Delta Time Travel
Explore how Delta Lake's time travel functionality in Databricks lets you view and restore previous versions of a Delta table. Understand how to check version history, query past data snapshots nondestructively, and recover from mistakes by restoring tables to earlier states using PySpark and SQL commands. This lesson teaches essential techniques for managing reliable, versioned data in a Lakehouse environment.
Delta Lake records every change made to a Delta table as a numbered version. Every time you write to a Delta table, whether you insert rows, update values, or delete records, Delta saves the previous state and assigns a new version number starting from 0.
Time Travel lets you read the table as it looked at any past version, without changing the current state. You can also fully restore the table to a previous version when you need to undo a mistake. The key distinction to keep in mind throughout this lesson: reading a past version is non-destructive (the table is unchanged); restoring permanently changes what the table looks like for all future queries.
In Databricks Community Edition, time travel works for managed Delta tables, and you don’t need to worry about file storage paths.
Why time travel is useful
Imagine this scenario:
Your
salestable has 100 rows, including a row for Alice with a sales value of150.Someone accidentally runs an
UPDATEthat sets Alice's sales to0.Without Delta, that original value would be gone permanently. ...