Merging data into Delta tables

In this hands-on recipe, we will learn how to merge data into a table using Delta Lake in Python. It provides powerful capabilities to perform updates, deletes, and merges on data stored in a Delta table, making it an excellent choice for managing big data workloads with data integrity and reliability.

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("read-delta-table")

       .master("spark://spark-master:7077")

       .config("spark.executor.memory&quot...