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name: retrieval-and-materialization description: "Use for Feast offline/historical retrieval, online retrieval, point-in-time joins, materialization, push ingestion, saved datasets, local retrieval checks, and DQM/monitoring basics." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Feast Retrieval and Materialization

Use this sub-skill when the user asks to retrieve training data, batch-score features, fetch online features for inference, materialize feature views into an online store, push streaming rows, save historical datasets, or diagnose null/stale retrieval results.

Route first

• Use this skill for FeatureStore.get_historical_features, get_online_features, materialize, materialize_incremental, push, entity rows, feature refs, FeatureService retrieval, local file offline stores, and SQLite online stores.
• Route feature object modeling, Entity, FeatureView, FeatureService, PushSource, and field schema questions to ../feature-definitions/SKILL.md.
• Route feature repo initialization, feature_store.yaml, feast apply, feast plan, registry paths, and CLI repo lifecycle to ../feature-repos-and-cli/SKILL.md.
• Route feature server, offline server, registry server, REST/gRPC, TLS, auth, and remote serving endpoints to ../servers-and-remote/SKILL.md.
• Route vector document retrieval, retrieve_online_documents, vector stores, and RAG retrievers to ../rag-and-vector-search/SKILL.md.

Fast workflow

1. Confirm the feature repo is applied and the registry is readable.
2. For historical retrieval, build an entity dataframe with join keys and event_timestamp, or use supported entity-less start_date/end_date retrieval.
3. Select features with either a FeatureService or feature refs such as driver_hourly_stats:conv_rate.
4. For online retrieval, materialize the needed feature views first, then call get_online_features(...).to_dict() or .to_df().
5. If results are null, stale, or missing columns, check join keys, timestamp windows, TTL, materialization range, online-store config, and feature-view online=True settings.

References

• references/api-reference.md for SDK and CLI retrieval/materialization calls.
• references/workflows.md for historical, online, push, saved dataset, and DQM flows.
• references/data-formats.md for entity rows, entity dataframes, feature refs, outputs, and local stores.
• references/troubleshooting.md for common failures and validation signals.
• scripts/local_retrieval_smoke.py for a safe local repo checker and command planner.