1Z0-184-25 Question 43
Select 2You are an OCI solutions architect for a retail analytics company. You have stored 256-dimensional product embeddings in an Oracle Autonomous Database table using the new VECTOR data type. To run approximate nearest neighbor (ANN) searches that recommend similar products, you need to create a vector index on this column. Which two actions must you perform to ensure a successful vector index creation that accelerates ANN queries?
- A
Include the matching dimension parameter for the VECTOR column in the CREATE INDEX statement
- B
Use the specialized approximate nearest neighbor (ANN) index type on the VECTOR column
- C
Convert the VECTOR column into a CLOB and apply text-based indexing
- D
Use standard numeric columns and rely on Automatic Indexing to handle ANN queries
Show answer and explanation
Correct answers: A, B
Explanation
To accelerate AI vector searches in Oracle Autonomous Database, you must store your data in the VECTOR data type and use the dedicated approximate nearest neighbor (ANN) indexing approach. Ensuring the index creation parameters match the dimension specified in your VECTOR column and applying a vector-specific index type are key steps. Refer to Oracle� documentation on vector data type and ANN indexing for best practices on dimension matching, index creation, and query optimization.
- A. Correct.
Correct. When creating a vector index, the dimension for the VECTOR data type must match in both the table definition and the index parameters to ensure proper indexing and query accuracy.
- B. Correct.
Correct. Oracle provides a specialized index type for vector columns aimed at approximate nearest neighbor queries. Using the correct index type is essential for efficient similarity searches on high-dimensional data.
- C. Incorrect.
Incorrect. Storing vector data in a CLOB and applying text-based indexing is a common misconception. Text-based indexes do not optimize numerical distances; you must use a vector-specific index for ANN searches.
- D. Incorrect.
Incorrect. Standard numeric columns and Automatic Indexing are not designed for high-dimensional vector operations. ANN queries require a dedicated vector index to deliver the necessary performance.