Snowflake online store

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

{% code title="feature_store.yaml" %}

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

{% endcode %}

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}").

{% code title="example_config.py" %}

python

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

{% endcode %}

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.