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test(table-catalog): expand live conformance guide (#4277)
Co-authored-by: Henry Guo <marshawcoco@users.noreply.github.com>
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@@ -48,6 +48,14 @@ catalog extension.
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| Databend | Manual/live harness | RustFS can generate an S3 stage read probe for table data files. RustFS does not claim Databend Iceberg REST Catalog integration yet. |
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| Snowflake Open Catalog / Iceberg integrations | Generated harness | RustFS can generate an operator-adapted external volume/catalog SQL template. Live RustFS interoperability is not claimed. |
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## Live Evidence And Operations Matrix
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| Area | Status | Current RustFS claim |
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|---|---|---|
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| Live conformance evidence template | Generated harness | `engine_compatibility.py --print-live-conformance` records required run metadata, per-client result rows, and claim promotion rules before a manual/live result can expand compatibility wording. |
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| Production operations guide | Generated harness | `engine_compatibility.py --print-operations-guide` records command, evidence, pass criteria, and fail-closed signals for live conformance, durable backing cutover, maintenance, recovery, permissions, credential vending, and unsupported-claim governance. |
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| Client claim promotion | Documented, not automated | PyIceberg remains the automated claim. Spark can be promoted only with recorded manual/live evidence; Trino and DuckDB read probes do not promote write compatibility; Snowflake and vendor profiles remain reference-only without repeatable live evidence. |
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## Catalog API Matrix
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| Area | Status | Covered behavior |
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@@ -199,6 +207,11 @@ python3 scripts/table-catalog/engine_compatibility.py \
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--metadata-location s3://rustfs-s3table-smoke/tables/table-id/metadata/v1.metadata.json \
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--print-live-conformance \
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--cleanup
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python3 scripts/table-catalog/engine_compatibility.py \
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--warehouse rustfs-s3table-smoke \
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--namespace smoke \
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--table events \
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--print-operations-guide
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python3 scripts/table-catalog/failure_coverage.py \
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--warehouse rustfs-s3table-smoke \
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--namespace smoke \
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@@ -222,7 +235,8 @@ Acceptable wording:
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> with PyIceberg smoke coverage, table-aware S3 data-plane policy checks,
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> controlled maintenance, catalog recovery diagnostics, manual conformance
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> input for Spark, Trino, DuckDB, Databend, and Snowflake, production-failure
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> probe harnesses, and disaster-recovery rehearsal probes.
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> probe harnesses, disaster-recovery rehearsal probes, and a machine-readable
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> production operations evidence guide.
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Do not claim:
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