1Z0-184-25 Question 180
Single answerYour organization stores machine learning embeddings in a new vector data column type introduced in the latest Oracle Database release. You need to migrate these tables containing vector columns from an on-premises database to Oracle Cloud Infrastructure using Oracle Data Pump. During test exports and imports, the vector columns were not recognized correctly when you used only the default export/import parameters. Which approach should you use to ensure a successful Data Pump job that preserves both the structure and the data of the vector columns?
- A
Use the DATA_ONLY parameter to limit the export to the actual values in the vector columns.
- B
Use the METADATA_ONLY parameter first to create the objects, and then run a separate import for vector data.
- C
Include the vector columns in the export by setting CONTENT=ALL and verifying that the newer vector data type definitions are included in both export and import jobs.
- D
Manually rename vector columns as standard numeric or VARCHAR2 columns before exporting, then rename them back after import.
Show answer and explanation
Correct answer: C
Explanation
When using Oracle Data Pump to migrate newly introduced data types (like vector columns) from an on-premises environment to OCI, you must ensure both metadata and data are transferred. CONTENT=ALL or the default content inclusion ensures that Data Pump copies the structural definitions (metadata) along with the data rows. Splitting exports into separate metadata-only and data-only jobs risks missing newer data type definitions if they aren�t properly synchronized. Refer to the official Oracle 23c (or later) Database Data Pump documentation for guidelines on exporting and importing specialized column types, including any prerequisite patches or compatibility settings required to fully support vector data.
- A. Incorrect.
Option 1 is incorrect. DATA_ONLY exports just the data rows without the necessary metadata definitions for specialized column types. This will not preserve the vector column structure required on the target.
- B. Incorrect.
Option 2 is incorrect. While splitting metadata and data can work in some scenarios, it can cause syncing issues for newer data types like vectors if you do not properly coordinate the creation of vector type definitions in the target environment before importing the data.
- C. Correct.
Option 3 is correct. By using CONTENT=ALL (or the full default which includes both metadata and data) and verifying that the newer vector data type definitions are recognized, you ensure that both the structure of the vector columns and their data are properly migrated. This approach aligns with Data Pump best practices for complex data types.
- D. Incorrect.
Option 4 is incorrect. Renaming columns to a different data type is risky and can cause data corruption or loss of precision, especially for high-dimensional embeddings stored in vector columns. It's not recommended when Oracle Data Pump can already handle vector types if configured correctly.