{"record":{"id":"19165ea670e70382","repo":"dbt-labs/dbt-core","slug":"only-available-with-bigquery-or-salesforce-adapter","errorCode":null,"errorMessage":"only available with BigQuery or Salesforce adapter","messagePattern":"only available with BigQuery or Salesforce adapter","errorType":"panic","errorClass":null,"httpStatus":null,"severity":"error","filePath":"crates/dbt-adapter/src/adapter/adapter_impl.rs","lineNumber":3510,"sourceCode":"                            INGEST_PATH.to_string(),\n                            OptionValue::String(file_path.to_string()),\n                        ),\n                        (\n                            INGEST_SCHEMA.to_string(),\n                            OptionValue::Bytes(serialized_ingest_schema),\n                        ),\n                    ],\n                    false,\n                    token,\n                )?;\n\n                Ok(none_value())\n            }\n            Salesforce => todo!(\"load_dataframe() for the Salesforce adapter\"),\n            Postgres | Snowflake | Databricks | Redshift | Spark | DuckDB | LakeCompute\n            | Fabric | ClickHouse | Exasol | Starburst | Athena | Trino | Datafusion | Dremio\n            | Oracle => {\n                unimplemented!(\"only available with BigQuery or Salesforce adapter\")\n            }\n        }\n    }\n\n    /// This only supports non-nested columns additions\n    ///\n    /// Since internally this is only used by snapshot materialization macro where newly added\n    /// columns all have non-nested data types, Read from\n    /// [here](https://github.com/sdf-labs/fs/blob/9b87be839f6aa54cab1ab91cde2c77855758c396/crates/dbt-loader/src/dbt_macro_assets/dbt-adapters/macros/materializations/snapshots/snapshot.sql#L32-L33).\n    /// This builds sql that creates the snapshot relation, and this relation only adds non-nested\n    /// columns to the source relation it is supposed to work well for this use case due to\n    /// limitation:\n    /// https://cloud.google.com/bigquery/docs/managing-table-schemas#add_a_nested_column_to_a_record_column\n    ///\n    /// BigQueryAdapter https://github.com/dbt-labs/dbt-adapters/blob/0efd8d3d1081e1ab43e38797d5104f7b424a6284/dbt-bigquery/src/dbt/adapters/bigquery/impl.py#L742\n    pub fn alter_table_add_columns(\n        &self,\n        state: &State,","sourceCodeStart":3492,"sourceCodeEnd":3528,"githubUrl":"https://github.com/dbt-labs/dbt-core/blob/0267ce9170576975b76b64ce856b2e5848e96617/crates/dbt-adapter/src/adapter/adapter_impl.rs#L3492-L3528","documentation":"todo!() in load_dataframe: the ingest/load_dataframe path is only implemented for BigQuery; when invoked with the Salesforce adapter the call aborts with this stub, so dataframe ingest on Salesforce cannot run in this build.","triggerScenarios":"Thrown at crates/dbt-adapter/src/adapter/adapter_impl.rs:3510 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":["Implement Salesforce data loading (e.g. Bulk API 2.0) in load_dataframe","Gate load_dataframe earlier and return a not-supported AdapterError for Salesforce","Route Salesforce ingest through an adapter-native method if one exists"],"exampleFix":null,"handlingStrategy":"fallback","validationCode":null,"typeGuard":null,"tryCatchPattern":null,"preventionTips":[],"tags":[],"backgroundTag":null,"analyzedSha":"0267ce9170576975b76b64ce856b2e5848e96617","analyzedAt":"2026-09-07T21:53:39.732Z","contentChangedAt":"2026-09-07T21:53:39.732Z","schemaVersion":2},"datasetVersion":"2026-09-17T15:17:12.973Z"}