Merge branch 'main' into fcm_feathr_merge

* main:
  Fixing purview test issues and improve performance (#350)
  [feathr] Add product_recommendation advanced sample (#348)
  obejectId query cmd update (#360)
  add license, release, docs, python api ref badges with shields img (#357)
  quick fix the 404 not found in read me link (#355)
  Python SQL Registry (#311)
  enable JWT token param in frontend API calls (#337)
  Optimize environment variable behavior (#333)
  Adding better warning message to let user know that config file is missing and they need to set env parameters. (#347)
  Feature Monitoring (#330)
  Windoze/211 maven submission (#334)
  Windoze/211 maven submission (#334)
  Windoze/211 maven submission (#334)
  Fix Synapse quickstart link (#346)
  Show feature details when click feature in lineage graph (#339)
  Update pull_request_push_test.yml
  Update UI README for how to create overrides for local development (#335)
  Update databricks quick start experience (#217)

.github/workflows/pull_request_push_test.yml

@@ -111,6 +111,7 @@ jobs:
           BLOB_KEY: ${{secrets.BLOB_KEY}}
           JDBC_SF_PASSWORD: ${{secrets.JDBC_SF_PASSWORD}}
           KAFKA_SASL_JAAS_CONFIG: ${{secrets.KAFKA_SASL_JAAS_CONFIG}}
+          MONITORING_DATABASE_SQL_PASSWORD: ${{secrets.MONITORING_DATABASE_SQL_PASSWORD}}
           SPARK_CONFIG__DATABRICKS__FEATHR_RUNTIME_LOCATION: dbfs:/${{ env.CI_SPARK_REMOTE_JAR_FOLDER}}/${{ env.FEATHR_LOCAL_JAR_NAME}}
 
         run: |
@@ -177,6 +178,7 @@ jobs:
           JDBC_DRIVER: ${{secrets.JDBC_DRIVER}}
           JDBC_SF_PASSWORD: ${{secrets.JDBC_SF_PASSWORD}}
           KAFKA_SASL_JAAS_CONFIG: ${{secrets.KAFKA_SASL_JAAS_CONFIG}}
+          MONITORING_DATABASE_SQL_PASSWORD: ${{secrets.MONITORING_DATABASE_SQL_PASSWORD}}
           SPARK_CONFIG__AZURE_SYNAPSE__FEATHR_RUNTIME_LOCATION: "abfss://${{secrets.SPARK_JAR_BLOB_CONTAINER}}@feathrazuretest3storage.dfs.core.windows.net/${{ env.CI_SPARK_REMOTE_JAR_FOLDER}}/${{ env.FEATHR_LOCAL_JAR_NAME}}"
         run: |
           # skip databricks related test as we just ran the test; also seperate databricks and synapse test to make sure there's no write conflict

README.md

@@ -1,5 +1,10 @@
 # Feathr – An Enterprise-Grade, High Performance Feature Store
 
+[![License](https://img.shields.io/badge/License-Apache%202.0-blue)](https://github.com/linkedin/feathr/blob/main/LICENSE)
+[![GitHub Release](https://img.shields.io/github/v/release/linkedin/feathr.svg?style=flat&sort=semver&color=blue)](https://github.com/linkedin/feathr/releases)
+[![Docs Latest](https://img.shields.io/badge/docs-latest-blue.svg)](https://linkedin.github.io/feathr/)
+[![Python API](https://img.shields.io/readthedocs/feathr?label=Python%20API)](https://feathr.readthedocs.io/en/latest/)
+
 ## What is Feathr?
 
 Feathr is the feature store that is used in production in LinkedIn for many years and was open sourced in April 2022. Read our announcement on [Open Sourcing Feathr](https://engineering.linkedin.com/blog/2022/open-sourcing-feathr---linkedin-s-feature-store-for-productive-m) and [Feathr on Azure](https://azure.microsoft.com/en-us/blog/feathr-linkedin-s-feature-store-is-now-available-on-azure/).
@@ -44,8 +49,10 @@ pip install git+https://github.com/linkedin/feathr.git#subdirectory=feathr_proje
 
 ## ☁️ Running Feathr on Cloud
 
+Feathr has native integrations with Databricks and Azure Synapse:
+
 - Please read the [Quick Start Guide for Feathr on Databricks](./docs/quickstart_databricks.md) to run Feathr with Databricks.
-- Please read the [Quick Start Guide for Feathr on Azure Synapse](./docs/quickstart.md) to run Feathr with Azure Synapse.
+- Please read the [Quick Start Guide for Feathr on Azure Synapse](./docs/quickstart_synapse.md) to run Feathr with Azure Synapse.
 
