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  • Introduction
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      • Driver ranking
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    • Validating historical features with Great Expectations
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    • Retrieval Augmented Generation (RAG) with Feast
  • How-to Guides
    • Running Feast with Snowflake/GCP/AWS
      • Install Feast
      • Create a feature repository
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      • Scaling Feast
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    • Running Feast in production (e.g. on Kubernetes)
    • Customizing Feast
      • Adding a custom batch materialization engine
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    • Starting Feast servers in TLS(SSL) Mode
  • Reference
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    • Feature repository
      • feature_store.yaml
      • .feastignore
    • Feature servers
      • Python feature server
      • [Alpha] Go feature server
      • Offline Feature Server
      • Registry server
    • [Beta] Web UI
    • [Beta] On demand feature view
    • [Alpha] Vector Database
    • [Alpha] Data quality monitoring
    • [Alpha] Streaming feature computation with Denormalized
    • Feast CLI reference
    • Python API reference
    • Usage
  • Project
    • Contribution process
    • Development guide
    • Backwards Compatibility Policy
      • Maintainer Docs
    • Versioning policy
    • Release process
    • Feast 0.9 vs Feast 0.10+
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  1. Reference
  2. Providers

Local

Description

  • Offline Store: Uses the File offline store by default. Also supports BigQuery as the offline store.

  • Online Store: Uses the Sqlite online store by default. Also supports Redis and Datastore as online stores.

Example

feature_store.yaml
project: my_feature_repo
registry: data/registry.db
provider: local
PreviousProvidersNextGoogle Cloud Platform

Last updated 6 days ago

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