arrow-util: canonicalize ranges decoded from Parquet#36499
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The reader for range columns called `push_range_with`, which writes the range to the row verbatim. For discrete range types (int4/int8/date), Parquet files authored by external engines may encode ranges with non-canonical bounds — e.g. `[1,10]` for `int4range`, which MZ stores internally as `[1,11)`. Without canonicalization those rows do not compare or hash equal to logically-identical values constructed inside MZ, so `COPY FROM PARQUET` rows mismatch their pure-SQL counterparts. Switch the decode path to `push_range`, which canonicalizes the range before packing. Add a unit test that decodes a hand-built non-canonical arrow StructArray and a testdrive regression test that round-trips a DuckDB-authored Parquet file through `COPY FROM ... (FORMAT PARQUET)`. Fixes DB-55. https://claude.ai/code/session_01KXioUsT2r5o2tRwrsHm4iR
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May 11, 2026
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Thanks for adding a test, lgtm!
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| key = _setup(c) | ||
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| c.run_testdrive_files( | ||
| f"--var=s3-access-key={key}", | ||
| "--var=aws-endpoint=minio:9000", | ||
| "range-noncanonical.td", | ||
| ) |
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Many workflows in test/iceberg do just this, we could put them all in a workflow_cdc instead that iterates over the files? But more of a test cleanup, not that important for this PR itself.
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The reader for range columns called
push_range_with, which writes the range to the row verbatim. For discrete range types (int4/int8/date), Parquet files authored by external engines may encode ranges with non-canonical bounds — e.g.[1,10]forint4range, which MZ stores internally as[1,11). Without canonicalization those rows do not compare or hash equal to logically-identical values constructed inside MZ, soCOPY FROM PARQUETrows mismatch their pure-SQL counterparts.Switch the decode path to
push_range, which canonicalizes the range before packing. Add a unit test that decodes a hand-built non-canonical arrow StructArray and a testdrive regression test that round-trips a DuckDB-authored Parquet file throughCOPY FROM ... (FORMAT PARQUET).Fixes DB-55.
https://claude.ai/code/session_01KXioUsT2r5o2tRwrsHm4iR