Develop AI Solutions by Using Azure Database for PostgreSQL AI-200 Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   Which pgvector operator is used to find the most similar vectors to a given query vector?

   • AIN (set membership)
   • BLIKE (pattern matching)
   • C= (equality)
   • D<-> (Euclidean distance)
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2. 2foundation · easy

   What is the primary purpose of using a composite index in PostgreSQL?

   • ATo optimize queries that filter on multiple columns
   • BTo store data in a compressed format
   • CTo automatically update statistics
   • DTo enforce foreign key constraints
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4. 3application · medium

   A social media analytics company stores user posts and their associated metadata in Azure Database for PostgreSQL. Each post has a variable-length text body, a fixed-size status code, and a timestamp. The application frequently queries posts by status and time range. Which table design and data types are most appropriate?

   • AUse a CHAR(1000) column for the post body, an INTEGER column for the status code, and a TIMESTAMP column for the timestamp.
   • BUse a JSONB column to store the entire post and metadata, and create a GIN index on the JSONB column.
   • CUse a TEXT column for the post body, a SMALLINT column for the status code, and a TIMESTAMPTZ column for the timestamp, with an index on (status, timestamp).
   • DUse a VARCHAR(255) column for the post body, a VARCHAR(10) column for the status code, and a DATE column for the timestamp.
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5. 4application · medium

   An application uses Azure Database for PostgreSQL to store product embeddings and performs similarity searches. The table has millions of rows. Queries are slow because the database performs a full scan for vector distance calculations. Which indexing strategy should the team implement to reduce query latency?

   • ACreate an HNSW index on the embedding column using the vector_cosine_ops operator class.
   • BCreate a B-tree index on the embedding column using the default operator class.
   • CCreate a partial index on the embedding column for rows where the vector is not null.
   • DCreate a GIN index on the embedding column using the vector_l2_ops operator class.
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6. 5application · medium

   A customer-support chatbot uses retrieval-augmented generation (RAG) with Azure Database for PostgreSQL. The knowledge base contains articles with metadata such as product line and language. The chatbot must only retrieve articles that match the user's product line and language before performing a vector similarity search. Which query pattern should the developer use?

   • AAdd WHERE clauses for product_line and language to the vector similarity query.
   • BPerform the vector similarity search first and then filter the results in the application code.
   • CStore all articles in a single table and ignore metadata during the search.
   • DUse a full-text search on the article text and then apply the metadata filters.
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