4. DML Delete Truncate Merge with SCD2

This video focuses on advanced Data Manipulation Language (DML) operations in Spark SQL, including deleting and truncating data, performing merges, and implementing Slowly Changing Dimensions (SCD) Type 2. Here's an explanation of each concept:
1. Delete Operation
Purpose: Used to remove specific rows from a table based on a condition.
Use Case: Cleaning up obsolete or irrelevant data without impacting other rows.
Example Application: Removing records for inactive users in a user management system.
2. Truncate Operation
Purpose: Deletes all rows in a table quickly and efficiently while preserving the table structure.
Difference from Delete: Truncate does not allow conditions and is faster because it does not log individual row deletions.
Use Case: Clearing out data from temporary or staging tables.
3. Merge Operation
Purpose: Combines data from two sources by performing insert, update, or delete operations in one step.
Key Features:
Matches rows between a target table and a source dataset.
Allows condition-based updates and inserts for unmatched rows.
Use Case: Keeping a table in sync with incoming updates, such as loading new transactions into a customer database.
4. SCD Type 2 (Slowly Changing Dimensions Type 2)
Purpose: A method for managing historical data in dimensional modeling.
How It Works:
Tracks changes to data by creating a new row for each change instead of updating or overwriting existing data.
Maintains the full history of changes.
Typical Attributes:
Effective Date: When the change becomes valid.
Expiry Date: When the change is no longer valid.
Is Current: Flags the current active record.
Use Case: Capturing changes in customer information (e.g., address changes) to maintain a historical trail.
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