Question 1

What is the purpose of the Vector Pool in Oracle Database 23ai?

Options :

A : To manage database partitioning

B : To store HNSW vector indexes and IVF index metadata

C : To enable longer SQL execution

D : To store non-vector data types

Answer: B

Question 2

How does an application use vector similarity search to retrieve relevant information from a database, and how is this information then integrated into the generation process?

Options :

A : Encodes the question and database chunks into vectors, finds the most similar using cosine similarity, and includes them in the LLM prompt

B : Trains a separate LLM on the database and uses it to answer, ignoring the general LLM

C : Converts the question to keywords, searches for matches, and inserts the text into the response

D : Clusters similar text chunks and randomly selects one from the most relevant cluster

Answer: A

Question 3

Which operation is NOT permitted on tables containing VECTOR columns?

Options :

A : SELECT

B : UPDATE

C : DELETE

D : JOIN ON VECTOR columns

Answer: D

Question 4

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 5

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