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Unify arrow exports across all query result types#495
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Periodic forward-merge of release-branch bugfixes into main. Notably brings in #495 "Unify arrow exports across all query result types" (the materialized slow-path lifetime / connection-GC fix and the test_arrow_refeed suite), replacing main's older SchemaCachingStreamWrapper/ArrowQueryResultStreamWrapper approach. Submodule: external/duckdb is kept at main's pin 0361de441a (v1.5's submodule bumps discarded; git fast-forwarded the gitlink to main's newer pin). Conflict resolution: - .github/workflows/packaging_wheels.yml: applied both intents — v1.5's windows-2025 -> windows-2022 (consistent with targeted_test.yml) and main's ARM64-comment removal. Adaptation for main's newer core: - pyresult.cpp: core's ColumnDataRef now takes vector<Identifier> (not vector<string>); promote the deduplicated scan names to Identifiers explicitly in MakeColumnDataScanStatement. Verified: clean build; tests/fast/arrow + tests/fast/udf = 2436 passed, 0 failed (incl. test_capsule_slow_path_survives_connection_gc and the new test_arrow_refeed suite).
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This PR unifies arrow exports across query result types, and makes sure we always provide the schema from within a transaction.
We are dealing with 3 arrow export types:
... across 3 result types:
The
StreamingQueryResultpaths are now unified. We re-feed the backing ColumnDataCollection to the engine for parallel conversion into aArrowQueryResult, and then we delegate to the correspondingArrowQueryResultpath.The
ArrowQueryResultpaths deal with materialized data already, and we have no way to plug into the transaction that generated it. The actual fix for this is to cache the schema when creating theArrowQueryResult, duringFinalize. This is a core change that we will probably apply in v2.0. The workaround is to fetch the schema in a separate transaction. For all paths, since we are already dealing with materialized data, we create an arrow table. Then for the streaming paths we return the corresponding stream types directly from the table.The
StreamingQueryResultpaths always have access to a valid transaction context, and can get the arrow schema on demand even when that requires catalog access.As a side effect of this PR, consuming an arrow c stream (reading from
con.sql(q).__arrow_c_stream__()) is now lazy, i.e. not materialized. This makes consumption of course slower, but allows streaming much larger datasets.The materialized paths are overall a little faster, and the non-c stream streaming paths as well.
Fixes #475