Snowflake

Description

The Snowflake online store provides support for materializing feature values into a Snowflake Transient Table for serving online features.

  • Only the latest feature values are persisted

The data model for using a Snowflake Transient Table as an online store follows a tall format (one row per feature)):

  • "entity_feature_key" (BINARY) -- unique key used when reading specific feature_view x entity combination

  • "entity_key" (BINARY) -- repeated key currently unused for reading entity_combination

  • "feature_name" (VARCHAR)

  • "value" (BINARY)

  • "event_ts" (TIMESTAMP)

  • "created_ts" (TIMESTAMP)

(This model may be subject to change when Snowflake Hybrid Tables are released)

Getting started

In order to use this online store, you'll need to run pip install 'feast[snowflake]'. You can then get started with the command feast init REPO_NAME -t snowflake.

Example

feature_store.yaml
project: my_feature_repo
registry: data/registry.db
provider: local
online_store:
    type: snowflake.online
    account: SNOWFLAKE_DEPLOYMENT_URL
    user: SNOWFLAKE_USER
    password: SNOWFLAKE_PASSWORD
    role: SNOWFLAKE_ROLE
    warehouse: SNOWFLAKE_WAREHOUSE
    database: SNOWFLAKE_DATABASE

Tags KWARGs Actions:

"snowflake-online-store/online_path": Adding the "snowflake-online-store/online_path" key to a FeatureView tags parameter allows you to choose the online table path for the online serving table (ex. "{database}"."{schema}").

example_config.py
driver_stats_fv = FeatureView(
    ...
    tags={"snowflake-online-store/online_path": '"FEAST"."ONLINE"'},
)

The full set of configuration options is available in SnowflakeOnlineStoreConfig.

Functionality Matrix

The set of functionality supported by online stores is described in detail here. Below is a matrix indicating which functionality is supported by the Snowflake online store.

Snowflake

write feature values to the online store

yes

read feature values from the online store

yes

update infrastructure (e.g. tables) in the online store

yes

teardown infrastructure (e.g. tables) in the online store

yes

generate a plan of infrastructure changes

no

support for on-demand transforms

yes

readable by Python SDK

yes

readable by Java

no

readable by Go

no

support for entityless feature views

yes

support for concurrent writing to the same key

no

support for ttl (time to live) at retrieval

no

support for deleting expired data

no

collocated by feature view

yes

collocated by feature service

no

collocated by entity key

no

To compare this set of functionality against other online stores, please see the full functionality matrix.