feat: support direct Variant projection in native Parquet scans - #5868
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peterxcli wants to merge 4 commits into
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feat: support direct Variant projection in native Parquet scans#5868peterxcli wants to merge 4 commits into
peterxcli wants to merge 4 commits into
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Which issue does this PR close?
Closes #5551.
Closes #5546.
Rationale for this change
Complete the ordinary-Parquet admission step in #5546 so Spark can project whole Variant values through a native scan.
What changes are included in this PR?
Enable direct top-level Variant projection with
allowReadingShredded=trueandpushVariantIntoScan=false. Carry missing-column defaults as constant[value, metadata]structs while preserving their schema indexes, and retain Spark fallbacks for unsupported consumers and reader settings.Reuse the Variant normalizer to handle Spark's empty object keys until Comet upgrades to an Arrow release containing apache/arrow-rs#10352. Document the supported surface and add removal TODOs for the compatibility paths, including #5477.
How are these changes tested?
Focused Spark 4.0/4.1 tests cover value parity, defaults, Unicode field matching, vector layout, and fallback behavior. Native Variant tests and clippy pass, and Spark 3.5 compiles. The new projection suite runs in Linux and macOS CI.