- Entity dataframes can be provided as a SQL query or can be provided as a Pandas dataframe. A Pandas dataframes will be uploaded to Trino as a table in order to complete join operations.
The Trino offline store does not achieve full test coverage. Please do not assume complete stability.
In order to use this offline store, you'll need to run
pip install 'feast[trino]'. You can then run
feast init, then swap out
feature_store.yamlwith the below example to connect to Trino.
The set of functionality supported by offline stores is described in detail here. Below is a matrix indicating which functionality is supported by the Trino offline store.
Below is a matrix indicating which functionality is supported by
export to dataframe
export to arrow table
export to arrow batches
export to SQL
export to data lake (S3, GCS, etc.)
export to data warehouse
export as Spark dataframe
local execution of Python-based on-demand transforms
remote execution of Python-based on-demand transforms
persist results in the offline store
preview the query plan before execution
read partitioned data
To compare this set of functionality against other offline stores, please see the full functionality matrix.