Clickhouse (contrib)

Description

The Clickhouse offline store provides support for reading ClickhouseSource.

• Entity dataframes can be provided as a SQL query or can be provided as a Pandas dataframe. A Pandas dataframes will be uploaded to Clickhouse as a table (temporary table by default) in order to complete join operations.

Disclaimer

The Clickhouse 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[clickhouse]'.

Example

feature_store.yaml

project: my_project
registry: data/registry.db
provider: local
offline_store:
  type: feast.infra.offline_stores.contrib.clickhouse_offline_store.clickhouse.ClickhouseOfflineStore
  host: DB_HOST
  port: DB_PORT
  database: DB_NAME
  user: DB_USERNAME
  password: DB_PASSWORD
  use_temporary_tables_for_entity_df: true
online_store:
    path: data/online_store.db

Note that use_temporary_tables_for_entity_df is an optional parameter. The full set of configuration options is available in ClickhouseOfflineStoreConfig.

Functionality Matrix

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

	Clickhouse
get_historical_features (point-in-time correct join)	yes
pull_latest_from_table_or_query (retrieve latest feature values)	yes
pull_all_from_table_or_query (retrieve a saved dataset)	no
offline_write_batch (persist dataframes to offline store)	no
write_logged_features (persist logged features to offline store)	no

Below is a matrix indicating which functionality is supported by ClickhouseRetrievalJob.

	Clickhouse
export to dataframe	yes
export to arrow table	yes
export to arrow batches	no
export to SQL	yes
export to data lake (S3, GCS, etc.)	yes
export to data warehouse	yes
export as Spark dataframe	no
local execution of Python-based on-demand transforms	yes
remote execution of Python-based on-demand transforms	no
persist results in the offline store	yes
preview the query plan before execution	yes
read partitioned data	yes

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