 ## 🔡 Feathr Examples
 
@@ -116,7 +123,7 @@ Read [Point-in-time Correctness and Point-in-time Join in Feathr](https://linked
 
 ### Running Feathr Examples
 
-Follow the [quick start Jupyter Notebook](./feathr_project/feathrcli/data/feathr_user_workspace/product_recommendation_demo.ipynb) to try it out. There is also a companion [quick start guide](https://linkedin.github.io/feathr/quickstart.html) containing a bit more explanation on the notebook.
+Follow the [quick start Jupyter Notebook](./feathr_project/feathrcli/data/feathr_user_workspace/product_recommendation_demo.ipynb) to try it out. There is also a companion [quick start guide](https://linkedin.github.io/feathr/quickstart_synapse.html) containing a bit more explanation on the notebook.
 
 ## 🗣️ Tech Talks on Feathr
 

docs/README.md

@@ -33,7 +33,7 @@ Feathr automatically computes your feature values and joins them to your trainin
 
 Feathr has native cloud integration. To use Feathr on Azure, you only need three steps:
 
-1. Get the `Principal ID` of your account by running `az ad signed-in-user show --query objectId -o tsv` in the link below (Select "Bash" if asked), and write down that value (something like `b65ef2e0-42b8-44a7-9b55-abbccddeefff`). Think this ID as something representing you when accessing Azure, and it will be used to grant permissions in the next step in the UI.
+1. Get the `Principal ID` of your account by running `az ad signed-in-user show --query id -o tsv` in the link below (Select "Bash" if asked), and write down that value (something like `b65ef2e0-42b8-44a7-9b55-abbccddeefff`). Think this ID as something representing you when accessing Azure, and it will be used to grant permissions in the next step in the UI.
 
 [Launch Cloud Shell](https://shell.azure.com/bash)
 
@@ -141,7 +141,7 @@ Feathr has native integration with Azure and other cloud services, and here's th
 
 ## Quickstart
 
-- [Quickstart](quickstart.md)
+- [Quickstart for Azure Synapse](quickstart_synapse.md)
 
 ## Concepts
 

docs/concepts/concepts.md

@@ -1,7 +1,6 @@
 ---
 layout: default
 title: Feathr Concepts
-nav_order: 3
 has_children: true
 permalink: docs/concepts
 ---

docs/concepts/feathr-concepts-for-beginners.md

@@ -107,9 +107,9 @@ client.get_offline_features(observation_settings=settings,
 
 ## What is "materialization" in Feathr?
 
-You are very likely to train a machine learning model with the features that you just queried (with `get_offline_features()`). After you have trained a machine learning model, say a fraud detection model, you are likely to put the machine learning model into an online envrionment and do online inference.
+You are very likely to train a machine learning model with the features that you just queried (with `get_offline_features()`). After you have trained a machine learning model, say a fraud detection model, you are likely to put the machine learning model into an online environment and do online inference.
 
-In that case, you will need to retrieve the features (for example the user historical spending) in real time, since the fraud detection model is very time sensitive. Usually some key-value store is used for that scenario (for example Redis), and Feathr will help you to materialize features in the online environment for faster inference. That is why you will see something like below, where you specify Redis as the online storage you want to use, and retrieve features from online envrionment using `get_online_features()` from there:
+In that case, you will need to retrieve the features (for example the user historical spending) in real time, since the fraud detection model is very time sensitive. Usually some key-value store is used for that scenario (for example Redis), and Feathr will help you to materialize features in the online environment for faster inference. That is why you will see something like below, where you specify Redis as the online storage you want to use, and retrieve features from online environment using `get_online_features()` from there:
 
 ```python
 redisSink = RedisSink(table_name="nycTaxiDemoFeature")
@@ -141,4 +141,4 @@ For more details on how to utilize Feathr to perform point-in-time joins, refer
 
 ## Next Steps
 
-After you are familar with the above concepts, please check out the [quick start guide](../quickstart.md) to get your hands dirty. Enjoy!
+After you are familar with the above concepts, please check out the [quick start guide](../quickstart_synapse.md) to get your hands dirty. Enjoy!

docs/dev_guide/dev-guide.md

@@ -1,7 +1,6 @@
 ---
 layout: default
 title: Feathr Developer Guides
-nav_order: 5
 has_children: true
 permalink: docs/dev_guide
 ---

docs/how-to-guides/azure-deployment.md

@@ -13,7 +13,7 @@ Due to the complexity of the possible cloud environment, it is almost impossible
 
 Feathr has native cloud integration and getting started with Feathr is very straightforward. You only need three steps:
 
-1. Get the principal ID of your account by running `az ad signed-in-user show --query objectId -o tsv` in the link below (Select "Bash" if you are asked to choose one), and write down that value (will be something like `b65ef2e0-42b8-44a7-9b55-abbccddeefff`)
+1. Get the principal ID of your account by running `az ad signed-in-user show --query id -o tsv` in the link below (Select "Bash" if you are asked to choose one), and write down that value (will be something like `b65ef2e0-42b8-44a7-9b55-abbccddeefff`)
 
 
 [Launch Cloud Shell](https://shell.azure.com/bash)