How to Run Python Script in Azure Databricks
BRIEF OVERVIEW
Azure Databricks is a cloud-based big data and analytics platform that provides an Apache Spark-based environment for running distributed data processing workloads. It allows you to run Python scripts seamlessly, enabling you to analyze large datasets, build machine learning models, and perform other data-related tasks efficiently.
FAQs:
Q: How do I create a new notebook in Azure Databricks?
A: To create a new notebook in Azure Databricks, follow these steps:
- Login to your Azure portal and navigate to the Azure Databricks workspace.
- Select the appropriate cluster or create a new one if required.
- In the left-hand sidebar, click on “Workspace” and then select “Create” > “Notebook”.
- Enter a name for your notebook and choose the programming language (Python).
- Click on “Create Notebook” button.
Q: How can I upload my Python script into an Azure Databricks notebook?
A: To upload your Python script into an Azure Databricks notebook, follow these steps:
- In your newly created notebook, click on the downward arrow next to the folder icon at the top-left corner of the screen.
Figure 1: Folder icon in Azure Databricks notebook
Select “Upload” from the dropdown menu.
Choose your Python script file from your local machine and click on “Open”.
Q: How do I run a Python script in an Azure Databricks notebook?
A: To run a Python script in an Azure Databricks notebook, follow these steps:
- In the cell of the notebook where you want to execute the script, enter or copy-paste your Python code.
- Press Shift + Enter or click on the Run button (triangle) located at the top-left corner of each cell.
Figure 2: Run button in Azure Databricks notebook
- The output of your Python code will be displayed below the executed cell. You can also view logs and errors if any occur during execution.
Q: Can I schedule my Python scripts to run automatically in Azure Databricks?
A: Yes, you can schedule your Python scripts to run automatically using Jobs feature provided by Azure Databricks. With Jobs, you can define recurring workflows that execute notebooks or JARs as tasks. You have options to specify the frequency, start time, and other parameters for your scheduled jobs. This allows you to automate data processing tasks and ensure regular execution of your Python scripts.
BOTTOM LINE
Azure Databricks provides a powerful platform for running Python scripts in a distributed environment. By following the steps mentioned above, you can easily create notebooks, upload your Python script files, execute them, and even schedule their automatic execution using Jobs feature.
