[coverage] Conformance findings: DATATYPE-043
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Valutazione
- Difficoltà
- 3/5
- Tempo stimato
- 1-2 giorni
- Idoneità per principianti
- 68/100
Direzione di ricerca
Start with the testUntypedNullColumnReportedAsString xfail in the coverage PR under tests/, then trace how this JDBC driver builds ResultSetMetaData.getColumnTypeName() for an untyped NULL. Compare the reported type with the typed NULL sibling and the existing normalizations mentioned in the issue. Done when the untyped NULL reports STRING on both thrift and SEA and the conformance assertions pass.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Descrizione
Summary
Surfaced by the multi-language coverage fan-out while conformance-testing these SPEC-IDs against databricks/databricks-jdbc. Each finding is committed as an expected-failure (xfail) test in the coverage PR — the test asserts the CORRECT (post-fix) behavior and stays red until THIS driver (databricks/databricks-jdbc) is fixed, then flips green as a tripwire.
Findings
- DATATYPE-043 [thrift, sea]: getColumnTypeName() reports "VOID" for an untyped NULL column instead of the driver's STRING type name, while getColumnType() for the same column is correctly Types.VARCHAR and the CAST(NULL AS STRING) sibling reports "STRING"
- failing test:
testUntypedNullColumnReportedAsString(see the coverage PR diff undertests/)
- failing test:
- DATATYPE-043: ResultSetMetaData.getColumnTypeName() returns the raw server type name "VOID" for an untyped NULL column (SELECT NULL) on both thrift and SEA, while getColumnType() for that same column is correctly Types.VARCHAR and a CAST(NULL AS STRING) sibling reports "STRING" — so the column is type-distinguishable from an equivalent STRING column and schema-mirroring consumers see an unbindable VOID type; columnTypeText should be normalised to "STRING" as it already is for geospatial-disabled and TIMESTAMP_NTZ columns
Reproduce & Expected
DATATYPE-043 — Verify that an UNTYPED SQL NULL column -- SELECT NULL AS c, whose Databricks logical type is VOID -- is reported through the driver's result type-metadata surface as the driver's STRING type: the S…
Expected (per the shared spec):
- result has exactly 1 row(s)
- result has 3 column(s)
- col
untyped_null, row 0 is null - col
typed_null_string, row 0 is null - col
typed_int, row 0 == 1 - full assertion contract:
result:
- row_count: 1
- column_count: 3
- reported_column_type:
column: untyped_null
same_as_column: typed_null_string
- reported_column_type:
column: untyped_null
sql_type: STRING
- reported_column_type:
column: typed_int
sql_type: INT
- column:
name: untyped_null
is_null: true
- column:
name: typed_null_string
is_null: true
- column:
name: typed_int
equals: 1
Context
- The behavior was first fixed in a DIFFERENT driver — reference PR: https://github.com/databricks/databricks-sql-nodejs/pull/569 — which seeded the shared language-neutral spec. This issue tracks the same conformance gap in databricks/databricks-jdbc; the reference PR is for cross-referencing the intended behavior, NOT a change to this repo.
- Coverage PR carrying the reproducing xfail test(s): https://github.com/databricks/databricks-driver-test/pull/1953
- Lingua principale
- Java
- Stelle
- 41
- Fork
- 49
- Merge medio
- 1g 7h
- PR unite (30g)
- 27
Preparare l'ambiente
- Nessun Dockerfile né file Docker Compose
- Ha un modello di pull request
- Leggi la guida per i contributori
Come iniziare
- Leggi tutta la issue e poi la guida ai contributi del progetto.
- Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
- Fai un fork del repository e lavora su un branch.
- Apri una pull request che faccia riferimento al numero della issue.
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