From be0c05d391864b4883a7ebed891e7b9cbdb44e0e Mon Sep 17 00:00:00 2001 From: Xiaoyong Zhu Date: Tue, 17 Jan 2023 19:42:05 -0800 Subject: [PATCH 1/5] Update docs --- docs/README.md | 20 ++++++++++++++++++++ docs/quickstart_local_sandbox.md | 14 ++++++++++++-- 2 files changed, 32 insertions(+), 2 deletions(-) diff --git a/docs/README.md b/docs/README.md index acfae7e62..10ee0a710 100644 --- a/docs/README.md +++ b/docs/README.md @@ -74,6 +74,26 @@ If you want to set up everything manually, you can checkout the [Feathr CLI depl | [Fraud Detection Demo](./samples/fraud_detection_demo.ipynb) | An example to demonstrate Feature Store using multiple data sources such as user account and transaction data. | Azure Synapse, Databricks, Local Spark | | [Product Recommendation Demo](./samples/product_recommendation_demo_advanced.ipynb) | Feathr Feature Store example notebook with a product recommendation scenario | Azure Synapse, Databricks, Local Spark | +## πŸƒ Getting Started with Feathr + +The best way to try out Feathr is to use the [Feathr Sandbox](https://feathr-ai.github.io/feathr/quickstart_local_sandbox.html) which is a self-contained container with most of Feathr's capabilities. To use it, simply run this command: + +```bash +# 80: Feathr UI 8000: Feathr API 8888: Jupyter 8080: VsCode 7080: Interpret +docker run -it --rm -p 8888:8888 -p 8000:8000 -p 80:80 -p 8080:8080 -p 7080:7080 --env API_BASE="api/v1" --env FEATHR_SANDBOX=True -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox +``` + +And you can view default jupyter notebook: +```bash +http://localhost:8888/lab/workspaces/auto-w/tree/local_quickstart_notebook.ipynb +``` + +After running the Notebooks, all the features will be registered in the UI, and you can visit the Feathr UI at: + +```bash +http://localhost:80 +``` + ## πŸ› οΈ Install Feathr Client Locally If you want to install Feathr client in a python environment, use this: diff --git a/docs/quickstart_local_sandbox.md b/docs/quickstart_local_sandbox.md index e72b3a0c4..7b721ecbf 100644 --- a/docs/quickstart_local_sandbox.md +++ b/docs/quickstart_local_sandbox.md @@ -21,15 +21,25 @@ The Sandbox is ideal for: ## Getting Started -To get started, simply run the command below. Note that the image is around 5GB so it might take a while to pull it from DockerHub. +First, make sure you have docker installed successfully on your machine by running this command: + +```bash +docker run hello-world +``` + +To get started using Feathr, simply run the command below. Note that the image is around 5GB so it might take a while to pull it from DockerHub. ```bash # 80: Feathr UI 8000: Feathr API 8888: Jupyter 8080: VsCode 7080: Interpret -docker run -it --rm -p 8888:8888 -p 8000:8000 -p 80:80 -p 8080:8080 -p 7080:7080 --env CONNECTION_STR="Server=" --env API_BASE="api/v1" --env FEATHR_SANDBOX=True -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox +docker run -it --rm -p 8888:8888 -p 8000:8000 -p 80:80 -p 8080:8080 -p 7080:7080 --env API_BASE="api/v1" --env FEATHR_SANDBOX=True -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox ``` 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. +If you see some errors like below, simply change the `-p 80:80` part to `-p :80` so the Feathr UI will be redirected to the new port. + +`docker: Error response from daemon: driver failed programming external connectivity on endpoint hardcore_bose (ae107e924cddce6b942f96f2654369345b027ac82e5e44929a9f132e2af71746): Bind for 0.0.0.0:80 failed: port is already allocated.