Amazon OpenSearch Vector Search Quiz

5 questions • Pass: 70% • +25 pts

Quiz covering Vector Store Solutions

Amazon OpenSearch Vector Search Quiz

5 questions | Pass: 70% | Earn 25 points

Questions in this quiz

A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.

  1. 1

    Which Amazon OpenSearch Service feature allows you to perform k-Nearest Neighbor (k-NN) searches on high-dimensional vector data?

  2. 2

    When configuring an index for vector search in OpenSearch, which parameter must be set to 'true' in the index settings to enable k-NN?

  3. 3

    Which of the following is a primary benefit of using the HNSW (Hierarchical Navigable Small World) algorithm within OpenSearch for vector search?

  4. 4

    In the context of Amazon OpenSearch, what is the role of the 'ml-commons' plugin when integrated with vector search?

  5. 5

    When tuning an HNSW index in OpenSearch, what is the functional trade-off between the 'm' parameter and the 'ef_construction' parameter?