Title: Discussion 4 — Choosing an Index When Filtering Dominates Your Workload
Course: AIINFRA 301: Production RAG & LLMOps — Observability and Evaluation > Section: Week 04 — Indexing Deep Dive: HNSW vs IVF and Metadata Filtering

💬 Discussion 4 — Choosing an Index When Filtering Dominates Your Workload (20 pts)

Imagine your RAG corpus is 80% one document type (say, "internal memos"), and your users almost always add a metadata filter to search within that one document type before running their vector query. Post a response addressing:

- Would you choose HNSW or IVF (or a hybrid/filter-aware approach) for this workload, and why?
- How does the fact that users routinely filter — rather than occasionally filtering — change your answer compared to a workload with no filtering at all?
- Name at least one concrete parameter (from m, ef_construction, ef_search, nlist, nprobe, or a Qdrant payload index) you'd tune first, and explain what trade-off you're making.

Then respond to at least two classmates — ideally to someone who reached a different conclusion than you. Push on their reasoning: what workload assumption would have to change for their answer to flip?