Performing joins with Apache Spark

In this recipe, we will discuss how to perform joins between DataFrames in Apache Spark. We will use Python as our primary programming language and the PySpark API and go over the various types of joins we can perform in Apache Spark.

How to do it...

1. Import the libraries: Import the required libraries and create a SparkSession object:

   from pyspark.sql import SparkSession

   from pyspark.sql.functions import broadcast

   spark = (SparkSession.builder

       .appName("perform-joins")

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

       .config("spark.executor.memory", "512m")

       .getOrCreate())

   spark.sparkContext.setLogLevel("ERROR")

2. Create the DataFrame: We will start by creating the datasets for cars, customers, transactions, and fraud:

   cards_df = (spark.read.format("csv")

       .option("header&quot...