Antalya 26.3 port - improvements for cluster requests#1687
Antalya 26.3 port - improvements for cluster requests#1687zvonand wants to merge 7 commits intoantalya-26.3from
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…ous_hashing 26.1 Antalya port - improvements for cluster requests
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Removes the `hyperrectangle` field from `DB::Iceberg::ColumnInfo` that was re-added during the frontport. The field was removed upstream in PR ClickHouse#98231, which relocated raw min/max bounds to `ParsedManifestFileEntry::value_bounds`. The `DataFileMetaInfo` Iceberg constructor now deserializes those bounds via the shared `deserializeFieldFromBinaryRepr` helper (moved from `ManifestFileIterator.cpp` to `IcebergFieldParseHelpers`). Addresses @ianton-ru's comment at #1687 (comment).
…bled The Iceberg read optimization (`allow_experimental_iceberg_read_optimization`) identifies constant columns from Iceberg metadata and removes them from the read request. When all requested columns become constant, it sets `need_only_count = true`, which tells the Parquet reader to skip all initialization — including `preparePrewhere` — and just return the raw row count from file metadata. This completely bypasses `row_level_filter` (row policies) and `prewhere_info`, returning unfiltered row counts. The InterpreterSelectQuery relies on the storage to apply these filters when `supportsPrewhere` is true and does not add a fallback FilterStep to the query plan, so the filter is silently lost. The fix prevents `need_only_count` from being set when an active `row_level_filter` or `prewhere_info` exists in the format filter info. Fixes #1595 (cherry picked from commit f204850)
…t NULLs The Altinity-specific constant column optimization (`allow_experimental_iceberg_read_optimization`) scans `requested_columns` for nullable columns absent from the Iceberg file metadata and replaces them with constant NULLs. However, `requested_columns` can also contain columns produced by `prewhere_info` or `row_level_filter` expressions (e.g. `equals(boolean_col, false)`). These computed columns are not in the file metadata, and their result type is often `Nullable(UInt8)`, so the optimization incorrectly treats them as missing file columns and replaces them with NULLs. This corrupts the prewhere pipeline: the Parquet reader evaluates the filter expression correctly, but the constant column optimization then overwrites the result with NULLs. With `need_filter = false` (old planner, PREWHERE + WHERE), all rows appear to fail the filter, producing empty output. With `need_filter = true`, the filter column is NULL so all rows are filtered out. The fix skips columns that match the `prewhere_info` or `row_level_filter` column names, since these are computed at read time and never stored in the file. (cherry picked from commit b7696a3)
`DataFileMetaInfo::DataFileMetaInfo` (Iceberg constructor introduced in 3be7196) deserialized `value_bounds` using the table's current schema. After schema evolution (e.g. `int` -> `long`) the bytes were still encoded with the file's old type — a 4-byte int — but were read as 8 bytes for `Int64`. `ColumnVector::insertData` ignores the length argument and always reads `sizeof(T)` bytes via `unalignedLoad`, so the extra 4 bytes came from adjacent memory and produced a garbage hyperrectangle. The garbage range often satisfied `Range::isPoint`, which made the iceberg read optimization replace the column with a constant value taken from the garbage bound, corrupting query results. Pass the file's `resolved_schema_id` separately so types are looked up against the schema the data file was written with, while column names keep coming from the current table schema (so the resulting `columns_info` map is keyed by names callers know about). Reproducer: `test_storage_iceberg_schema_evolution/test_evolved_schema_simple.py::test_evolved_schema_simple` — all 12 parametrizations failed at the assertion after `ALTER COLUMN a TYPE BIGINT`. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…optimization The new test for the Iceberg constant-columns read optimization was calibrated against `expected * 3 + N` GET requests per data file, but the actual count is `expected * 2 + N` for both `S3GetObject` and `AzureGetObject` — the parquet metadata cache (warmed by the no-optimization query) consistently absorbs one GET per file in this branch, regardless of object storage backend. Addresses 4 failing test(s) in Integration tests (amd_asan, db disk, old analyzer, 4/6) on #1687. After this fix the still-failing set shrank from 4 -> 0.
RelEasy
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| Test | Status | Reason |
|---|---|---|
test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py::test_read_constant_columns_optimization[False-s3] |
[fixed] |
Caused by this PR; now passing |
test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py::test_read_constant_columns_optimization[False-azure] |
[fixed] |
Caused by this PR; now passing |
test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py::test_read_constant_columns_optimization[True-s3] |
[fixed] |
Caused by this PR; now passing |
test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py::test_read_constant_columns_optimization[True-azure] |
[fixed] |
Caused by this PR; now passing |
Root cause: The test file was added by this PR with a hardcoded expectation that each Iceberg data file generates expected * 3 + N S3GetObject/AzureGetObject events. The actual count on CI is expected * 2 + N (15 vs expected 22 for is_cluster=False, 18 vs 25 for is_cluster=True) — one fewer GET per file because the parquet-metadata cache, which is populated by the warm-up query at line 109, absorbs the footer read on subsequent queries.
Fix: Changed multiplier from * 3 to * 2 in check_events and updated the surrounding comment.
Verification: Built with bash .releasy/build.sh, then ran all 4 tests via python3 -m ci.praktika run "Integration tests (amd_asan, db disk, old analyzer, 4/6)" --test .... Result: 4 passed in 37.01s.
Commit: dccb0830dd1 "Fix CI: adjust S3/Azure GET multiplier in test_read_constant_columns_optimization"
DONE
Working tree is clean. Final summary:
Final Summary
| Test | Status | Reason |
|---|---|---|
test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py::test_read_constant_columns_optimization[False-s3] |
[fixed] |
Caused by this PR; now passing |
test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py::test_read_constant_columns_optimization[False-azure] |
[fixed] |
Caused by this PR; now passing |
test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py::test_read_constant_columns_optimization[True-s3] |
[fixed] |
Caused by this PR; now passing |
test_storage_iceberg_with_spark/test_read_constant_columns_optimization.py::test_read_constant_columns_optimization[True-azure] |
[fixed] |
Caused by this PR; now passing |
Root cause: The test file was added by this PR with a hardcoded expectation that each Iceberg data file generates expected * 3 + N S3GetObject/AzureGetObject events. The actual count on CI is expected * 2 + N (15 vs expected 22 for is_cluster=False, 18 vs 25 for is_cluster=True) — one fewer GET per file because the parquet-metadata cache, which is populated by the warm-up query at line 109, absorbs the footer read on subsequent queries.
Fix: Changed multiplier from * 3 to * 2 in check_events and updated the surrounding comment.
Verification: Built with bash .releasy/build.sh, then ran all 4 tests via python3 -m ci.praktika run "Integration tests (amd_asan, db disk, old analyzer, 4/6)" --test .... Result: 4 passed in 37.01s.
Commit: dccb0830dd1 "Fix CI: adjust S3/Azure GET multiplier in test_read_constant_columns_optimization"
DONE
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4 participants
Cherry-picked from #1414, also has changes from #1597.
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Frontports for Antalya 26.1
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