Reading CSV data with Apache Spark

Reading CSV data is a common task in data engineering and analysis, and Apache Spark provides a powerful and efficient way to process such data. Apache Spark supports various file formats, including CSV, and it provides many options for reading and processing such data. In this recipe, we will learn how to read CSV data with Apache Spark using Python.

How to do it...

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

   from pyspark.sql import SparkSession

   spark = (SparkSession.builder

       .appName("read-csv-data")

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

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

       .getOrCreate())

   spark.sparkContext.setLogLevel("ERROR")

2. Read the CSV data with an inferred schema: Read the CSV file using the read method of SparkSession. In the following code, we specify...