Versioning and time travel for Delta Lake tables

To version, time travel, and restore data in Delta Lake, we need to use the Delta Lake library, which provides ACID transactions and other data management capabilities on top of Apache Spark. In this hands-on recipe, we will explore how to accomplish these tasks using Delta Lake in Python.

How to do it...

1. Import the required libraries: Start by importing the necessary libraries for working with Delta Lake. In this case, we need the delta module and the SparkSession class from the pyspark.sql module:

   from delta import configure_spark_with_delta_pip, DeltaTable

   from pyspark.sql import SparkSession

2. Create a SparkSession object: To interact with Spark and Delta Lake, you need to create a SparkSession object:

   builder = (SparkSession.builder

                  .appName("time-travel-delta-table")

            ...