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  • Introduction
  • Community
  • Roadmap
  • Changelog
  • Getting started
    • Quickstart
    • Concepts
      • Overview
      • Data source
      • Entity
      • Feature view
      • Feature service
      • Feature retrieval
    • Architecture
      • Overview
      • Feature repository
      • Registry
      • Offline store
      • Online store
      • Provider
    • FAQ
  • Tutorials
    • Overview
    • Driver ranking
    • Fraud detection on GCP
    • Real-time credit scoring on AWS
  • How-to Guides
    • Running Feast with GCP/AWS
      • Install Feast
      • Create a feature repository
      • Deploy a feature store
      • Build a training dataset
      • Load data into the online store
      • Read features from the online store
    • Running Feast in production
    • Upgrading from Feast 0.9
    • Adding a custom provider
    • Adding a new online store
    • Adding a new offline store
  • Reference
    • Data sources
      • File
      • BigQuery
      • Redshift
    • Offline stores
      • File
      • BigQuery
      • Redshift
    • Online stores
      • SQLite
      • Redis
      • Datastore
      • DynamoDB
    • Providers
      • Local
      • Google Cloud Platform
      • Amazon Web Services
    • Feature repository
      • feature_store.yaml
      • .feastignore
    • Feast CLI reference
    • Python API reference
    • Usage
  • Project
    • Contribution process
    • Development guide
    • Versioning policy
    • Release process
    • Feast 0.9 vs Feast 0.10+
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  1. Reference
  2. Data sources

BigQuery

Description

BigQuery data sources allow for the retrieval of historical feature values from BigQuery for building training datasets as well as materializing features into an online store.

  • Either a table reference or a SQL query can be provided.

  • No performance guarantees can be provided over SQL query-based sources. Please use table references where possible.

Examples

Using a table reference

from feast import BigQuerySource

my_bigquery_source = BigQuerySource(
    table_ref="gcp_project:bq_dataset.bq_table",
)

Using a query

from feast import BigQuerySource

BigQuerySource(
    query="SELECT timestamp as ts, created, f1, f2 "
          "FROM `my_project.my_dataset.my_features`",
)
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Last updated 3 years ago

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