The Spark offline store provides support for reading SparkSources.
Entity dataframes can be provided as a SQL query or can be provided as a Pandas dataframe. A Pandas dataframes will be converted to a Spark dataframe and processed as a temporary view.
Disclaimer
The Spark offline store does not achieve full test coverage. Please do not assume complete stability.
Getting started
In order to use this offline store, you'll need to run pip install 'feast[spark]'. You can get started by then running feast init -t spark.
The full set of configuration options is available in .
The set of functionality supported by offline stores is described in detail . Below is a matrix indicating which functionality is supported by the Spark offline store.
Spark
Below is a matrix indicating which functionality is supported by SparkRetrievalJob.
Spark
To compare this set of functionality against other offline stores, please see the full .
offline_write_batch (persist dataframes to offline store)
no
write_logged_features (persist logged features to offline store)
no
export to SQL
no
export to data lake (S3, GCS, etc.)
no
export to data warehouse
no
export as Spark dataframe
yes
local execution of Python-based on-demand transforms
no
remote execution of Python-based on-demand transforms