Question 1

What is the primary purpose of the VECTOR NORM() function in Oracle Database 23ai?

Options :

A : To return the magnitude or length of a vector.

B : To convert a vector to a string representation.

C : To determine the number of dimensions in a vector.

D : To calculate the Euclidean distance between two vectors.

Answer: A

Question 2

Assuming we have a table called VT2 that contains vectors for mapping various shapes, colors, and sizes, what is the primary purpose of the following UPDATE statements? SQL> UPDATE vt2

SET shape = 'Triangle

WHERE id IN (2, 4, 7, 22, 31, 41, 44, 55);

SQL> UPDATE vt2

SET size = 'Medium'

WHERE id IN (5, 22, 25, 32, 34, 42, 43, 53, 54, 55);

Options :

A : To add new rows of data to the VT2 table with different sizes and shapes.

B : To assign attributes like size and shape to existing vectors based on their IDs.

C : To delete rows from the VT2 table that do not meet specific criteria.

D : To modify the vector values stored in the VT2 table.

Answer: B

Question 3

A machine learning team is using IVF indexes in Oracle Database 23ai to find similar images in a large dataset. During testing, they observe that the search results are often incomplete, missing relevant images. They suspect the issue lies in the number of partitions probed. How should they improve the search accuracy?

Options :

A : Add the TARGET_ACCURACY clause to the query with a higher value for the accuracy

B : Change the index type to HNSW for better accuracy

C :

Increase the VECTOR_MEMORY_SIZE initialization parameter

D : Re-create the index with a higher EFCONSTRUCTION value

Answer: A

Question 4

What is the correct order of steps for building a RAG application using PL/SQL in Oracle Database 23ai?

Options :

A :

Load ONNX Model, Vectorize Question, Load Document, Split Text into Chunks, Create Embeddings, Perform Vector Search, Generate Output

B :

Load Document, Split Text into Chunks, Load ONNX Model, Create Embeddings, Vectorize Question, Perform Vector Search, Generate Output

C :

Vectorize Question, Load ONNX Model, Load Document, Split Text into Chunks, Create Embeddings, Perform Vector Search, Generate Output

D :

Load Document, Load ONNX Model, Split Text into Chunks, Create Embeddings, VectorizeQuestion, Perform Vector Search, Generate Output

Answer: B

Question 5

Multi-Vector Similarity Search is typically used for:

Options :

A : Exact vector matching

B : Single-vector comparisons

C : Multi-document search

D : Image recognition

Answer: C

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