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Databricks offers a powerful unified analytics engine that allows users to build FT data pipelines across batch and streaming data. It also allows you to automate these data pipelines using SQL. In this blog post, we will learn how to automate jobs using Databricks SQL and scheduling them to run at specified intervals using Databricks’ job scheduler.
Getting Started
Before you can create SQL jobs in Databricks, be sure to have a pre-existing SQL query that you want to automate. For this example, we will use a simple SQL query that retrieves all data from a dummy database table named ‘Employee’.
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SELECT * FROM Employee |
Scheduling SQL Jobs
To create a new SQL job and schedule it in Databricks, follow the steps below:
Step 1: Creating a New Job
On the Databricks Workspace, navigate to the ‘Jobs’ tab and click on ‘Create Job’. Give your job a name, e.g., ‘Employee Data Extraction’.
Step 2: Setting the SQL Query
Next, you will want to specify the SQL query that the job will execute. Navigate to the ‘Tasks’ tab and select ‘SQL’ as the job task type. Then, paste the SQL query from above:
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SELECT * FROM Employee |
Step 3: Scheduling the Job
Now it’s time to schedule your job. In the ‘Schedule’ tab, click on ‘New Schedule’. Set the time and interval according to your needs. For example, to run the job every day at 12.00 AM, select ‘Daily’ in the ‘Repeat’ drop-down menu, and set the ‘Starting’ date and time accordingly.
Conclusion
We have covered the basics of Databricks SQL automation and job scheduling. Remember, the SQL capability in Databricks is powerful and extends beyond basic SELECT queries. With practice, you can automate complex data analytics workflows with sophisticated SQL queries. Happy coding!