Databricks Runtime 9.1 LTS is a long-term support (LTS) version of Databricks that includes Apache Spark 3.1.2 and Python. This version is designed for stability and reliability, with updates and bug fixes provided over an extended period.

Key features and information:

• Long-Term Support: Databricks Runtime 9.1 LTS receives long-term support, ensuring stability and reliability for production workloads.
• Apache Spark 3.1.2: This version includes Apache Spark 3.1.2, a popular open-source framework for big data processing and analytics.
• Python Integration: Databricks Runtime 9.1 LTS supports Python for data analysis, machine learning, and other tasks.
• Machine Learning Support: There’s a separate version called Databricks Runtime 9.1 LTS for Machine Learning that includes additional libraries and tools for machine learning workloads.

Using Python in Databricks 9.1 LTS:

You can use Python in Databricks 9.1 LTS notebooks just like you would in any other Python environment. You have access to the standard Python libraries, as well as additional libraries provided by Databricks for working with Spark and other big data tools.

• PySpark: The primary way to interact with Spark from Python is through the PySpark API.
• Pandas API on Spark: If you’re familiar with Pandas, you can use the Pandas API on Spark to work with large datasets in a familiar way.
• Notebook-scoped Python libraries: You can install additional Python libraries using %pip commands in your notebooks.