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1Z0-184-25 Oracle AI Vector Search Professional

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Oracle · 1Z0-184-25

Free 1Z0-184-25 Exam Dumps Preview

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Question 1

Single choice

You are tasked with finding the closest matching sentences across books, where each book has multiple paragraphs and sentences.

Which SQL structure should you use?

A
A nested query with ORDER BY
B
Exact similarity search with a single query vector
C
GROUP BY with vector operations
D
FETCH PARTITIONS BY clause

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Correct answerA

Question 2

Single choice

Which vector index available in Oracle Database 23ai is known for its speed and accuracy, making it a preferred choice for vector search?

A
Binary Tree (BT) index
B
Inverted File System (IFS) index
C
Inverted File (IVF) index
D
Hierarchical Navigable Small World (HNSW) index

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Correct answerD

Question 3

Single choice

Which SQL statement correctly adds a VECTOR column named "v" with 4 dimensions and FLOAT32 format to an existing table named "my_table"?

A
ALTER TABLE my_table MODIFY (v VECTOR(4, FLOAT32))
B
ALTER TABLE my_table ADD (v VECTOR(4, FLOAT32))
C
UPDATE my_table SET v = VECTOR(4, FLOAT32)
D
ALTER TABLE my_table ADD v VECTOR(4, FLOAT32)

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Correct answerB

Question 4

Single choice

What are the key advantages and considerations of using Retrieval Augmented Generation (RAG) in the context of Oracle AI Vector Search?

A
It excels at optimizing the performance and efficiency of LLM inference through advanced caching and precomputation techniques, leading to faster response times but potentially increasing storage requirements
B
It prioritizes real-time data extraction and summarization from various sources to ensure the LLM always has the most up-to-date information
C
It focuses on training specialized LLMs within the database environment for specific tasks, offering greater control over model behavior and data privacy but potentially requiring more development effort
D
It leverages existing database security and access controls, thereby enabling secure and controlled access to both the database content and the LLM

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Correct answerD

Question 5

Single choice

What is the primary difference between the HNSW and IVF vector indexes in Oracle Database 23ai?

A
Both operate identically but differ in memory usage
B
HNSW guarantees accuracy, whereas IVF sacrifices performance for accuracy
C
HNSW uses an in-memory neighbor graph for faster approximate searches, whereas IVF uses the buffer cache with partitions
D
HNSW is partition-based, whereas IVF uses neighbor graphs for indexing

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Correct answerC

Question 6

Single choice

When using SQL*Loader to load vector data for search applications, what is a critical consideration regarding the formatting of the vector data within the input CSV file?

A
Enclose vector components in curly braces ({})
B
As FVEC is a binary format and the vector dimensions have a known width, fixed offsets can be used to make parsing the vectors fast and efficient
C
Use sparse format for vector data
D
Rely on SQL*Loader's automatic normalization of vector data

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Correct answerA

Question 7

Single choice

A database administrator wants to change the VECTOR_MEMORY_SIZE parameter for a pluggable database (PDB) in Oracle Database 23ai.

Which SQL command is correct?

A
ALTER SYSTEM SET VECTOR_MEMORY_SIZE=1G SCOPE=BOTH
B
ALTER DATABASE SET VECTOR_MEMORY_SIZE=1G SCOPE=VECTOR
C
ALTER SYSTEM SET VECTOR_MEMORY_SIZE=1G SCOPE=SGA
D
ALTER SYSTEM RESET VECTOR_MEMORY_SIZE

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Correct answerA

Question 8

Single choice

What is the advantage of using Euclidean Squared Distance rather than Euclidean Distance in similarity search queries?

A
It is the default distance metric for Oracle AI Vector Search
B
It supports hierarchical partitioning of vectors
C
It is simpler and faster because it avoids square-root calculations
D
It guarantees higher accuracy than Euclidean Distance

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Correct answerC

Question 9

Single choice

Which statement best describes the capability of Oracle Data Pump for handling vector data in thecontext of vector search applications?

A
Data Pump only exports and imports vector data if the vector embeddings are stored as BLOB (Binary Large Object) data types in the database
B
Data Pump treats vector embeddings as regular text strings, which can lead to data corruption or loss of precision when transferring vector data for vector search
C
Data Pump provides native support for exporting and importing tables containing vector data types, facilitating the transfer of vector data for vector search applications
D
Because of the complexity of vector data, Data Pump requires a specialized plug-in to handle the export and import operations involving vector data types

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Correct answerC

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Oracle AI Vector Search Professional

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