choice, aligning with real -world RAG use cases where response time matters as much as relevance. Reference: Oracle Database 23ai AI Vector Search Guide, Section on Approximate Search Queries. 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 database administrator wants to change the VECTOR_MEMORY_SIZE parameter for a pluggable database (PDB) in Oracle Database 23ai. Which SQL command is correct?
Reference: Oracle Database 23ai AI Vector Search Guide, Section on HNSW Indexing. What is the purpose of the Vector Pool in Oracle Database 23ai?
In Oracle Database 23ai, which SQL function calculates the distance between two vectors using the Euclidean metric?
Oracle GoldenGate 23ai is a real -time data replication and integration tool, extended in 23ai to handle the VECTOR data type for AI applications. Its key advantage (A) is enabling real -time updates of vector data across distributed locations —e.g., replicating VECTOR columns from a primary database in New York to a secondary in London with sub -second latency. This ensures AI models (e.g., for similarity search or RAG) access the latest embeddings as source data (e.g., documents) changes, critical for dynamic environments like customer support systems where new queries demand current context. Imagine a VECTOR column storing embeddings of support tickets; GoldenGate keeps these synchronized across regions, minimizing staleness that could degrade AI responses. Option B (automatic translation) is fictional; GoldenGate doesn’t convert vector formats (e.g., FLOAT32 to INT8) —that’s a model or application task. Option C (compression) isn’t a GoldenGate feature; compression might occur at the storage layer, but GoldenGate focuses on replication fidelity, not size reduction. Option D (version control) misaligns with GoldenGate’s purpose; it ensures data consistency, not historical versioning like Git. Real -time replication (A) stands out, as Oracle’s documentation emphasizes GoldenGate’s role in keeping vector -driven AI applications globally consistent, a game - changer for distributed AI deployments where latency or inconsistency could disrupt user trust. Without this, static exports (e.g., Data Pump) would lag, undermining real -time AI use cases. Reference: Oracle GoldenGate 23ai Release Notes, Section on Vector Data Support; Oracle Database 23ai AI Vector Search Guide, Data Management. What happens when you attempt to insert a vector with an incorrect number of dimensions into a VECTOR column with a defined number of dimensions?
➢ TOTAL QUESTIONS: 360 Which Oracle feature enhances performance when generating vector embeddings at scale?
