⏩ Understanding Unity Catalog in Databricks ⏮
In Databricks, the Unity Catalog is a data catalog that allows you to store, access, and manage data within your Databricks workspace. It provides a unified interface for working with data across different sources and storage systems, such as Amazon S3, Azure Blob Storage, and HDFS.
The Unity Catalog provides a number of features to help you organize, discover, and understand your data, including:
💡 A searchable interface for finding specific data sets and tables
💡 A schema browser for exploring the structure and contents of data sets and tables
💡 A data preview feature for quickly previewing the data in a table
💡 Support for external data catalogs, such as Apache Hive and Apache Atlas, allowing you to easily access data stored in external systems
Here is an example of how you might use the Unity Catalog in Databricks:
💡 Connect to a data source: First, you will need to connect to a data source where your data is stored. This can be done through the Databricks UI or through code.
💡 Create a table: Once you have connected to your data source, you can create a table in the Unity Catalog to represent the data. This can be done through the Databricks UI or through code using SQL or the Databricks API.
💡 Query the table: You can use SQL or the Databricks API to query the table and retrieve the data.
💡 Explore the data: You can use the schema browser and data preview features in the Unity Catalog to explore the structure and contents of the data.
💡 Share the data: You can share the data in the Unity Catalog with other members of your Databricks workspace, allowing them to access and query the data as well.
How do give Access to Someone in Databricks Unity Catalog?
💡 CREATE CATALOG ml;
💡 CREATE SCHEMA ml.team_sandbox;
💡 GRANT USE_CATALOG ON CATALOG ml TO ml_team;
💡 GRANT USE_SCHEMA ON SCHEMA ml.team_sandbox TO ml_team;
💡 GRANT CREATE TABLE ON SCHEMA ml.team_sandbox TO ml_team;
💡 GRANT SELECT ON SCHEMA ml.team_sandbox TO ml_team;
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