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Merge pull request feast-dev#15 from redhatHameed/doc-change
update the document change and fix teardown function
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docs/SUMMARY.md

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* [PostgreSQL (contrib)](reference/offline-stores/postgres.md)
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* [Trino (contrib)](reference/offline-stores/trino.md)
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* [Azure Synapse + Azure SQL (contrib)](reference/offline-stores/mssql.md)
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* [Remote Offline](reference/offline-stores/remote-offline-store.md)
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* [Online stores](reference/online-stores/README.md)
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* [Overview](reference/online-stores/overview.md)
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* [SQLite](reference/online-stores/sqlite.md)
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* [Python feature server](reference/feature-servers/python-feature-server.md)
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* [\[Alpha\] Go feature server](reference/feature-servers/go-feature-server.md)
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* [\[Alpha\] AWS Lambda feature server](reference/feature-servers/alpha-aws-lambda-feature-server.md)
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* [Remote Offline Store ](reference/feature-servers/remote-offline-store.md)
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* [Offline Feature Server](reference/feature-servers/offline-feature-server)
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* [\[Beta\] Web UI](reference/alpha-web-ui.md)
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* [\[Alpha\] On demand feature view](reference/alpha-on-demand-feature-view.md)

docs/reference/feature-servers/README.md

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{% content-ref url="alpha-aws-lambda-feature-server.md" %}
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[alpha-aws-lambda-feature-server.md](alpha-aws-lambda-feature-server.md)
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{% endcontent-ref %}
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{% content-ref url="offline-feature-server.md" %}
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[offline-feature-server.md](offline-feature-server.md)
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{% endcontent-ref %}
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# Offline feature server
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## Description
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The Offline feature server is an Apache Arrow Flight Server that uses the gRPC communication protocol to exchange data.
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This server wraps calls to existing offline store implementations and exposes interfaces as Arrow Flight endpoints.
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## How to configure the server
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## CLI
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There is a CLI command that starts the Offline feature server: `feast serve_offline`. By default, remote offline server uses port 8815, the port can be overridden with a `--port` flag.
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## Deploying as a service on Kubernetes
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The Offline feature server can be deployed using helm chart see this [helm chart](https://github.com/feast-dev/feast/blob/master/infra/charts/feast-feature-server).
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User need to set `feast_mode=offline`, when installing Offline feature server as shown in the helm command below:
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```
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helm install feast-offline-server feast-charts/feast-feature-server --set feast_mode=offline --set feature_store_yaml_base64=$(base64 > feature_store.yaml)
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```
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## Server Example
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The complete example can be find under [remote-offline-store-example](../../../examples/remote-offline-store)
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## How to configure the client
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Please see the detail how to configure offline store client [remote-offline-store.md](../offline-stores/remote-offline-store.md)
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## Functionality Matrix
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The set of functionalities supported by remote offline stores is the same as those supported by offline stores with the SDK, which are described in detail [here](../offline-stores/overview.md#functionality).
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docs/reference/feature-servers/remote-offline-store.md

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# Remote Offline Store
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## Description
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The Remote Offline Store is an Arrow Flight client for the offline store that implements the `RemoteOfflineStore` class using the existing `OfflineStore` interface.
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The client implements various methods, including `get_historical_features`, `pull_latest_from_table_or_query`, `write_logged_features`, and `offline_write_batch`.
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## How to configure the client
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User needs to create client side `feature_store.yaml` file and set the `offline_store` type `remote` and provide the server connection configuration
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including adding the host and specifying the port (default is 8815) required by the Arrow Flight client to connect with the Arrow Flight server.
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{% code title="feature_store.yaml" %}
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```yaml
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offline_store:
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type: remote
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host: localhost
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port: 8815
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```
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{% endcode %}
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## Client Example
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The complete example can be find under [remote-offline-store-example](../../../examples/remote-offline-store)
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## How to configure the server
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Please see the detail how to configure offline feature server [offline-feature-server.md](../feature-servers/offline-feature-server.md)

sdk/python/tests/integration/feature_repos/universal/data_sources/file.py

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def teardown(self):
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super().teardown()
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if self.proc is None and self.proc.is_alive():
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if self.proc is not None:
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self.proc.kill()
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# wait server to free the port

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