# Couchbase Columnar (contrib)

## Description

The Couchbase Columnar offline store provides support for reading [CouchbaseColumnarSources](https://docs.feast.dev/v0.58-branch/reference/data-sources/couchbase). **Note that Couchbase Columnar is available through** [**Couchbase Capella**](https://cloud.couchbase.com/)**.**

* Entity dataframes can be provided as a SQL++ query or can be provided as a Pandas dataframe. A Pandas dataframe will be uploaded to Couchbase Capella Columnar as a collection.

## Disclaimer

The Couchbase Columnar 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[couchbase]'`. You can get started by then running `feast init -t couchbase`.

To get started with Couchbase Capella Columnar:

1. Sign up for a [Couchbase Capella](https://cloud.couchbase.com/) account
2. [Deploy a Columnar cluster](https://docs.couchbase.com/columnar/admin/prepare-project.html)
3. [Create an Access Control Account](https://docs.couchbase.com/columnar/admin/auth/auth-data.html)
   * This account should be able to read and write.
   * For testing purposes, it is recommended to assign all roles to avoid any permission issues.
4. [Configure allowed IP addresses](https://docs.couchbase.com/columnar/admin/ip-allowed-list.html)
   * You must allow the IP address of the machine running Feast.

## Example

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

```yaml
project: my_project
registry: data/registry.db
provider: local
offline_store:
  type: couchbase.offline
  connection_string: COUCHBASE_COLUMNAR_CONNECTION_STRING # Copied from Settings > Connection String page in Capella Columnar console, starts with couchbases://
  user: COUCHBASE_COLUMNAR_USER # Couchbase cluster access name from Settings > Access Control page in Capella Columnar console
  password: COUCHBASE_COLUMNAR_PASSWORD # Couchbase password from Settings > Access Control page in Capella Columnar console
  timeout: 120 # Timeout in seconds for Columnar operations, optional
online_store:
    path: data/online_store.db
```

{% endcode %}

Note that `timeout`is an optional parameter. The full set of configuration options is available in [CouchbaseColumnarOfflineStoreConfig](https://rtd.feast.dev/en/master/#feast.infra.offline_stores.contrib.couchbase_offline_store.couchbase.CouchbaseColumnarOfflineStoreConfig).

## Functionality Matrix

The set of functionality supported by offline stores is described in detail [here](https://docs.feast.dev/v0.58-branch/reference/overview#functionality). Below is a matrix indicating which functionality is supported by the Couchbase Columnar offline store.

|                                                                    | Couchbase Columnar |
| ------------------------------------------------------------------ | ------------------ |
| `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) | no                 |

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

|                                                       | Couchbase Columnar |
| ----------------------------------------------------- | ------------------ |
| 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](https://docs.feast.dev/v0.58-branch/reference/overview#functionality-matrix).