{"record":{"id":"d68bf2b158b1ba42","repo":"dbt-labs/dbt-core","slug":"oracle-d68bf2","errorCode":null,"errorMessage":"Oracle","messagePattern":"Oracle","errorType":"panic","errorClass":null,"httpStatus":null,"severity":"error","filePath":"crates/dbt-adapter/src/column/column_builder.rs","lineNumber":40,"sourceCode":"\n    pub fn build(&self, field: &FieldRef, type_ops: &dyn TypeOps) -> AdapterResult<Column> {\n        use AdapterType::*;\n        match self.adapter_type {\n            Snowflake => Ok(Self::build_snowflake(field, type_ops)),\n            Bigquery => Ok(Self::build_bigquery(field, type_ops)),\n            Databricks | Spark => Ok(Self::build_databricks(field, type_ops)),\n            Redshift => Ok(Self::build_redshift(field, type_ops)),\n            Postgres | Salesforce | DuckDB | LakeCompute => {\n                Ok(Self::build_postgres_like(field, type_ops))\n            }\n            Fabric => Ok(Self::build_fabric(field, type_ops)),\n            ClickHouse => Self::build_clickhouse(field, type_ops),\n            Exasol => Ok(Self::build_exasol(field, type_ops)),\n            Starburst => todo!(\"Starburst\"),\n            Athena => todo!(\"Athena\"),\n            Trino => todo!(\"Trino\"),\n            Dremio => todo!(\"Dremio\"),\n            Oracle => todo!(\"Oracle\"),\n            Datafusion => todo!(\"Datafusion\"),\n        }\n    }\n\n    pub fn build_from_parts(\n        &self,\n        name: String,\n        dtype: String,\n        char_size: Option<u32>,\n        numeric_precision: Option<u64>,\n        numeric_scale: Option<u64>,\n        mode: Option<BigqueryColumnMode>,\n    ) -> Column {\n        use AdapterType::*;\n        match self.adapter_type {\n            Postgres => Column::new(\n                Postgres,\n                name,","sourceCodeStart":22,"sourceCodeEnd":58,"githubUrl":"https://github.com/dbt-labs/dbt-core/blob/0267ce9170576975b76b64ce856b2e5848e96617/crates/dbt-adapter/src/column/column_builder.rs#L22-L58","documentation":"A `todo!()` panic in `ColumnBuilder::build` (column_builder.rs:40) for the Oracle adapter. No column-building strategy exists for Oracle, so building Column metadata from a schema with an Oracle adapter panics with the message 'Oracle'.","triggerScenarios":"schema_to_columns, get_column_schema_from_query, or update_node_columns invoked with adapter type Oracle — typically during query-result schema extraction or docs/catalog generation.","commonSituations":"Running schema introspection against an Oracle adapter profile before the Oracle arm was implemented; also reached when tests sweep all AdapterType variants through `build`.","solutions":["Use a supported adapter for column metadata workflows until Oracle support is added.","Implement the Oracle arm in column_builder.rs:40, mapping NUMBER/VARCHAR2 etc. into the Column model (possibly a dedicated build_oracle).","Replace `todo!()` with a typed error such as DbtError::UnsupportedAdapter for catchable failures."],"exampleFix":"// before\nOracle => todo!(\"Oracle\"),\n// after\nOracle => Ok(Self::build_postgres_like(field, type_ops)),","handlingStrategy":"type-guard","validationCode":"if adapter == AdapterType::Oracle {\n    return Err(anyhow!(\"Oracle column building is not implemented yet\"));\n}","typeGuard":"fn build_supported(t: AdapterType) -> bool {\n    matches!(t, Postgres | Salesforce | DuckDB | LakeCompute | Fabric | ClickHouse | Exasol)\n}","tryCatchPattern":"match std::panic::catch_unwind(AssertUnwindSafe(|| builder.build(field, type_ops))) {\n    Ok(r) => r?,\n    Err(_) => return Err(anyhow!(\"column building not implemented for Oracle\")),\n}","preventionTips":["Do not use Oracle profiles for docs/catalog generation until the arm exists","Implement a dedicated build_oracle mapping NUMBER/VARCHAR2 types","Enumerate AdapterType variants in tests over ColumnBuilder::build","Prefer returning DbtError::UnsupportedAdapter over panicking"],"tags":["rust","adapter","todo-panic","oracle","column-builder"],"backgroundTag":"method-not-implemented","analyzedSha":"0267ce9170576975b76b64ce856b2e5848e96617","analyzedAt":"2026-09-07T21:53:39.732Z","contentChangedAt":"2026-09-07T21:53:39.732Z","schemaVersion":2},"datasetVersion":"2026-09-14T16:17:12.679Z"}