If you want to run a spark job in windows that make use of the spark SQL pool, you need to set the HADOOP_HOME and hadoop.home.dir environment variables manually and there is a very quick and easy solution to do this.
For me, Windows11 is the best shell of Linux. I´m using it in my home and work and for that reason I´m using WSL2 to run my Linux and dev station (python, scala,…), so there is a trick to avoid the problem of the Git credential store in WSL2. The trick is to configure the credential helper of the git inside WSL2 as the windows11 credential helper.
When you work with Azure Machine Learning, you are not required to work with Azure Machine Learning portal. Since Azure Machine Learning libraries supports to work connected with your workspace through the official library, you can benefit from containers to create an entire dev container to develop and deploy your code into Azure Machine Learning Service.
