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FAQ

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Getting started

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Do you have any examples of how Feast should be used?

The is the easiest way to learn about Feast. For more detailed tutorials, please check out the page.

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Concepts

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What is the difference between feature tables and feature views?

Feature tables from Feast 0.9 have been renamed to feature views in Feast 0.10+. For more details, please see the discussion .

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Functionality

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Does Feast provide security or access control?

Feast currently does not support any access control other than the access control required for the Provider's environment (for example, GCP and AWS permissions).

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Does Feast support streaming sources?

Feast is actively working on this right now. Please reach out to the Feast team if you're interested in giving feedback!

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Does Feast support composite keys?

A feature view can be defined with multiple entities. Since each entity has a unique join_key, using multiple entities will achieve the effect of a composite key.

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How does Feast compare with Tecton?

Please see a detailed comparison of Feast vs. Tecton . For another comparison, please see .

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What are the performance/latency characteristics of Feast?

Feast is designed to work at scale and support low latency online serving. Benchmarks to be released soon, and active work is underway to support very latency sensitive use cases.

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Does Feast support embeddings and list features?

Yes. Specifically:

  • Simple lists / dense embeddings:

    • BigQuery supports list types natively

    • Redshift does not support list types, so you'll need to serialize these features into strings (e.g. json or protocol buffers)

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Does Feast support X storage engine?

The list of supported offline and online stores can be found and , respectively. The indicates the stores for which we are planning to add support. Finally, our Provider abstraction is built to be extensible, so you can plug in your own implementations of offline and online stores. Please see more details about custom providers .

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How can I add a custom online store?

Please follow the instructions .

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Does Feast support S3 as a data source?

Yes. There are two ways to use S3 in Feast:

  • Using Redshift as a data source via Spectrum (), and then continuing with the guide. See a we did on this at our apply() meetup.

  • Using the s3_endpoint_override in a FileSource data source. This endpoint is more suitable for quick proof of concepts that won't necessarily scale for production use cases.

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How can I use Spark with Feast?

Feast does not support Spark natively. However, you can create a that will support Spark, which can help with more scalable materialization and ingestion.

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Is Feast planning on supporting X functionality?

Please see the .

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Project

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What is the difference between Feast 0.9 and Feast 0.10+?

Feast 0.10+ is much lighter weight and more extensible than Feast 0.9. It is designed to be simple to install and use. Please see this for more details.

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How do I migrate from Feast 0.9 to Feast 0.10+?

Please see this . If you have any questions or suggestions, feel free to leave a comment on the document!

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How do I contribute to Feast?

For more details on contributing to the Feast community, see and this .

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What are the plans for Feast Core, Feast Serving, and Feast Spark?

Feast Core and Feast Serving were both part of Feast Java. We plan to support Feast Serving. We will not support Feast Core; instead we will support our object store based registry. We will not support Feast Spark. For more details on what we plan on supporting, please see the .

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Don't see your question?

We encourage you to ask questions on or . Even better, once you get an answer, add the answer to this FAQ via a !

Feast's implementation of online stores serializes features into Feast protocol buffers and supports list types (see )

  • Sparse embeddings (e.g. one hot encodings)

    • One way to do this efficiently is to have a protobuf or string representation of

  • quickstart
    tutorials
    herearrow-up-right
    herearrow-up-right
    herearrow-up-right
    here
    here
    roadmap
    here
    here
    AWS tutorialarrow-up-right
    Running Feast with GCP/AWS
    presentationarrow-up-right
    custom provider
    roadmap
    documentarrow-up-right
    documentarrow-up-right
    here
    here
    roadmap
    Slackarrow-up-right
    Githubarrow-up-right
    pull request
    referencearrow-up-right
    https://www.tensorflow.org/guide/sparse_tensorarrow-up-right