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Oracle 1Z0-184-25 Exam Questions and Answers, Oracle AI Vector Search Professional | SPOTO

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Question #1
What is the purpose of the VECTOR_DISTANCE function in Oracle Database 23ai similarity search?
A. To fetch rows that match exact vector embeddings
B. To create vector indexes for efficient searches
C. To group vectors by their exact scores
D. To calculate the distance between vectors using a specified metric
View answer
Correct Answer: D
Question #2
What is the primary difference between the HNSW and IVF vector indexes in Oracle Database 23ai?
A. HNSW is partition-based, whereas IVF uses neighbor graphs for indexing
B. Both operate identically but differ in memory usage
C. HNSW guarantees accuracy, whereas IVF sacrifices performance for accuracy
D. HNSW uses an in-memory neighbor graph for faster approximate searches, whereas IVF uses the buffer cache with partitions
View answer
Correct Answer: D
Question #3
You are storing 1,000 embeddings in a VECTOR column, each with 256 dimensions using FLOAT32. What is the approximate size of the data on disk?
A. 1 MB
B. 4 MB
C. 256 KB
D. 1 GB
View answer
Correct Answer: B
Question #4
Which DDL operation is NOT permitted on a table containing a VECTOR column in Oracle Database 23ai?
A. Creating a new table using CTAS (CREATE TABLE AS SELECT) that includes the VECTOR column from the original table
B. Dropping an existing VECTOR column from the table
C. Modifying the data type of an existing VECTOR column to a non-VECTOR type
D. Adding a new VECTOR column to the table
View answer
Correct Answer: C
Question #5
What is the significance of splitting text into chunks in the process of loading data into Oracle AI Vector Search?
A. To reduce the computational burden on the embedding model
B. To facilitate parallel processing of the data during vectorization
C. To minimize token truncation as each vector embedding model has its own maximum token limit
View answer
Correct Answer: C

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