Oracle AI Vector Search Mock Test
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Name: Your Name
1. When generating vector embeddings outside the database, what is the most suitable option for
storing the embeddings for later use?
in a CSV file
in a binary FVEC file with the relational data in a CSV file
in the database as BLOB (Binary Large Object) data
in a dedicated vector database
2. When generating vector embeddings for a new dataset outside of Oracle Database 23ai, which factor
is crucial to ensure meaningful similarity search results?
The choice of programming language used to process the dataset (for example, Python, Java)
The physical location where the vector embeddings are stored
The storage format of the new dataset (for example, CSV, JSON)
The same vector embedding model must be used for vectorizing the data and creating a query vector
3. You are working with vector search in Oracle Database 23ai and need to ensure the integrity of your
vector data during storage and retrieval. Which factor is crucial for maintaining the accuracy and
reliability of your vector search results?
Using the same embedding model for both vector creation and similarity search
Regularly updating vector embeddings to reflect changes in the source data
The specific distance algorithm employed for vector comparisons
The physical storage location of the vector data
4. Which DDL operation is NOT permitted on a table containing a VECTOR column in Oracle Database
23ai?
Creating a new table using CTAS CREATE TABLE AS SELECT that includes the VECTOR column from the original
table
Dropping an existing VECTOR column from the table
Modifying the data type of an existing VECTOR column to a non-VECTOR type
Adding a new VECTOR column to the table
5. Which SQL statement correctly adds a VECTOR column named v with 4 dimensions and FLOAT32
format to an existing table named my_table?
ALTER TABLE my_table MODIFY (V VECTOR(4, FLOAT32))
ALTER TABLE my_table ADD (V VECTOR(4, FLOAT32))
UPDATE my_table SET v = VECTOR(4, FLOAT32)
ALTER TABLE my_table ADD v VECTOR(4, FLOAT32)
6. 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 is in the number of partitions probed. How should they
improve the search accuracy?
Add the TARGET_ACCURACY clause to the query with a higher value to raise the accuracy
Change the index type to HNSW for better accuracy
Increase the VECTOR MEMORY SIZE initialization parameter
Re-create the index with a higher EFCONSTRUCTION value
7. What does the VECTOR_NORM function return?
The Euclidean norm or distance between the vector and the origin
The angle between two vectors
The number of dimensions of a vector
The negated dot product of two vectors
8. A retail company uses an Oracle Database 23ai HNSW vector index to recommend products to
customers based on their browsing history. The database administrator notices that after restarting the
database, product recommendations are slower. What steps should the administrator take to resolve
the issue?
Rebuild the HNSW index or enable automatic reload
Decrease the VECTOR_MEMORY_SIZE parameter
Modify the distance metric to DOT
Adjust the NEIGHBOR PARTITION PROBES parameter for improved accuracy
9. Which SQL statement will successfully insert a vector into a table named my_table with a single
VECTOR column named v?
INSERT INTO my_table VALUES ((1.1, 2.2, 3.3))
INSERT INTO my_table VALUES ('[1.1, 2.2, 3.3]')
INSERT INTO my_table (v) VALUES (1.1, 2.2, 3.3)
INSERT INTO my_table (v) VALUES ('[1.1, 2.2, 3.3]')
10. What specifically does the VECTOR_NORM function calculate in Oracle Database 23ai?
The Euclidean norm or distance between the vector and the origin
The Manhattan distance between the vector and the origin
The cosine similarity of the vector with a unit vector
The maximum value of any component in the vector
11. A retail company uses an Oracle Database 23ai HNSW vector index to recommend products to
customers based on their browsing history. The database administrator notices that after restarting the
database, product recommendations are slower. What is the most effective solution?
Rebuild the HNSW index or enable automatic reload
Increase the memory allocation for the database instance
Create a new HNSW index with a higher M parameter value
Schedule index maintenance during off-peak hours
12. Where are ONNX models stored after being loaded into an Oracle Database instance?
A table that includes BLOB data type
The database system tablespace
An external file system referenced by the database
The database's in-memory area
13. What is a key advantage of generating vector embeddings outside the database?
Flexibility in choosing specialized embedding models
Reduced computational load on the database
Simplified security management
Better integration with database analytics
14. What is the primary function of Select AI in Oracle Autonomous Database?
To eliminate the need for SQL expertise by enabling users to query data using natural language
To eliminate the need for manual coding by automatically generating SQL queries for complex data analysis tasks
To provide real-time data visualization and reporting tools integrated with Autonomous Database
To improve the efficiency of AI applications by training machine learning models directly within the database
15. What does a target accuracy of 80% in an approximate similarity search imply?
The search will process 80% of the dataset
80% accuracy seen in the index calculated distances
Only 80% of the indexed vectors are used
