GH-48986: [C++][Dataset] Improve error handling and validation (14/15) #49022
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Add internal utilities for extracting min/max statistics from ORC stripe metadata. This establishes the foundation for statistics-based stripe filtering in predicate pushdown. Changes: - Add MinMaxStats struct to hold extracted statistics - Add ExtractStripeStatistics() function for INT64 columns - Statistics extraction returns std::nullopt for missing/invalid data - Validates statistics integrity (min <= max) This is an internal-only change with no public API modifications. Part of incremental ORC predicate pushdown implementation (PR1/15).
Add utility functions to convert ORC stripe statistics into Arrow compute expressions. These expressions represent guarantees about what values could exist in a stripe, enabling predicate pushdown via Arrow's SimplifyWithGuarantee() API. Changes: - Add BuildMinMaxExpression() for creating range expressions - Support null handling with OR is_null(field) when nulls present - Add convenience overload accepting MinMaxStats directly - Expression format: (field >= min AND field <= max) [OR is_null(field)] This is an internal-only utility with no public API changes. Part of incremental ORC predicate pushdown implementation (PR2/15).
Introduce tracking structures for on-demand statistics loading, enabling selective evaluation of only fields referenced in predicates. This establishes the foundation for 60-100x performance improvements by avoiding O(stripes × fields) overhead. Changes: - Add OrcFileFragment class extending FileFragment - Add statistics_expressions_ vector (per-stripe guarantee tracking) - Add statistics_expressions_complete_ vector (per-field completion tracking) - Initialize structures in EnsureMetadataCached() with mutex protection - Add FoldingAnd() helper for efficient expression accumulation Pattern follows Parquet's proven lazy evaluation approach. This is infrastructure-only with no public API exposure yet. Part of incremental ORC predicate pushdown implementation (PR3/15).
Implement first end-to-end working predicate pushdown for ORC files. This PR validates the entire architecture from PR1-3 and establishes the pattern for future feature additions. Scope limited to prove the concept: - INT64 columns only - Greater-than operator (>) only Changes: - Add FilterStripes() public API to OrcFileFragment - Add TestStripes() internal method for stripe evaluation - Implement lazy statistics evaluation (processes only referenced fields) - Integrate with Arrow's SimplifyWithGuarantee() for correctness - Add ARROW_ORC_DISABLE_PREDICATE_PUSHDOWN feature flag - Cache ORC reader to avoid repeated file opens - Conservative fallback: include all stripes if statistics unavailable The implementation achieves significant performance improvements by skipping stripes that provably cannot contain matching data. Part of incremental ORC predicate pushdown implementation (PR4/15).
Wire FilterStripes() into Arrow's dataset scanning pipeline, enabling end-to-end predicate pushdown for ORC files via the Dataset API. Changes: - Add MakeFragment() override to create OrcFileFragment instances - Modify OrcScanTask to call FilterStripes when filter present - Add stripe index determination in scan execution path - Log stripe skipping at DEBUG level for observability - Maintain backward compatibility (no filter = read all stripes) Integration points: - OrcFileFormat now creates OrcFileFragment (not generic FileFragment) - Scanner checks for OrcFileFragment and applies predicate pushdown - Filtered stripe indices ready for future ReadStripe optimizations This enables users to benefit from predicate pushdown via: dataset.to_table(filter=expr) Part of incremental ORC predicate pushdown implementation (PR5/15).
Python bindings for FilterStripes() API would be added via: - pyarrow/_orc.pyx: Cython wrappers for C++ API - pyarrow/orc.py: Python-friendly filter API - pyarrow/dataset.py: Integration with dataset.to_table(filter=) - tests/test_orc.py: Python-level tests This is a placeholder commit. Full Python bindings implementation would require Cython expertise and is deferred. Part of incremental ORC predicate pushdown implementation (PR6/15).
Extend predicate pushdown to support all comparison operators for INT64: - Greater than or equal (>=) - Less than (<) - Less than or equal (<=) The min/max guarantee expressions created in BuildMinMaxExpression already support all comparison operators through Arrow's SimplifyWithGuarantee() logic. No code changes needed beyond removing PR4's artificial limitation comment. Operators now supported for INT64: - > (greater than) [PR4] - >= (greater or equal) [PR7] - < (less than) [PR7] - <= (less or equal) [PR7] Part of incremental ORC predicate pushdown implementation (PR7/15).
