceberg's Appendix A) and some older Spark writers emit them. Not + // probed because BYTE_ARRAY carries no `type_length` and sign-extension + // padding is writer-dependent, so a single-length probe would miss + // padded entries and prune row groups that do hold the value. A sound + // version ORs a check over every length from minimal..=16. + _ => true, // Conservatively might match + } + } + PrimitiveLiteral::UInt128(v) => { + // UUID: stored as FIXED_LEN_BYTE_ARRAY(16), big-endian + let bytes = v.to_be_bytes(); + sbbf.check(&ByteArray::from(bytes.to_vec())) Review Comment: `bytes` is already a `[u8; 16]` on the stack, so we can hand the slice straight to `check` and skip the `Vec` + `ByteArray` allocation — the `Binary` arm just above already does this with `v.as_slice()`. ```suggestion sbbf.check(bytes.as_ref()) ``` Same bytes hashed, just no per-probe alloc, which adds up for `IN` over many row groups. -- This is an automated message from the Apache Git Service. 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