# Athena (contrib)

## Description

The Athena offline store provides support for reading [AthenaSources](https://docs.feast.dev/master/reference/data-sources/athena).

* Entity dataframes can be provided as a SQL query or can be provided as a Pandas dataframe.

## Disclaimer

The Athena 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[aws]'`.

## Example

{% code title="feature\_store.yaml" %}

```yaml
project: my_project
registry: data/registry.db
provider: local
offline_store:
  type: athena
  data_source: AwsDataCatalog
  region: us-east-1
  database: my_database
  workgroup: primary
online_store:
    path: data/online_store.db
```

{% endcode %}

The full set of configuration options is available in [AthenaOfflineStoreConfig](https://rtd.feast.dev/en/master/#feast.infra.offline_stores.contrib.athena_offline_store.athena.AthenaOfflineStoreConfig).

## Functionality Matrix

The set of functionality supported by offline stores is described in detail [here](https://docs.feast.dev/master/reference/overview#functionality). Below is a matrix indicating which functionality is supported by the Athena offline store.

|                                                                    | Athena |
| ------------------------------------------------------------------ | ------ |
| `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)          | yes    |
| `offline_write_batch` (persist dataframes to offline store)        | no     |
| `write_logged_features` (persist logged features to offline store) | yes    |

Below is a matrix indicating which functionality is supported by `AthenaRetrievalJob`.

|                                                       | Athena |
| ----------------------------------------------------- | ------ |
| 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.)                   | no     |
| export to data warehouse                              | no     |
| 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](https://docs.feast.dev/master/reference/overview#functionality-matrix).