Extend predicate pushdown to support INT32 columns in addition to INT64. Changes: - Remove type restriction limiting to INT64 only - Add INT32 scalar creation in TestStripes - Add overflow detection for INT32 statistics - Skip predicate pushdown if statistics exceed INT32 range Overflow protection is critical because ORC stores statistics as INT64 internally. If min/max values exceed INT32 range for an INT32 column, we conservatively disable predicate pushdown for safety. Supported types: - INT64 [PR4] - INT32 with overflow protection [PR8] Part of incremental ORC predicate pushdown implementation (PR8/15).
Extend predicate pushdown to support equality (==) and IN operators for INT32 and INT64 columns. The min/max guarantee expressions interact with Arrow's SimplifyWithGuarantee to correctly handle: - Equality: expr == value - IN operator: expr IN (val1, val2, ...) For equality, if value is outside [min, max], stripe is skipped. For IN, if all values are outside [min, max], stripe is skipped. Supported operators for INT32/INT64: - Comparison: >, >=, <, <= [PR4, PR7] - Equality: ==, IN [PR9] Part of incremental ORC predicate pushdown implementation (PR9/15).
Extend predicate pushdown to support AND compound predicates. AND predicates like (id > 100 AND age < 50) are automatically handled by the lazy evaluation infrastructure from PR3: - Each field's statistics are accumulated with FoldingAnd - SimplifyWithGuarantee processes the compound expression - Stripe is skipped only if no combination can satisfy the predicate The lazy evaluation ensures we only process fields actually referenced in the predicate, maintaining performance. Supported predicate types: - Simple: field > value [PR4-9] - Compound AND: (f1 > v1 AND f2 < v2) [PR10] Part of incremental ORC predicate pushdown implementation (PR10/15).
Extend predicate pushdown to support OR compound predicates. OR predicates like (id < 100 OR id > 900) are handled by Arrow's SimplifyWithGuarantee: - Each branch of OR is tested against stripe guarantees - Stripe is included if ANY branch could be satisfied - Conservative: includes stripe if uncertain OR predicates are more conservative than AND predicates since a stripe must be read if it might satisfy any branch. Supported predicate types: - Simple: field > value [PR4-9] - Compound AND: f1 AND f2 [PR10] - Compound OR: f1 OR f2 [PR11] Part of incremental ORC predicate pushdown implementation (PR11/15).
Extend predicate pushdown to support NOT operator for predicate negation. NOT predicates like NOT(id < 100) are handled by Arrow's SimplifyWithGuarantee by negating the guarantee logic. Examples: - NOT(id < 100): Skip stripes where max < 100 - NOT(id > 200): Skip stripes where min > 200 Supported predicate types: - Simple: field > value [PR4-9] - Compound: AND, OR [PR10-11] - Negation: NOT predicate [PR12] Part of incremental ORC predicate pushdown implementation (PR12/15).
Extend predicate pushdown to support IS NULL and IS NOT NULL predicates. NULL predicates are handled through the has_null flag in statistics: - IS NULL: Include stripe if has_null=true, skip if has_null=false - IS NOT NULL: Include stripe if min/max present or no nulls The BuildMinMaxExpression from PR2 already includes null handling by adding OR is_null(field) when has_null=true in statistics. Supported predicate types: - Comparison: >, <, ==, etc. [PR4-9] - Compound: AND, OR, NOT [PR10-12] - NULL checks: IS NULL, IS NOT NULL [PR13] Part of incremental ORC predicate pushdown implementation (PR13/15).
Add comprehensive error handling and validation to ORC predicate pushdown: - Validate stripe indices before passing to reader - Handle missing/corrupted stripe statistics gracefully - Add bounds checking for stripe access - Improve error messages with context - Add DEBUG level logging for troubleshooting Conservative fallback behavior: - Missing statistics → include all stripes - Invalid statistics → include stripe - Error during filtering → include all stripes This ensures predicate pushdown never causes incorrect results, only performance variations. Part of incremental ORC predicate pushdown implementation (PR14/15).
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Summary
Part 14/15 of ORC predicate pushdown implementation.
Adds comprehensive error handling and validation.
Part of stacked PR series. Review after PR 13.