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  • Introduction
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  • How-to Guides
    • Running Feast with Snowflake/GCP/AWS
      • Install Feast
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    • Running Feast in production (e.g. on Kubernetes)
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      • Adding a custom batch materialization engine
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    • Offline stores
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    • Feature repository
      • feature_store.yaml
      • .feastignore
    • Feature servers
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      • [Alpha] Go feature server
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    • [Beta] Web UI
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    • [Alpha] Vector Database
    • [Alpha] Data quality monitoring
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    • Feast CLI reference
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  • 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. Registries

S3

Description

S3 registry provides support for storing the protobuf representation of your feature store objects (data sources, feature views, feature services, etc.) in S3 file system.

While it can be used in production, there are still inherent limitations with a file-based registries, since changing a single field in the registry requires re-writing the whole registry file. With multiple concurrent writers, this presents a risk of data loss, or bottlenecks writes to the registry since all changes have to be serialized (e.g. when running materialization for multiple feature views or time ranges concurrently).

An example of how to configure this would be:

Example

feature_store.yaml
project: feast_aws_s3
registry:
  path: s3://[YOUR BUCKET YOU CREATED]/registry.pb
  cache_ttl_seconds: 60
online_store: null
offline_store:
  type: dask
PreviousLocalNextGCS

Last updated 3 months ago

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