最新的Oracle AI Vector Search Professional - 1Z0-184-25免費考試真題

A. Perform the similarity search without a WHERE clause

B. Use VECTOR_INDEX_HINT and NO WHERE clause

C. Apply relational filters and a similarity search in the query

D. Use UNION ALL with vector operations

A. The physical storage location of the vector data

B. Using the same embedding model for both vector creation and similarity search

C. Regularly updating vector embeddings to reflect changes in the source data

D. The specific distance algorithm employed for vector comparisons

A. Native Support for Vector Search Only within the Database Server

B. AI Smart Scan

C. Loading Vector Data using SQL*Loader

D. Vector Replication with GoldenGate

A. Enhanced security because data remains within the database

B. Support for legacy SQL*Plus clients

C. Reduced embedding dimensions for faster processing

D. Improved accuracy compared to external models

A. The database ignores the defined dimensions and inserts the vector as is

B. The database truncates the vector to fit the defined dimensions

C. The insert operation fails, and an error message is thrown

D. The database pads the vector with zeros to match the defined dimensions

A. UPDATE my_table SET v = VECTOR(4, FLOAT32)

B. ALTER TABLE my_table ADD v VECTOR(4, FLOAT32)

C. ALTER TABLE my_table MODIFY (v VECTOR(4, FLOAT32))

D. ALTER TABLE my_table ADD (v VECTOR(4, FLOAT32))

A. To serialize vectors into a string

B. To calculate vector dimensions

C. To calculate vector distances

D. To generate a single vector embedding for data