` + The default jupyter notebook is here: ```bash http://localhost:8888/lab/workspaces/auto-w/tree/local_quickstart_notebook.ipynb From 31306b66878764bc9a7280639da0b32ed7e21b4a Mon Sep 17 00:00:00 2001 From: Xiaoyong Zhu Date: Tue, 17 Jan 2023 19:50:05 -0800 Subject: [PATCH 2/5] Update README.md --- docs/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/README.md b/docs/README.md index 10ee0a710..979dad5ac 100644 --- a/docs/README.md +++ b/docs/README.md @@ -76,7 +76,7 @@ If you want to set up everything manually, you can checkout the [Feathr CLI depl ## πŸƒ Getting Started with Feathr -The best way to try out Feathr is to use the [Feathr Sandbox](https://feathr-ai.github.io/feathr/quickstart_local_sandbox.html) which is a self-contained container with most of Feathr's capabilities. To use it, simply run this command: +The easiest way to try out Feathr is to use the [Feathr Sandbox](https://feathr-ai.github.io/feathr/quickstart_local_sandbox.html) which is a self-contained container with most of Feathr's capabilities. To use it, simply run this command: ```bash # 80: Feathr UI 8000: Feathr API 8888: Jupyter 8080: VsCode 7080: Interpret From 6f2c59b23896651654e1d341d073d9a1b2cfd633 Mon Sep 17 00:00:00 2001 From: Xiaoyong Zhu Date: Tue, 17 Jan 2023 22:11:01 -0800 Subject: [PATCH 3/5] Update README.md --- docs/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/README.md b/docs/README.md index 979dad5ac..503435f5d 100644 --- a/docs/README.md +++ b/docs/README.md @@ -76,7 +76,7 @@ If you want to set up everything manually, you can checkout the [Feathr CLI depl ## πŸƒ Getting Started with Feathr -The easiest way to try out Feathr is to use the [Feathr Sandbox](https://feathr-ai.github.io/feathr/quickstart_local_sandbox.html) which is a self-contained container with most of Feathr's capabilities. To use it, simply run this command: +The easiest way to try out Feathr is to use the [Feathr Sandbox](https://feathr-ai.github.io/feathr/quickstart_local_sandbox.html) which is a self-contained container with most of Feathr's capabilities and you should be productive in 5 minutes. To use it, simply run this command: ```bash # 80: Feathr UI 8000: Feathr API 8888: Jupyter 8080: VsCode 7080: Interpret From 305f6c78dcda5c50f2ebe9e84f21c925783db5ab Mon Sep 17 00:00:00 2001 From: Xiaoyong Zhu Date: Tue, 17 Jan 2023 23:47:47 -0800 Subject: [PATCH 4/5] update URLs --- build.gradle | 4 ++-- docs/dev_guide/creating_bacpac_file.md | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/build.gradle b/build.gradle index 82aa48514..19b9d62a7 100644 --- a/build.gradle +++ b/build.gradle @@ -174,7 +174,7 @@ allprojects { pom { name = 'Feathr' description = 'An Enterprise-Grade, High Performance Feature Store' - url = 'https://github.com/linkedin/feathr' + url = 'https://github.com/feathr-ai/feathr' licenses { license { name = 'APL2' @@ -190,7 +190,7 @@ allprojects { } scm { connection = 'scm:git@github.com:linkedin/feathr.git' - url = 'https://github.com/linkedin/feathr' + url = 'https://github.com/feathr-ai/feathr' } } } diff --git a/docs/dev_guide/creating_bacpac_file.md b/docs/dev_guide/creating_bacpac_file.md index 02754184c..8bcb3f26c 100644 --- a/docs/dev_guide/creating_bacpac_file.md +++ b/docs/dev_guide/creating_bacpac_file.md @@ -13,7 +13,7 @@ In case you need to re-create the BACPAC file, follow these steps: 1. Create a new, empty SQL database on Azure ![Create Empty Database](../images/bacpac-sql-database.png) -2. Connect to the database with a SQL client, such as Azure Data Studio, run the SQL script at https://github.com/linkedin/feathr/blob/main/registry/sql-registry/scripts/schema.sql +2. Connect to the database with a SQL client, such as Azure Data Studio, run the SQL script at https://github.com/feathr-ai/feathr/blob/main/registry/sql-registry/scripts/schema.sql 3. Now we created the tables required by the registry service, we can use β€œExport” function to create the BACPAC file ![Bacpac Export UI](../images/bacpac-export.png) From 2c59810168809d227c75588c28b9dce438260986 Mon Sep 17 00:00:00 2001 From: Xiaoyong Zhu Date: Wed, 18 Jan 2023 00:29:04 -0800 Subject: [PATCH 5/5] fix comments --- docs/README.md | 4 ++-- docs/quickstart_local_sandbox.md | 8 ++++---- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/README.md b/docs/README.md index 503435f5d..05f61f169 100644 --- a/docs/README.md +++ b/docs/README.md @@ -80,7 +80,7 @@ The easiest way to try out Feathr is to use the [Feathr Sandbox](https://feathr- ```bash # 80: Feathr UI 8000: Feathr API 8888: Jupyter 8080: VsCode 7080: Interpret -docker run -it --rm -p 8888:8888 -p 8000:8000 -p 80:80 -p 8080:8080 -p 7080:7080 --env API_BASE="api/v1" --env FEATHR_SANDBOX=True -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox +docker run -it --rm -p 8888:8888 -p 8000:8000 -p 8081:80 -p 8080:8080 -p 7080:7080 --env API_BASE="api/v1" --env FEATHR_SANDBOX=True -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox ``` And you can view default jupyter notebook: @@ -91,7 +91,7 @@ http://localhost:8888/lab/workspaces/auto-w/tree/local_quickstart_notebook.ipynb After running the Notebooks, all the features will be registered in the UI, and you can visit the Feathr UI at: ```bash -http://localhost:80 +http://localhost:8081 ``` ## πŸ› οΈ Install Feathr Client Locally diff --git a/docs/quickstart_local_sandbox.md b/docs/quickstart_local_sandbox.md index 7b721ecbf..c964f744b 100644 --- a/docs/quickstart_local_sandbox.md +++ b/docs/quickstart_local_sandbox.md @@ -31,14 +31,14 @@ To get started using Feathr, simply run the command below. Note that the image i ```bash # 80: Feathr UI 8000: Feathr API 8888: Jupyter 8080: VsCode 7080: Interpret -docker run -it --rm -p 8888:8888 -p 8000:8000 -p 80:80 -p 8080:8080 -p 7080:7080 --env API_BASE="api/v1" --env FEATHR_SANDBOX=True -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox +docker run -it --rm -p 8888:8888 -p 8000:8000 -p 8081:80 -p 8080:8080 -p 7080:7080 --env API_BASE="api/v1" --env FEATHR_SANDBOX=True -e GRANT_SUDO=yes feathrfeaturestore/feathr-sandbox ``` 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. -If you see some errors like below, simply change the `-p 80:80` part to `-p :80` so the Feathr UI will be redirected to the new port. +If you see some errors like below, simply change the `-p 8081:80` part to `-p :80` so the Feathr UI will be redirected to the new port. -`docker: Error response from daemon: driver failed programming external connectivity on endpoint hardcore_bose (ae107e924cddce6b942f96f2654369345b027ac82e5e44929a9f132e2af71746): Bind for 0.0.0.0:80 failed: port is already allocated.` +`docker: Error response from daemon: driver failed programming external connectivity on endpoint hardcore_bose (ae107e924cddce6b942f96f2654369345b027ac82e5e44929a9f132e2af71746): Bind for 0.0.0.0:8081 failed: port is already allocated.` The default jupyter notebook is here: ```bash @@ -51,7 +51,7 @@ http://localhost:8888/lab/workspaces/auto-w/tree/local_quickstart_notebook.ipynb After running the Notebooks, all the features will be registered in the UI, and you can visit the Feathr UI at: ```bash -http://localhost:80 +http://localhost:8081 ```