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Oracle 1Z0-184-25 - Questions & Answers

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Question 1
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

Question 2
Single choice

What is the primary purpose of a similarity search in Oracle Database 23ai?

A.

Optimize relational database operations to compute distances between all data points in a database

B.

To find exact matches in BLOB data

C.

To retrieve the most semantically similar entries using distance metrics between different vectors

D.

To group vectors by their exact scores

Question 3
Single choice

Which PL/SQL package is primarily used for interacting with Generative AI services in Oracle Database 23ai?

A.

DBMS_AI

B.

DBMS_ML

C.

DBMS_VECTOR_CHAIN

D.

DBMS_GENAI

Question 4
Single choice

Which statement best describes the core functionality and benefit of Retrieval Augmented Generation (RAG) in Oracle Database 23ai?

A.

It empowers LLMs to interact with private enterprise data stored within the database, leading to more context-aware and precise responses to user queries

B.

It primarily aims to optimize the performance and efficiency of LLMs by using advanced data retrieval techniques, thus minimizing response times and reducing computational overhead

C.

It allows users to train their own specialized LLMs directly within the Oracle Database environment using their internal data, thereby reducing reliance on external AI providers

D.

It enables Large Language Models (LLMs) to access and process real-time data streams from diverse sources to generate the most up-to-date insights

Question 5
Single choice

You are tasked with creating a table to store vector embeddings with the following characteristics: Each vector must have exactly 512 dimensions, and the dimensions should be stored as 32-bitfloating point numbers.

Which SQL statement should you use?

A.

CREATE TABLE vectors (id NUMBER, embedding VECTOR(512))

B.

CREATE TABLE vectors (id NUMBER, embedding VECTOR)

C.

CREATE TABLE vectors (id NUMBER, embedding VECTOR(*, INT8))

D.

CREATE TABLE vectors (id NUMBER, embedding VECTOR(512, FLOAT32))

Question 6
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

Question 7
Single choice

What happens when querying with an IVF index if you increase the value of the NEIGHBOR_PARTITIONS probes parameter?

A.

The number of centroids decreases

B.

Accuracy decreases

C.

Index creation time is reduced

D.

More partitions are probed, improving accuracy, but also increasing query latency

Question 8
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

Question 9
Single choice

Which Python library is used to vectorize text chunks and the user's question in the following example?

import oracledb

connection = oracledb.connect(user=un, password=pw, dsn=ds) table_name = "Page"

with connection.cursor() as cursor:

create_table_sql = f"""

CREATE TABLE IF NOT EXISTS {table_name} (

id NUMBER PRIMARY KEY,

payload CLOB CHECK (payload IS JSON),

vector VECTOR

)"""

try:

cursor.execute(create_table_sql)

except oracledb.DatabaseError as e:

raise

connection.autocommit = True

from sentence_transformers import SentenceTransformer

encoder = SentenceTransformer('all-MiniLM-L12-v2')

A.

sentence_transformers

B.

oci

C.

oracledb

D.

json

Question 10
Single choice

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

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