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Update the sandbox docker run command in docs to use release tag (#1095)
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‎docs/README.md‎

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@@ -53,7 +53,7 @@ The easiest way to try out Feathr is to use the [Feathr Sandbox](https://feathr-
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```bash
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# 80: Feathr UI, 8888: Jupyter, 7080: Interpret
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docker run -it --rm -p 8888:8888 -p 8081:80 -p 7080:7080 -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox
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docker run -it --rm -p 8888:8888 -p 8081:80 -p 7080:7080 -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox:releases-v1.0.0-rc4
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```
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And you can view default jupyter notebook:
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![Architecture Diagram](./images/architecture.png)
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| Feathr component | Cloud Integrations |
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| ------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Offline store – Object Store | Azure Blob Storage, Azure ADLS Gen2, AWS S3 |
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| Offline store – SQL | Azure SQL DB, Azure Synapse Dedicated SQL Pools, Azure SQL in VM, Snowflake |
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| Streaming Source | Kafka, EventHub |
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| Online store | Redis, [Azure Cosmos DB](https://feathr-ai.github.io/feathr/how-to-guides/jdbc-cosmos-notes.html#using-cosmosdb-as-the-online-store), Aerospike (coming soon) |
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| Feature Registry and Governance | Azure Purview, ANSI SQL such as Azure SQL Server |
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| Compute Engine | Azure Synapse Spark Pools, Databricks |
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| Machine Learning Platform | Azure Machine Learning, Jupyter Notebook, Databricks Notebook |
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| File Format | Parquet, ORC, Avro, JSON, Delta Lake, CSV |
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| Credentials | Azure Key Vault |
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| Feathr component | Cloud Integrations |
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| ------------------------------- |--------------------------------------------------------------------------------------------------------------------------------------|
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| Offline store – Object Store | Azure Blob Storage, Azure ADLS Gen2, AWS S3 |
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| Offline store – SQL | Azure SQL DB, Azure Synapse Dedicated SQL Pools, Azure SQL in VM, Snowflake |
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| Streaming Source | Kafka, EventHub |
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| Online store | Redis, [Azure Cosmos DB](https://feathr-ai.github.io/feathr/how-to-guides/jdbc-cosmos-notes.html#using-cosmosdb-as-the-online-store) |
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| Feature Registry and Governance | Azure Purview, ANSI SQL such as Azure SQL Server |
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| Compute Engine | Azure Synapse Spark Pools, Databricks |
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| Machine Learning Platform | Azure Machine Learning, Jupyter Notebook, Databricks Notebook |
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| File Format | Parquet, ORC, Avro, JSON, Delta Lake, CSV |
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| Credentials | Azure Key Vault |
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## 🚀 Roadmap
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- [x] Support streaming features with transformation
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- [x] Support common data sources and sinks. Read more in the [Cloud Integrations and Architecture](#️-cloud-integrations-and-architecture) part.
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- [x] Support feature store UI, including Lineage and Search functionalities
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- [x] Support a sandbox Feathr environment for better getting started experience
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- [x] Support online transformation
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- [x] Support feature data deletion and retention
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- [ ] More Feathr online client libraries such as Java
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- [ ] Support feature versioning
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- [ ] Support feature monitoring

‎docs/dev_guide/feathr_overall_release_guide.md‎

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- [feathr_config.yaml](https://github.com/feathr-ai/feathr/blob/main/feathr_project/test/test_user_workspace/feathr_config.yaml#L86) - To set the spark runtime location for Azure Synapse and Azure Databricks used by test suite. Please update all .yaml files under this path.
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- [package.json](https://github.com/feathr-ai/feathr/blob/main/ui/package.json#L3) - For Feathr UI version
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- [package-lock.json](https://github.com/feathr-ai/feathr/blob/main/ui/package-lock.json) - For Feathr UI version
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- [README.md](https://github.com/feathr-ai/feathr/blob/main/docs/README.md) - Update docker image version in the homepage README.
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- [quickstart_local_sandbox.md](https://github.com/feathr-ai/feathr/blob/main/docs/quickstart_local_sandbox.md) - Update docker image version in the sandbox quickstart guide.
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Following file should only be updated for release, which means should be skipped for release candidate.

‎docs/quickstart_local_sandbox.md‎

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```bash
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# 80: Feathr UI, 8888: Jupyter, 7080: Interpret
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docker run -it --rm -p 8888:8888 -p 8081:80 -p 7080:7080 -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox:releases/v1.0.0-rc4
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docker run -it --rm -p 8888:8888 -p 8081:80 -p 7080:7080 -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox:releases-v1.0.0-rc4
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```
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It should pop up a Jupyter link in `http://127.0.0.1:8888/`. Double click on the notebook file to start the Jupyter Notebook, and you should be able to see the Feathr sample notebook. Click the triangle button on the Jupyter notebook and the whole notebook will run locally.
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- Feathr Registry API
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- Local Redis server
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## Build Docker Container
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## Build Feathr Sandbox Docker Image
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If you want to build the Feathr sandbox, run the below command in the Feathr root directory:
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By default, Feathr Sandbox uses a SQLite backend in Feathr registry, and the content will be deleted if you restart the container. If you want to use a persistent registry, say a remote MySQL database or SQL Server, you can configure an environment variable when starting the Feathr Sandbox container like below, by specifying `FEATHR_SANDBOX_REGISTRY_URL` environment variable:
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```bash
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docker run -it --rm -p 8888:8888 -p 8081:80 -p 7080:7080 --env FEATHR_SANDBOX_REGISTRY_URL="mysql://scott:tiger@localhost/foo" -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox
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docker run -it --rm -p 8888:8888 -p 8081:80 -p 7080:7080 --env FEATHR_SANDBOX_REGISTRY_URL="mysql://scott:tiger@localhost/foo" -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox:releases-v1.0.0-rc4
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```
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Take a look at the [Database URLs](https://docs.sqlalchemy.org/en/20/core/engines.html#database-urls) section for more details on how this URL is formatted. Basically it will be like this:

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