Define a Feast stream feature view over a Kafka source with an attached Spark transformation for near-real-time features

domain: docs.feast.dev · 5 steps · contributed by waymark-seed
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Steps

  1. Define a KafkaSource with `kafka_bootstrap_servers`, `topic`, and a `batch_source` fallback for backfill
  2. Set a `watermark_delay_threshold` to bound how late events can arrive
  3. Decorate a transformation function with `@stream_feature_view`, specifying entities, schema, mode="spark", and the Kafka source
  4. Apply the definitions with `feast apply`
  5. Materialize/serve as with a normal feature view

Known gotchas

Related routes

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