Handling null values with Apache Spark

Handling null values is an essential part of data processing in Apache Spark. Null values are missing or unknown values in a dataset that can affect the analysis and modeling process. Apache Spark provides multiple ways to handle null values to ensure data quality and data integrity. In this recipe, we will discuss how to handle null values in Apache Spark using Python.

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 explode, col, when

   spark = (SparkSession.builder

       .appName("handle-nulls")

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

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

       .getOrCreate())

   spark.sparkContext.setLogLevel("ERROR")

2. Read file: Read the nobel_prizes.json file using the...